EARTH SCIENCES CENTRE
GÖTEBORG UNIVERSITY
B296 2001
TEXTURE AND NUTRIENT STATUS IN THE
TOPSOIL SIX YEARS AFTER LOW AND
HIGH INTENSITY WILDFIRES,
NE CATALONIA, SPAIN
Elisabeth Simelton
Department of Physical Geography
GÖTEBORG 2001
GÖTEBORGS UNIVERSITET
Institutionen för geovetenskaper
Naturgeografi
Geovetarcentrum
TEXTURE AND NUTRIENT STATUS IN THE
TOPSOIL SIX YEARS AFTER LOW AND
HIGH INTENSITY WILDFIRES,
NE CATALONIA, SPAIN
Elisabeth Simelton
ISSN 1400-3821
Postadress
Centre Geovetarcentrum
S-405 30 Göteborg
B296
Projketarabete
Göteborg 2001
Besöksadress
Geovetarcentrum
Guldhedsgatan 5A
Telefo
031-773 19 51
Telfax
031-773 19 86
Earth Sciences
Göteborg University
S-405 30 Göteborg
SWEDEN
Abstract
The forest wildfire frequency in Mediterranean high risk-areas is increasing. One way to
prevent wildfires is regular prescribed burning. The research on post-fire soil processes often
ceases after the first critical 2-3 years, whereas the post fire effects generally last longer. This
study compares the cation content, mineralisation and texture in the 3 cm topsoil of two
Xerochrepts (Catalonia, NE Spain) six years after a wildfire in a mixed stand of Pinus
pinaster and Quercus suber with a similar unburned forest. In all 90 topsoil samples were
analysed for Ca, Mg, N, K, pH, conductivity, C, N and texture.
The results show that six years after the fire there were still some significant differences
between burned and unburned zones, as well as between the high and low intensity fire sites.
Although the mineralisation (C:N) ratios were similar to unburned forest, the N- and organic
C contents were significantly lower in the burned zones. The post fire augmentation of plant
available soil nutrients remained longer in the low intensity soil than the higher. Despite
previous erosion and outwash, the textural class, sandy loam, remained.
The post-fire vegetation species were similar in but faster regrowth in the low intensity.
Assuming that the low intensity fire equals a prescribed burn, the implication would be that
although the revegetation makes a fire risk, more than six years between fires are required to
recover this topsoil.
KEYWORDS: forest fire, soil, Spain, Catalonia, Pinus, Quercus, prescribed burning
ISSN 1400-3821 B 296(2001)
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List of contents
Fel! Bokmärket är inte definierat.
Abstract................................................................................................................................................... 1
Foreword................................................................................................................................................. 4
Acknowledgement ................................................................................................................................. 4
1 Introduction..................................................................................................................................... 5
Causes of Mediterranean fires ......................................................................................................... 5
Wildfire prevention, prescribed burning ............................................................................................ 5
Consequences of fires ...................................................................................................................... 6
2 Background..................................................................................................................................... 8
Wildfire types ........................................................................................................................................ 8
Short term fire effects on the soil ......................................................................................................... 9
Fire intensity ................................................................................................................................... 10
Classification of wildfires ................................................................................................................ 10
Water repellence (hydrophobicity) and aggregates........................................................................ 11
(Top-)soil recovery processes ............................................................................................................ 12
The season of the fire and the frequency of intense rain storms ................................................... 12
The fire intensity ............................................................................................................................. 13
The ash, and hydrophobicity........................................................................................................... 13
The nutrients and the duration of their effects ................................................................................... 13
pH, conductivity, carbon, nitrogen .................................................................................................. 13
Biological activity and revegetation ................................................................................................ 14
Human impacts............................................................................................................................... 14
3 Objective........................................................................................................................................ 15
4 Site description............................................................................................................................. 16
The fire site in Llagostera, July 1994-May 2001 ................................................................................ 19
5 Methods ......................................................................................................................................... 22
6 Results........................................................................................................................................... 24
Texture 2001 ...................................................................................................................................... 24
Structure 2001.................................................................................................................................... 25
pH and conductivity 2001 ................................................................................................................... 25
Macro nutrients................................................................................................................................... 25
Potassium, calcium, magnesium, and sodium 2001 ..................................................................... 26
Calcium, magnesium, potassium, and sodium 1994-2001............................................................. 27
Mineralisation (carbon, nitrogen)........................................................................................................ 28
C and N-contents, C:N-ratio 2001 .................................................................................................. 28
N, C, and C:N-ratio 1994-2001....................................................................................................... 29
Terrace levels 2001............................................................................................................................ 29
7 Discussion..................................................................................................................................... 31
Methods.............................................................................................................................................. 31
Biological activity ................................................................................................................................ 32
The organic matter.......................................................................................................................... 32
Mineralisation (C, N) ....................................................................................................................... 33
Nitrogen .......................................................................................................................................... 34
Physical processes............................................................................................................................. 34
Texture............................................................................................................................................ 34
Structure: aggregations and layers................................................................................................. 35
Chemical processes ........................................................................................................................... 36
pH ................................................................................................................................................... 36
Calcium, magnesium, potassium.................................................................................................... 36
Sodium & conductivity .................................................................................................................... 37
New fire risks and future research ..................................................................................................... 38
8 Conclusions .................................................................................................................................. 39
References............................................................................................................................................ 40
Appendix 1 Ca, Mg, Na, K; texture; pH, conductivity, and C:N, 2001 .................................................. 43
Appendix 2 Topsoil description, 1996................................................................................................... 47
Appendix 3 Laboratory analysis............................................................................................................ 48
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Foreword
This study was part of a Master’s degree in Physical Geography at the Earth Sciences Centre,
Göteborg University, Sweden. The fieldwork and laboratory analysis was carried out at the
Department of Physical Geography/ Faculty of Geography and History, Barcelona University,
Spain in collaboration with the Mediterranean Environment Research Group (GRAM). The
length of the study and stay in Catalonia was two months, May-June 2001.
Acknowledgement
At the Department of Physical Geography at Barcelona University, I would like to express my
gratitudes to Prof. Maria Sala who received me without hesitation. Ph D Xavier Ubeda and
Ms Sara Bernia have been invaluable guides to all kinds of information and practical work.
¡Moltas moltas graçias! Ph D Montserrat Salva not only opened the door to her house.
Together with Prof. Josep Maria Panareda, she also took me on unforgetable tours to the
Catalonian jungle. Graçias also to Mr Carlos Rubio who provided the weather data, and to Ms
Lourdes Reina who shared valuable information and a computer with me. Thanks are due to
Grup Recerca Ambiental Mediterrania (GRAM) and Barcelona University for letting me use
the laboratory. A special thank you to Mr Jesus Perna, for the geological excursions, they
were great experiences! ...and thank you all for the music...
At the Department of Physical Geography at Earth Sciences Centre, Göteborg University, as
always, Dr Margit Werner again has proven that everything is possible – including cutting out
text from a thesis. Dr Björn Holmer kindly helped out with statistics. Ms Anita Malm
formatted the maps. Tusen tack for all the help and support!
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1
Introduction
Each year about 50.000 fires sweep through 700.000-1.000.000 ha of Mediterranean forest
(Velez 1997:15) resulting in ecological and socio-economic costs (Kalabokidis 1999). The
area affected by fires has tripled between 1960-1985, from 200 000 to 600 000 ha, and from 1
300 fires/year to 9 000 (Conacher & Sala 1998:206). It is not specified how big this share is.
As one reference, between 1973-1998 in Catalonia, NE Spain, wildfires affected land areas,
which are equal to 14 % of the autonomy. One of the 1 217 Catalonian fires during the peak in
1994, was the Llagostera-fire (see this study), which affected 55 ha forest of the total 76 625
ha land that burned (Panareda & Arola 1999:44; Ubeda 1998) (fig 6b).
The research on forest fires and post-fire soil processes is often on a short-term basis, whereas
the effects of fire on soil and vegetation may last at least 10-50 years (Giovannini 1994), and
still be detected after 140 years (Driscoll et al. 1999). The aim of this study is to follow up on
previous research (Ubeda 1998) and compare some common soil parameters six years after a
wildfire in Llagostera, NE Spain, in order to see what has happened in the soil after two
different fire intensities.
Causes of Mediterranean fires
There are natural and human causes to fires. The main natural causes are lightning, volcanic
eruptions, and sparks from falling rock boulders (Goudie & Viles 1997). The increasing fire
frequency in the Mediterranean areas has been ascribed the recent increase in dry years (see
fig 4, 5), and particularly human intentional and accidental impacts. In Spain, e.g. EU
livestock subsidies have favoured pastoral land use, where fires are used for maintaining
herbage for fodder (Velez 1997). The fire risks have increased due to: other Common
Agricultural Policies, e.g. to set aside productive land to fallow, or to plant fast-growing
species, (Sala & Coelho 2000:23); low appreciation for forest maintenance (Sala pers. comm.
2001) due to a decreasing profitability and a falling tendency of using forestry products for
raw material; insurance speculation (Conacher & Sala 1998); depopulation of rural areas,
urbanisation, and an increasing use of forested areas for recreation (Velez 1997). Similarly to
the rest of Spain, the Catalonian fires are related with roads, settlement (Conacher & Sala
1998:314-317) and with a drier climate in the 1980s (Velez 1997:15-16).
Wildfire prevention, prescribed burning
Some examples of smaller scale natural fire breaks from Australia and the United States are
ponds, marshes, stony areas, summer green or sappy plant crops and hedgerows, compost
litter in swales, plant inflammable trees on ridge tops (Mollison 1988:451-455). The common
alternatives to minimise the wildfire hazards in the Mediterranean area are to slash the
undergrowth manually, which is costly, app. 160 000 pesetas/ha (app. SEK 8 000/ha) (Sala
pers. comm. 2001), or to have animals grazing, which cause erosion and disturb the regrowth
(Mazzoleni & Esposito 1993). Prescribed burning is a widespread method to reduce the fire
risks in many parts of the world, particularly to protect living areas (Goudie & Viles 1997:2032).
Prudent prescribed burning programmes have potential to replace the destructive wildfires
(Kalabokidis 1999:6). Although prescribed burning is a controlled low temperature fire under
suitable weather conditions, there is a conflict between fire hazard and soil conservational
5
aspects. For example, meanwhile tree litter protects against rain splash erosion and overland
flow, it can infest pests and increase the amount of combustible fuel (Shakesby et al.
1996:350). Some drawbacks are that prescribed burning needs to be done repeatedly with fire
brigade and forest guards involved, which makes it expensive (Sala pers. comm. 2001).
Moreover, cool burns open up canopy and under storey, which allows the germination of
invasive grass and weed and increases the fire risk (Conacher & Sala 1998:314). Moreover,
the fire excavated the trunks of old Scots pines with cavities after fungi and/or insects tree.
However the increased mortality could itself be consequence of that the forest had not been
burnt for a long time (Linder et al. 1998).
Prescribed burning is carried out with 5-10 year intervals in the United States and Australia. It
is obligatory on mountain catchments in South Africa. In Italy light fires keep a temperature
of 180-200 ˚C (Conacher & Sala 1998:314-317). In Spain the local governments have the
legislative power to allow prescribed burning. Consequently the prescribed burning
management varies and there is some debate about the harms and goods of this method.
Consequences of fires
Besides fauna, humans and infrastructure, fires have affects on soil, water, air, and naturally,
the vegetation.The Mediterranean forests are generally located on steep slopes with young,
thin soils, which can cause appreciable physical and chemical degradation after forest fires
(Andreu et al. 1994:80). By extinguishing some vegetation, fires can make soil nutrients
available to new plants. However, a certain part of the nutrients is lost in volatilization during
the fire (Goudie & Viles 1997; Raison et al. 1993), through run off and soil erosion, related to
the first post fire rain-period when the soil is unprotected. Some longer term consequences of
soil loss are siltation in catchments and land degradation (Ubeda & Sala 1998).
On the other hand, biodiversity may increase in stands where fires occur, because fires assist
in seed germination, alter seedbeds by removing litter, competitive seeds and toxic substances
in the soil, and by raising the pH (ibid 1997). Although, biodiversity favours the long term
stability of the habitat (Goudie & Viles 1997), two critical temporal parameters are the
frequency (Raison et al. 1993) and intensity (Giovannini & Lucchesi 1993) of the fire. In
many studies there appears to be some presupposition that forest soils can recover to pre-fire
rates sooner (Carballas et al. 1993; Giovannini 1994:25), notably often within 3 years, or later
(Raison et al. 1993). Some find no difference between fire intensities after a few years (LuisCalabuig & Tarrega 1993). Others (Albaladejo et al. 1998) conclude after 55 months study,
that the deterioration of vital soil properties appeared to be irreversible. Repeated fires may
change the natural vegetation totally (Raison et al. 1993). In place of a forest, a mosaicpatterned (Thanos 1997) maquis vegetation has become widespread. This type of flora
consists of xerophilous evergreen bushes and shrubs with thick foliage and trunks, which
normally are obscured by low-level branches. It includes plants that send up suckers from
ground level after burning (Goudie & Viles 1997:32), resprout and reseed from soil banks
(Thanos 1997), or are encouraged by fire (Goudie & Viles 1997:32; Folch i Guellen 1981).
Some species will be introduced in the next chapter.
The patchy vegetation creates an irregular combustion, where the ash not only may seal the
soil surface by causing hydrophobic (water-repellent) layers of accumulated ash, organic, and
eroded mineral material (Ubeda 1998; Giovannini 1997; Pradas et al. 1994), but also increase
soil aggregation (Giovannini 1997). In arid zones this affects on hydrology and groundwater
recharge. Firstly because water is lost by surface runoff, and secondly, more water is lost
through evaporation of bare soils than from vegetative transpiration (Sandström 1998).
6
In summary, the present understanding of fire processes is good enough to produce computer
simulation programs, like Farsite and Nexus (www.fire.org). However, the available data on
the effects of fire on the soil is limited (Giovannini 1997:217), particularly after wildfires and
the development of soil properties for a long period (Carballas 1997:250). Moreover, due to
e.g. irregular vegetation and rainfall patterns, research experiments may show higher
variability within one plot than between plots (Shakesby et al. 1996), hence be difficult to use.
Research on fire effects is of great importance because it provides a feedback to other
activities: as fire prevention, fire fighting planning, and rehabilitation of burned areas (Viegas
1997:11).
7
2
Background
Below is a background, firstly to different types of wild fires. Then, some further short-term
effects of fires according to fire intensities and a classification of wildfires. Water repellence
is explained, followed by a compilation of research on forest fire effects over longer periods
(see table 1), and finally, factors that determine the recovery process in Mediterranean areas.
Wildfire types
Fire is a vague term (Viegas 1997:11) on a very complex phenomenon (Giovannini
1997:218). Three elements are necessary for a fire: heat, combustible fuel and oxygen. The
Table 1. Some studies on the changes in soil nutrients after Mediterranean wildfires lasting
longer than 3 years.
Author
Length of
study
Focus of study/Method
Driscoll et al. 1999
> 140 years
Soil-N
Faraco et al. 1993
1-16 years
Legrand 1993
15 years
Raison et al. 1993
14 years
Andreu et al. 1994
14 years
1974-1988
Thanos 1997
10 years
Carballas et al. 1993 10 years
Cerda 1998
Luis-Calabuig &
Tarrega 1993
Mazzoleni &
Esposito 1993
Shakesby et al.
1994; Shakesby et
al. 1996
Tartaglini 1993
6 years
1990-96
5 years
4 years
1988-1992
3 years
1986-89
3 years
1989-91
Soiltype/Area
Spruce forest.
British Columbia,
Canada.
Reveg species and diversity Soil not mentioned
C Spain
P. pinaster & Cytisus.
Wildfire
Sandstone.
Cistus, Erica. Wildfire &
prescribed burning
France
Repeated low intensity
Australia
fires, nutrient cycles N&P.
Chemical properties of
Calcareous
runoff sediment
Rendzina-Lithosol.
Valencia
Revegetation Cistus, Pinus E Mediterranean
Field and laboratory
Organic matter, N, P,
Cambisols
microbial evolution wildfire NW Spain
Revegetation, soil moisture. Calcareous loams.
Rain simulation.
Valencia, Spain.
Regeneration Q. pyrenaica Soil not mentioned.
soil samples. Wildfire
Leon, NW Spain
Vegetation regrowth
Pyroclastic,
macchia species.
dolomite, calc &
Experiment plots
sandstone.
S Italy, Corfu
Post fire management,
Schist.
Portugal
Pinus pinaster and
Eucalyptus globulus.
Mycorrhizae and post-fire
Calcareous soil.
succession. Wildfire
Tuscany
8
main factors determining fire dynamics are precipation, temperature and time of the day,
relative humidity, wind, topography and orientation, vegetation characteristics and soil water
content (Panareda & Arola 1999:30-37). However, their relative importance varies (Turner et
al. 1999). Three regimes of fire propagation according to fuel layers are involved in the
combustion process: ground fire, surface fire, and crown fire. The type of fire is related with
fire intensity and the classification system (see the next two paragraphs and fig 6b).
Ground fires burn the organic layer above the mineral soil without flame. Usually the
propagation is slow and cause little threat to upper layers of the vegetation cover. If not
carefully extinguished, these fires may rekindle. Surface fires are the most common. A wide
class of vegetation litter, dead and live fine fuels at or near the soil surface may be lost in a
flaming combustion. Crown fires are extended to the upper layers of the crown foliage. In
weak wind the convection column above the fire causes a horisontal downward flow that
entrains air into the combustion at ground level. In stronger winds the fire is vertically
extended and spreads quickly. This convective process makes topography and vegetation
relatively less important. Crown fires often burn in heterogenous patterns and may cause
secondary spot fires (Viegas 1997; Farsite).
Short term fire effects on the soil
There have been studies on the short term effects of heating on soil chemical quality
(Giovannini 1997; Raison et al. 1993), on soil hydrology and physical erosion (Sala et al.
1993; Ubeda 1998; Cerda 1998), on water repellency (Robinchaud & Hungerford 2000;
Singer & Le Bissonais 1998), regeneration of vegetation (Cerda 1998; Turner et al. 1999) and
fauna. Various rain fall simulation experiments have been carried out (Shakesby et al. 1994;
Boix-Fayos et al. 1998; Singer & Le Bissonais 1998) and the implications of laboratory
analyses and simulations for spatial and temporal variations discussed (Lascelles et al. 2000).
Few of the studies are integrated and discuss long term processes (tab 1).
Fig 1. Simplified model over amounts and patterns of fuel accumulation and fuel nutrients.
Note: many factors are excluded, e.g. topography, soil texture changes. (Modified after
Raison et al. 1993:347-363 and Inbar et al. 1998).
The ways which fires modify the soil nutrients are complex (fig 1). The interrelations and
their durations are not easily monitored in terms of cause and effects. The main processes are:
(1) transformation of nutrients from organic to inorganic forms, (2) nutrient transfers to
atmosphere in smoke (volatilisation), (3) erosion of ash and nutrient-rich surface soil, (4)
change in nitrogen-fixing systems, (5) modification of decomposition rates of litter and soil
organic matter (Raison et al. 1993:347; Panareda & Arola 1999:39-47).
9
Fire intensity
The intensity of the fire affects the soil, soil nutrients and their availability (Giovannini 1997;
Raison et al. 1993). To enable comparisons, fire effect studies must include a characterisation
of the fire situation that occurred (Viegas 1997:11).
The temperature scale below is based on a compilation of 27 studies of temperature effects on
topsoils by Ubeda (2000), and many experiments by Giovannini (1993, 1994, 1997). The
physical and chemical processes are explained more closely in this chapter under the section
The nutrients and the duration of their effects.
Temperature °C
50-60
100
100-200
200-300
300
315
315-400
400-550
550-700
700-900
Impact on soil
Lethal for plant protoplasma.
N-compounds decompose.
Lethal for bacteria in fungi. Water evaporise.
Loss: 50 % of the N. Decreasing: pH-value, soil´s water adsorption
capacity, plasticity. Some organic matter components dissappear.
Increasing: sand fraction, ammonium, P, Ca, Mg and Na, as well as
water repellence.
Disputed: increase or decrease of structural stability and porosity.
Organic matter reduce to ash. Hydrophobic surface formation.
Increase: pH. Decreasing: cation exchange capacity (CEC).
Loss: 75 % of the N.
Decreasing: water absorption capacity and plasticity, Ca, Na, and Mg.
Loss: NH4, all organic carbonate residues. Increasing: K. Water
repellence peaks.
Loss: organic matter totally destructed, OH-compunds of clays.
Decreasing: structural stability. Increasing: pH, P, K.
Soil oxidation. Loss: irreversible changes of clays. Carbonates
decompose. Decreasing: K. Increasing: Ca, Mg, water absorptivity.
The thermal reaction of soils to increasing heat can be summarised in three steps:
< 220 °C, 220 – 460 °C and > 550 °C. The lower temperature dehydrates soil and gel
complexes, promotes solubility of cations while soil physical properties are intact. The
medium temperature can be chemically beneficial if soil organic matter is restored in few
years, but physical qualities begin to deteriorate. Above 460 °C both physical and chemical
alterations makes the soil an erosion hazard (Giovannini 1994:15-28).
Classification of wildfires
When wildfires occur, it is often too late to measure the exact temperatures. Instead, the
classification of fire intensity can be based on combustibility rates, as evidenced by the colour
of ash. Black ash corresponds to temperatures below 177°C and white ash to temperatures
above 400°C in the subsoil and 510°C in the topsoil (Ubeda 2000:119 cites Bentley & Fenner
1958). Below is a general description according to this method. The following sentences states
how the fire intensities in this study were classified in 1994. For comparison the unaffected
control forest had a 3 cm layer of humus, decomposed and undecomposed leaves (fig 6, 7).
1. Low intensity: The trees maintain some leaves, most branches and fine to very fine
twigs. A lot of unburnt, undecomposed leaves cover the soil. Black ash. In Llagostera
10
Quercus suber and some Pinus pinaster survived. Patches of black ash deposited in
the leaves still remained 2 years after the fire (Ubeda 1998). Slope aspect: southeast.
Position: foot slope and back slope.
Fig 2. Some pines left in the wildfire valleys in Llagostera six years after low intensity fires
(to the left) and high intensity on the crest in the centre. The left valley faces southwest and
the crest faces south (see fig 6b). Photo: Simelton May 2001.
2. Medium intensity: The trees lose most leaves; a number of branches are intact. Few
undecomposed leaves. In Llagostera patches of black ash remained for 30 months.
Slope aspect: south. Position: back slope below high intensity, perpendicular to (east
of) the low intensity zone. The medium intensity is not included in this study.
3. High intensity: Some tree trunks are conserved, but all branches and leaves are lost.
White ash. In Llagostera, contrary to the less intensity zones, Arbutus unedo was lost
and the soil surface totally unprotected. Grey and white ash covered the entire soil and
disappeared quickly after the first rains. Slope aspect: south. Position: shoulder above
medium intensity.
Water repellence (hydrophobicity) and aggregates
After a fire, soils lose their plasticity and become more water resistant (Giovannini 1994;
Diaz-Fierroz et al. 1994:172). The degree of water repellence depends on the temperature near
the soil surface, the soil water content and the soil’s physical properties (ibid; Balabanis et al.
1997; Giovannini & Lucchessi 1993). There appears to be different types of water repellency
induced by fire (Giovannini 1994:24):
In Llagostera for example, the ash remained on the soil surface and clogged the soil pores.
The half-calcinated black ash did not dissolve in water, and was considered more waterrepellent than the white, totally mineralised, ash. This ash was washed away with the first
rains (Ubeda 1998). In another case, an ash-seal was formed after the rainfall.This happened
11
sooner and faster on an initially dry soil compared to a wet, because dry aggregates slaked
quicker by the rain drop impact and formed a new surface layer with less permeable
microaggregates (Boix-Fayos et al. 1998). Moreover, ash is an important component of:
Aggregates, i.e. hydrophobic colloids, coagulate faster and easier than hydrophilous because
strong hydration (colloids bound by the attraction between water molecules) counteracts
coagulation of clay particles joined in bigger units (Wiklander 1976:90-91). Another type of
hydrophobicty involves accumulation layers in the subsurface (Giovannini, 1994; Pradas et
al. 1994). During a fire, a solution with hydrophobic organic substances penetrates
downwards and until they condense on the cooler soil and organic colloides, accumulate and
form a hydrophobic layer (Balabanis et al. 1997; Giovannini, 1994; Robinchaud &
Hungerford 2000).
(Top-)soil recovery processes
The duration and rates of fire effects are interrelated and determined by many factors.
The effects on soils after the fire can vary from minutes to several years or more (Raison et al.
1993; Driscoll et al. 1999; Mollison. 1988:451). Luis-Calabuig & Tarrega (1993) argue that
the correlation between time and soil variables is always negative and within two years there
were hardly any differences between different fire intensities. Alcañiz et al (1996:129)
concluded that often the indirect effects of fires have more serious consequences on soil than
the fire itself.
To assess the recovery time of fire affected soils, scientists often use the pre-fire status
(Giovannini & Lucchesi 1993; Dimitrakopoulos & Martin 1994) or a control forest as a
reference (Carballas, 1993; Ubeda, 1998). As mentioned earlier, the longer term studies are
more often on revegetation, and rarely include soil types. Soil scientists, on the other hand,
often focus on 2-3 year changes in aspects of soil nutrients, hydrology etc, irrespective of
regrowth. Studies of textural changes after fires are frequently related with aggregates, runoff
and erosion sediments (ibid; Pradas et al. 1994; Boix-Fayos et al. 1998) rather than the in situ
soil. Below is an attempt to relate some of the parameters, e.g. fire intensity, parent material,
location, soil and ash erosion, leaching, the loss of organic matter, texture, hydrophobicity, the
sterility of the environment, age of the stand; that might be critical after the initial 2-3 years of
post fire topsoil recovery.
The season of the fire and the frequency of intense rain storms
The postfire weather determined the soil erosion and runoff rates at least two years after the
fire (Ubeda 1998), and influenced the speed of revegetation (Thanos, 1997). The return to prefire levels varied for different seasons. Regeneration processes were slower after rain and in
soils with high moisture content than in dry soils because the heat penetrates faster and deeper
in moist soils compared to dry and destroys microbiota (Dimitrakopoulos & Martin
1994:207). The location matters. In SW Spain the highest runoff erosion rates were during the
first winter with low intensity rain (Cerda 1998), whereas the highest rates in NE Spain
followed heavy summer and autumn rains the first and the third years (Ubeda 1998).The soil
erosion increased drastically during the first rain fall due to hydrophobicity and aggregation as
well as the lack of pine needle carpet to absorbe the rain drops. The relationship between
erosion and rainfall were more profound in the higher fire intensities as well as in higher rain
intensities (ibid) .
12
The fire intensity
Although soils return to their initial temperature within few hours after the heating stopped
(Dimitrakopoulos & Martin 1994:212) the fire intensity influence the post-fire processes
(Giovannini 1997). Erosion continues due to: e.g. hydrophobic layers, aggregation, or the lack
of organic matter. After one year the soil erosion (kg/ha) was ten times greater after the
severe fire compared to the light fire, and 50 times greater than the control plot (Giovannini &
Lucchesi 1993). After 2,5 years the erosion rates were still fluctuating at a level slightly
higher than those of the control forest (Ubeda 1998). The different combustibility rates
influenced the soil chemical composition at least 10 years after the fire (Carballas et al. 1993).
The ash, and hydrophobicity
Ash is an important new substance that differs burned soils from unburned. The concentration
of elements in ash is high. The fine ash (grey or white) contains high amounts of P and cations
(Raison et al. 1993), especially Ca and Mg (Alcañiz et al. 1996:116). However, nutrients are
lost through volatilisation, erosion, and leaching. The potential for nutrient export by erosion
of ash and surface soil after fire greatly exceeds that for leaching losses (Raison et al. 1993).
On the other hand, electrolytes from the ash-leaches might cause flocculation of the clay
fraction and reduce erosion (Giovannini 1994, ibid 1997). Moreover, when a hydrophobic
layer impedes the infiltration, the water flows laterally and takes away soil particles from the
upper layer (ibid). Once the topsoil is removed by erosion, the hard sub layer may be more
resistant so that soil loss declines over time (Morgan 1995:115).
The nutrients and the duration of their effects
The plant nutrients normally occur in three forms: 1) in soil solution, 2) in exchangeable form,
and 3) in non exchangeable forms. Of the soil nutrients, particularly Ca, Mg, K, and P are in
the exchangeable mode (Wiklander 1976:178-180). Feldspar is one source of Ca and K, and
biotite of Mg and K (ibid: 180-196; Mollison 1988:190-193). The amounts of P, Mg, K, and
Ca released by the burning of vegetation are high in relation to both the total and the available
quantities of these elements in soils (Goudie & Viles 1997). However, only 10-30 % of the
cations from ash are easily dissolved in water and leached from the topsoil into the mineral
soil, kept in the exchange complex, or transported away (Alcañiz et al. 1996:127). It can be
difficult to deduct soil nutrients simply as consequences of fires. On one hand, soil properties
are also positively related to other factors, such as organic matter and clay content are to
gradient (Boix-Fayos et al. 1998), or erosion to rain (Ubeda 1998). On the other hand, fires
may accentuate the natural erosion.
pH, conductivity, carbon, nitrogen
The soil pH may fluctuate for 5-50 years and conductivity for 10 years, because the crude ash
is incompletely incorporated to the soil (Giovannini 1994), the cations are leaching, or new is
humus formed (Carballas, 1997:251).
The carbon and inorganic nitrogen contents were similar in burnt and unburnt forests in NW
Spain after 2 and 5 years respectively. The soil enzymatic activities increased slowly and
progressively after two years. After five years there was a considerable increase and after ten
years the levels were similar to the undisturbed forest (Carballas et al. 1993), however there is
no description of fire intensity. The availability of N may decrease due to fires (Alcañiz et al.
1996:127). Ubeda (1998) found that the N-values increased but were not related to fire
intensity. The cover and the type of post fire succession influenced the soil-N at least for 140
years in Canada (Driscoll et al. 1999). The losses of N and P are replaced naturally by rain,
13
which may take 11 and 20+ years respectively (Mollison 1988:451-455, cites Ecos 42,
Summer 85/85). Moreover, the N-balance is indirectly affected by changes in the Pavailability. Most fire-prone ecosystems rely on N-fixing species to replenish N. The inputs of
available P increases with fire intensity, however if regular fires deplete P, the efficiency of
N-fixing systems may decline (Raison et al. 1993).
Biological activity and revegetation
The loss of vegetation is critical for soil recovery processes (Pradas et al. 1994). (1) Trees,
shrubs and herbs attenuates the energy supplied by rain. The interception capacity of pine
trees can range up to 25-35 % of the rainfall (Shakesby et al. 1994). (2) The accumulating
litter layer of branches, bark and leaves similarly absorbes raindrops and furthermore slows
runoff (ibid). (3) Irregular microtopography may increase infiltration and consequently reduce
runoff, such as provided by cryptogams (ibid), or pine needles (Ubeda & Sala 1998). Rain fall
simulation-experiments have indicated that surface properties, such as soil texture and
hydrophobic behaviour, have greater influence on the infiltration and runoff coefficient than
rainfall intensity (Pradas et al. 1994:238). (4) Surficial roots are important in soil retention and
increase the soil´s resistance to detachment (Shakesby et al. 1994).
The revegetation processes vary a lot. Older stands are likely to be more severe burned, and
the return for revegetation to pre-fire status is slower (Linder et al. 1998; Turner et al. 1999).
In one case the revegetation started three months after both severe and light fires (Giovannini
& Lucchessi. 1993). In another case the restoration stagnated four years after a fire and a
complete restoration was likely to take at least 15 years (Raison et al. 1993). The sterilising
effect of fires decreased the microbial activity (Altenburg et al. 1993), and leguminous plants
were more important for the chemical than the physical soil properties, eg increasing nutrient
availability, soil fertility, pH and electric conductivity (Gonzales et al. 1993), however
Carballas (1997) did not detect long term effects on microbiota.
A common revegetation flora consists of xerophilous evergreen bushes which send up suckers
from ground level after burning: holly oak (Quercus ilex), kermes oak (Q. coccifera) (Goudie
& Viles 1997:32), plants which resprout and reseed from soil banks: rockroses (Cistus spp)
(Thanos, 1997; Legrand 1993; Santiesteban et al. 1993), or are encouraged by fire: tree heath
(Erica arborea) and strawberry trees (Arbutus unedo) (Goudie & Viles 1997:32; Folch i
Guellen 1981) (fig 7 c,d).
Human impacts
After the fire soil is very sensitive to rain impact. Post-fire management, such as logging, rip
ploughing, may increase soil erosion. Natural pine seedling regrowth (Pinus pinaster) in
Portugal returned erosion levels to pre-fire rates in about 5 years, whereas the erosion
increased where litter and pine needles had been removed (Shakesby et al. 1994). Simililarly,
pine needles protect soils from rainsplash erosion in Spain (Ubeda 1998). Without human
intervention, erosion dynamics in shrublands were back to prefire rates within 2-4 years
(Cerda 1998). Moreover, the natural fire risk is high until the forest has established, from 3 to
5 years (Morgan 1995).
14
3
Objective
The effects of fires on soils are complex and not easily studied. Some important post fire
changes in soil properties can be related to weather, the intensity of the fire, new inputs as ash,
soil chemical and physical processes, biological activity and revegetation, and human
intervention. Few studies of wildfires on topsoils have lasted longer than 3 years.
The general objective of this study is to contribute to the understanding of post-fire processes
six years after the wildfire in Llagostera, NE Catalonia, Spain (1994). The study involved two
fire intensities and a control forest, and followed up on parts of previuos research by Ubeda
(1998). The specific objectives were to:
1) analyse the topsoil for texture, carbon/nitrogen (C:N) and calcium (Ca), magnesium
(Mg), sodium (Na), potassium (K) and phosphorous (P), in order to compare
a) two different fire intensities with the control forest, and
b) three terrace levels within each zone, for erosion.
2) When possible, analyse and compare (1) with the state immediately after the fire in
1994.
The phosphorous-results were lost (see Method), and have not be considered in the report.
15
4
Site description
Catalonia is the north eastern-most of Spain’s 17 autonomies. It shares international borders to
the north with France and Andorra, and national borders to the west and south with Aragon
and Valencia. Catalonia is divided in 4 provinces and 41 comarcas (regions). Girones is one of
the comarcas, in which Llagostera is situated, on the southern slopes of the Gavarres-massive.
The fire site is located 2°55’ E, 41°45’ N, app. 7 km southeast of Llagostera, nearby the GI
681-road between Tossa de Mar and Llagostera.
Geology and topography
The Gavarres and Cadiretes mountain system (519 m a sl) is in the northern corner of the
paleozoic Catalan littoral and prelitorral ranges. The range is composed of intrusive
leucogranites (light grey granites) from the Mediterranean coastline halfways to Llagostera.
Fig 3 a, b. a) Location of the study area near Llagostera, Catalonia (lightly dotted), NE
Iberian Peninsula (left). (Ubeda & Sala, 1998, and b) topographic map (right) with
Llagostera fire site. Note the distance to the Mediterranean Sea (Ubeda 1998).
The fire area is approximately in a facies limit (N-S direction) with coarse grain size to the
east and medium grain size to the west. Further west towards Llagostera is a region with
granodiorite, biotitic granites and ordovician contact metamorphosed quartsfeldspatic schists,
slates, and sandstones. The NW-SE faults refer from the Hercynian orogenesis and were
reactivated during the Alpine folding. The main contents of the leucogranites are SiO2 77 %,
Al2O314 %, K2O 4 %, Na2O 3 % and less than 1%/each of other compounds. The
granodiorites are less siliceous and have higher content of Al2O3 and 3 % of each CaO, Na2O,
16
and K2O (IGME 1983). The Llagostera basin is mainly made of Pliocene eroded granitic sand
and clay, and Quarternary alluvial sand and clay.
The fluvial valleys are oriented perpendicular to the coast. The frontier of the inferior hillslope
on the coastal range captures part of the drainage that flows into the Ter basin. The fluvial
terraces are little developed due to minor importance of the water courses. The area in this
study is situated on the SW slopes of the Llobatera mountains, 200-300 m a sl. The catchment
fills Benaula river, which is temporary dry. The highest tops are 500 m a sl (Ubeda 1998).
The natural erosion and runoff in pine and oak-forests on granite as well as slate in the
Gavarres-massive are low. However, the weathering mantle of the slate is thinner, thus
providing relatively less erodible material (Sala & Rubio 2000).
For the area related to in this study, the parent material has been referred to as granite
previuosly. The soils are Inceptisols according to FAO classification, and in Soil Taxonomy
the control forest and low intensity areas are typic Xerocrepts and the high intensity as lithic
Xerochrept. Slope aspects 9-10° (Ubeda 1998).
Climate
The character of Catalonian air masses depends on their origin. The main types are: (1)
Westerly zonal winds can occur all year round, however more frequently during the cold
months, and give a few showers. (2) Standing highs turn up particularly in summertime and
give stable, dry weather and no winds. (3) Cold Arctic air pass in autumns as humid Atlantic
winds or drier Asian north easterlies, which may cause heavy rains. The relief and the
geographic location give Catalonia important local
250
25
200
20
150
15
mm
°C
Precipitation (mm)
Temperature (ºC)
Jan 99
Oct
Jul
Apr
Jan 98
Jul
Oct
Apr
Jan 97
Oct
Jul
Apr
Jan 96
Jul
Oct
Apr
Oct
Jan 95
Jul
Apr
0
Jan 94
0
Jul
5
Oct
50
Apr
10
Jan 93
100
Evaporation (mm)
Fig 4. Monthly mean temperature, precipitation and evaporation 1993-1998, at weather
station in Cassà de Selva, Girones. The annual average precipitation is 675 mm, however
there are big variations (see fig 5). The weather station is 14 km from the place of the fire in
July 1994. Note in 1994 how temperatures and evaporation increased and precipitation
decreased, and how rain peaks generally occur in autumn. Data is missing when the lines are
cut. Raw data source: GRAM, Barcelona 2001.
17
climatic variations: (1) The Mediterranean climate with four seasons: warm, dry summers;
cold, humid winters, and short humid autumns and springs, with subdivided regimes for
maritime plains, lowlands and mid-mountains, and for continental plains, mid-mountains and
high mountains. (2) The Atlantic regime gives higher air humidity and daily and yearly
thermic contrasts. (3) The mountainous areas have lower temperatures, local storms and
abundant precipitation, which increase with increasing altitude and the rain maximum in
summer (Gran Atlas 1993:52-55).
1500
1000
500
Evaporation (mm)
Precipitation (mm)
0
Annual Balance
-500
-1000
1993
1994
1995
1996
1997
1998
Fig 5. Annual water balance (mm) at Cassà de Selva 1993-1998. Note that precipitation and
evaporation have been omitted for some months in 1998, when data is missing. Raw data
source: GRAM, Barcelona 2001.
Llagostera borders the continental – maritime Mediterranean mid-mountain regimes with big
daily and yearly contrasts. Dry and relatively high temperatures, irregular short unpredictable
rains in the autumns (fig 4). The yearly predominant wind direction is from ESE. Most fires
occur in the summer and are extinguished within 3 hours (Fecsa 1996:37-47). The summer
fires are related with periods of little rain, high temperatures, and inland winds with high
speeds and strong dessicating power. During winter fires are spread by dry, cold and/or
southerly winds (ibid:15-16).
Land Use
Catalonia had the most rapid agricultural mechanisation in Spain. Since the 1960s there has
been an accumulation of large farms (> 50 ha), nevertheless privately small-scale farms use ¾
of the agriculture land (table 2). The demand of meat products increased in the 1980s. One
third of Spain’s
Table 2. Land use and population in the area of the study. Girones is among the most forested
commarcas in Catalonia.
Area (km2)
Total
Agriculture Forestry (ha) Population
agricultural (ha)
land (ha)
Catalonia
31 895
2 470 000
1 100 000
980 000
6 000 000
Girones com.
575
40 000
15 000
25 000
126 000
Llagostera
77
5 000
No data
No data
No data
Source: Gran Atlas 1992.
18
pork and poultry meat is produced in Catalonia. Most of the forestland is located in the
Pyrenees, and on abandoned terraced land on the transversal and coastal mountain ranges. The
forested area is equal to one third of the total Catalonian area, or, less than half of the total
agriculture land. The dominating production is pine wood (P. sylvestris, P. nigra, P.
halepensis) on 320 000 ha. Populus nigra and Castanea sativa dominate the 70 000 ha used
for deciduous species. The Quercus (petrae, suber spp) is important but occupy only 10 % of
the forestland. Girones is among the most forested commarcas with 60 % forest cover.
Furniture and wood is an important industry of the commarca, together with chemical
industries. (Gran Atlas 1992:52-55)
Socio economic setting
The commarca of Girones is relatively densely populated, and 80 % of the population is
concentrated in urban communities with more than 10 000 inhabitants. The depopulation of
rural Catalonian areas has increased since the 1950s due to industrialisation and declining
agriculture, nevertheless the population has remained stable ascribed to decreasing fertility
rates since 1975 (Gran Atlas 1992:52-55).
The fire site in Llagostera, July 1994-May 2001
The fire, presumably intentional, started at noon on July 5, 1994. It was extinguished within
six hours and affected a total of 55 ha oak and pine plantation on terraced slopes. The
investigated areas involved 1,6 ha with low fire intensity, 5,7 ha medium intensity, and 5,4 ha
high intensity (Ubeda, 1998). The soil samples in 2001 were taken in central areas of the high
and low intensity, and control forest within an area of app. 100 m2 (fig 6b, 7a,b).
The following (known) post-fire activities and studies have been undertaken at the fire site in
Llagostera:
Jul 94
Fire intensity zones were classified (low, medium, high) (see above),
corresponding unaffected control forest at similar altitude and
inclination was identified in the neighbour valley. Unaffected in this
case means not affected by fires for at least 50 years.
Jul 94-Dec 96
Gerlach traps installed for measuring erosion sediment and runoff
water.
Nov-Dec 96
Soil profile analysis for soil classification (see appendix 3)
Jul 94-Nov 96
Runoff sediment samples
Jul 94, Mar 95, Oct 96, Mar 97
Soil samples
Jul 94-Mar 97
Soil moisture data
Mar 95, Mar 97
Infiltration capacity
Jan, Aug 95, Aug 96 Vegetation inventory
Jul 96
Post fire clearing
97
Replantation of Quercus suber and Pinus pinaster
May 01
Topsoil samples in low and high intensity (Simelton, 2001)
The total erosion between July 1994 and March 1995 was 0,2 t/ha/year from the low intensity
and 40,7 t/ha/year from the high intensity (Ubeda 1998; Ubeda & Sala 1998:182).
19
Fig 6 a,b. a) The control forest, May 2001. Pinus pinaster mixed with some Quercus suber and
the bushes Erica arborea and Arbutus unedo give a thick moist cover to the topsoil. Photo:
Simelton, 2001. b) Topographic sketch of the fire area, 55 ha (see fig 2) next by the road
between Llagostera and Tossa de Mar. Note how the fire intensities more or less follow the
contour lines. The soil samples were taken where the fire intensities are marked. The length of
the N-arrow app. equals 100 m (see 7a, b). Adapted from Ubeda 1998.
20
Fig 7 a-d. The location of the soil samples, a) high intensity (above left) and ,b) low intensity
(above right). Typical post-fire vegetation, Cistus, in Llagostera, May 2001. Compare with fig
6b. Sunlight still reaches the soil surface after c) high intensity fire (below left) and d) low
intensity (below right) despite its height (70-130 cm). Note the differences the in amounts of
pine needles, herbal vegetation and microtopography. Photo: Simelton 2001.
21
5
Methods
To enable a comparison with the previous study 1994-1996 (Ubeda 1998), the aim was to
carry on with the same methods. However, different methods were used for analysing texture
and phosphorous. This study was made in May-June 2001. The three days previous to the
sampling were dry and sunny with day temperatures of 22-23˚C. The total amount of
precipitation 10 days before the sampling was approximately 30 mm
(http://trackinggirona.com/meteo.htm). A detailed description of laboratory analyses is given
in appendix 3.
Field
Soil sample: A total of 90 samples (app. 500 g) from the upper 3 cm of the topsoil were
collected in approximately 100 m2 sized central areas of the same control
forest, high and low intensities as Ubeda in 1994 (all three zones) and 1996
(fire affected areas) (photo 3&4). 30 samples were taken per fire intensity (low,
high and control forest). Of these 30 samples, 10 each were taken at three
terrace levels (upper = samples 1-10, middle = samples 11-20, lower = samples
21-30) to see if there was an accumulation of nutrients or particles down slope,
which could indicate erosion.
Laboratory
The following analyses made in the laboratory at Barcelona University:
Soil preparation:
air dried for two days. Carefully crushed and sieved at 2 mm to separate
fine earth.
Texture:
9 texture analyses were made. One composite per fire intensity, and 1
per terrace level in the burned zones. Composite means to make one
analysis with a mix of the same amount of fine earth from all 30 or 10
fine earth soil samples. Robinson pipette (Ubeda & Sala 1995:16-20).
Texture classification according to USDA (1998:2-29).
pH (H2O):
Crison pH-meter 507 (Ubeda & Sala 1995:38-39) Classification (MOPT
1992:236-237) 90 samples.
Salinity/conductivity: Crison conductivity meter 524 (Ubeda & Sala 1995:39-41) 90 samples.
Organic C/organic matter: calcination in 450°C for 8 hrs. 90 samples(Unpublished stud
material, Ubeda pers. comm. 2001). The organic matter is calculated:
Organic matter (%) = Organic C x 1,724 (Cobertera 1993:248).
Phosphorous:
Osmond-Bray (Practiques d´edafologia p 34-35). 180 samples
The phosphorous results from 2001 have not been used. The increasing
blue colour and variability of the results indicate that we probably
allowed too long time between adding the reactant and the
photocolometric reading. Rather than speculating with the data, it was
omitted from this report.
Five analyses were made at Serveis Cientifico-Tecnics, Barcelona University:
22
Carbon/nitrogen:
Elemental analysis. 180 samples. The relation C:N is calculated:
Total organic C (%) / Total N (%) (Cobertera 1993:257-258).
Assimilable potassium:
Ammonic acetate at pH 7 atomic adsorption analysis (AAS). 90
samples.
Assimilable calcium, magnesium, and sodium: plasma with induction (ICP). 90 samples.
Meteorological data
The weather data was supplied as Excel software by GRAM, and compiled into monthly and
yearly averages by the author.The data included hourly measurements of temperature,
precipitation, evaporation, wind velocity and wind direction between 93-08-03 to 99-0331.The weather station is in Cassà de Selva, 14 km northwest of the fire area. Only the data
from 1994 to 1998 has been used. Some rainfall data is missing from 1998 (fig 4). In the
water balance diagram (fig 5) the evaporation is omitted for the months that miss
precipitation. The weather data previuos to the sampling 2001 was available on internet:
http://trackinggirona.com/meteo.htm.
Statistical analysis
The standard deviation (SD) of the observations and mean error (σM ) were calculated in
Excel. Mean error (σM ) = SD/√n, where n= number of samples.
If a gaussian distribution is assumed the 95 % confidence interval (α=0.05) for the mean can
be estimated as CD95 = 2xSD/√(n), where n is the number of samples. If the confidence
intervals from the means of one parameter overlap with the interval of another parameters,
there is no statistically significant difference between them.
The confidence interval calcutated for 2001 was also used for 1994.
To avoid confusion between fire intensity and relative amounts of nutrients etc. the soil
samples will be referred to in the text as H and a number for the high intensity (eg. H7), L for
low intensity, and CF for control forest. Sample numbers 1-10 are from the uppermost terrace
level in the investigated zone, 11-20 from the middle level, and 21-30 from the lower.
23
6
Results
The result paragraphs for macronutrients and C:N have been divided in two sections. The first
section analyses the results from May 2001. The second aims to relate these figures to
previous years, based on the studies by Ubeda (1998). Many results were significantly
different in 2001 compared with 1994. To enable a comparison over time, the same 95 %
(α=0.05) confidence interval as for 2001 has been assumed for 1996 and 1994. The detailed
laboratory results are in Appendix 1. The soil samples from the high intensity site are referred
to as H, low intensity L, and control forest CF. Sample number 1-10 are from the uppermost
terrace level in the investigated zone, 11-20 from the middle level, and 21-30 from the lower
level (see Methods).
The revegetation in the burned zones six years after the fire consisted of four dominant
species: Arbutus unedo, Ulex parviflorus, Cistus monspeliensis and C. salvifolius (fig 7c,d).
The bushes reached 70-130 cm and were about 30 cm taller in the low intensity. The A. unedo,
which disappeared after the high intensity fire in 1994, had reached the same height in both
zones, 130 cm. There were some sporadic pine and oak saplings, particularly in the low
intensity.
Texture 2001
The evident signs of erosion at the fire site in May 2001 were sheet erosion, rill erosion,
structural changes due to raindrop impact, and intrasol erosions, where finer topsoil is
transported leaving behind a concentration of stonier material.
The topsoil of the control forest had a thick (> 1 cm) cover of needles and humus. The forest
topsoil was considerably moister and darker than in the burned areas. In the fire-affected sites,
remnants of partially burned organic matter and black ash were noted. The low intensity also
had rests of burned bark. The topsoil was thinner, stonier and more compacted in the high
intensity than in the low (see fig 7c,d). Nevertheless, the textural analysis (tab 3) showed
sandy loam topsoils in all three fields and in all terrace levels, except for the lowest situated
terrace in the high intensity, which was loamy sand.
Table 3. The texture of 0-3 cm topsoil (average) has remained the same 1994-2001. A
different method was used in 2001. The texture in the lower terrace level of the high intensity
was loamy sand (2001).
TOPSOIL
Control forest
Low intensity fire
High intensity fire
Jul 94 May 01 Jul 94 Oct 96 May 01 Jul 94 Oct 96 May 01
Texture (%)
N=1
N=4
N=4
62
75
54
59
69
58
63
73
Sand
34
12
41
37
18
38
34
16
Silt
4
13
5
4
13
4
3
11
Clay
sandy sandy sandy sandy sandy sandy sandy sandy
Texture
loam
loam
loam
loam
loam
loam
loam
loam
class
Source: for 1994 and 1996: Ubeda (1998); for 2001: Simelton field study 2001 (App 1).
The surface cover on granites are generally loamy sands or the more profound sandy loams,
and the derived soils are typically shallow and sterile with fragments (MOPT 1992:267). Both
24
the high and low intensities had a higher content of sand in the lowest terrace level. The
difference was clear, particularly for the high intensity, when compared with its composite
(average) sample. However, more texture analyses are needed to draw conclusions about
accumulation.
Structure 2001
Three types of aggregation were noted in the soil samples.
Aggregates. Many samples from the burned areas contained finer organic (undecomposed as
well as ash) and mineral particles (mica), which had formed secondary sub angular and
granular aggregates and micro aggregates. The aggregates were difficult to disintegrate,
particularly those of the high intensity. Some samples with aggregates had distinct yellow
coloured soil solutions (L7, L25-27, L29; H21-30) and most of them had lower C-contents
than average (App 1). Of some samples with aggregates and black coloured (ash) soil
solutions (L3, L13, L15, H19), one (L13) had very high contents of Ca, Mg, N, Corg and C:N
(18). Two samples with black aggregates (L3, H19) had very high amounts of N and C, and a
higher C:N-ratio (14-15) than a similar sample with brown soil solution (H20) with average C,
N and C:N (11).
”Pellets”. Some aggregations in the high intensity resembled animal feed pellets (H2, H7,
H23-H26). The pellets disintegrated in to smaller mineral particles by grinding. The samples
with pellets had conductivity and C:N-rates slightly below average. The four samples from the
lower terrace levels (H23-H26) also had a very low Ca-content.
Layers. Other aggregates were held together as cm-thick weaved mats/layers (H4, CF2, CF5,
CF9). Despite H2O2-treatment, black organic substances (ash) floated up to the water surface
when the soil samples were soaked. These samples had the highest values for Ca, Mg,
conductivity, N, and total-C, but average amounts of organic-C, Na, and K.
pH and conductivity 2001
The pH (H2O) averages for all soils ranged between 5.9-6.5 (App 1), which can be classified
as moderately acid (MOPT 1992:236; Porta et al. 1994:226). The minimum and maximum pH
values ranged between 4.93-7.14. Both the burned soils had significant higher values (+ 0.5)
than the control forest. The lower pH in control forest can be expected due to humic acids and
slower mineralisation and a higher content of organic material (MOPT 1992:237).
The conductivity (salt content) of the burnt zones were about half of the control forest (171
μS/cm). There were insignificant differences in conductivity (the confidence intervals
overlapped) between the high (72 μS/cm) and low (92 μS/cm) fire intensities. The
conductivity had wide ranges: 103-313 (control forest), 38-124 (high intensity), and 44-229
(low intensity) μS/cm. At least for the control forest, some samples with higher total C had a
higher conductivity (CF2, CF5, CF9, CF 10, CF 23, CF 28) whereas the same relation was not
found in the burned zones. On the contrary, in the low intensity many samples with total C
above average had conductivity below average.
Macro nutrients
Table 4 shows the mean values of the chemical analyses of the topsoils with 95 % confidence
interval in 2001 and 1994.Table 5 gives the development for each zone 1994-2001, but not
their relative differences. Table 6 uses the control forest as an index to relate increase or
decrease. Note that the absolute numbers show great discrepancies for mean Ca, Mg, K and
25
Na. The variations of the data suggest that data may be comparable among intensities/year,
but with precaution amongst the years. Fig 8 is a histogram which demonstrates the
proportions and amounts for the macro nutrients in 1994 and 2001.
Potassium, calcium, magnesium, and sodium 2001
The only significant (α= 0.05) difference among the four exchangeable macronutrients (Ca,
Mg, Na and K) in 2001 between the topsoils of high and low fire intensities was for the
exchangeable K (tab 4, fig 8). The highest amounts of K were found in the soil samples with
plenty of visible ash particles (e.g. L13, L15).
Table 4. Diffences between average values in the upper 3 cm topsoil immediately after the
fire, after two and six years. The margin of error is based on 2001 with 95 % confidence
degree. Significant differences are marked *) α=0.05 between fire-no fire, and ¤) α=0.05
between high-low fire intensity.
Control forest
Jul 94
May 01
n=30
Ca
(ppm)
Mg
K
Na
Month/ 7/94
year
(%)
Org
matter
C-org
Tot-N
Low intensity
Jul 94
May 01
n=30
1443 4451 ±541*
High intensity
Jul 94
May 01
n=30
1103 2909 ±333
1419 2619 ±244*
427 877 ±113*
157 310 ±24
221 691 ±84
260 340 ±39*¤
280 589 ±78*
302 268 ±21¤
436 458 ±139
387 621 ±163
329 566 ±114
5/01
7/94
10/96
05/01
7/94
10/96
05/01
22.8 10.4 ±0.63 *
29.8
24.9 5.7 ±1.45*¤
19.1
5.2 2.9 ±0.83*¤
13.2 6.0 ±0.36*
0.51 0.44 ±0.07 *
17.3
0.79
14.6 3.3 ±0.84*¤
0.44 0.23±0.05*¤
11.1
0.50
3.0 1.7 ±0.48*¤
0.14 0.15±0.03*¤
28.7 15.9 ±2.52
21.7
33.1 13.9 ±0.96¤
22.0
C:N
Source: Ubeda, 1998: data from 1994 and 1996; Simelton for 2001.
21.6 10.4±0.63*¤
High concentrations of Ca and Mg occurred in soil samples with organic layers from the
control forest (e.g. CF2, CF5, CF9) and in C-rich aggregates in the low fire intensity (e.g. L8,
L13, L18). The lower amounts of Ca occurred in many samples with N below average (L4
L26, L27). The confidence intervals are wide because the min-max variability ranged more
than 3 000 ppm for Ca, and 900 ppm for Mg. The K-values showed more regular values: 124569 ppm (low intensity), 182-373 ppm (high intensity) and 183-477 ppm (control forest).
The highest Na-content in 2001 was in the low intensity and the lowest in the control forest.
The min-max values ranged between 182-1834 ppm (low intensity), 187-1466 ppm (high
intensity) and 71-1962 ppm (control forest).The lack of significance in 2001 is probably due
to the high variability among the samples.
26
Contrary to the fire temperature scale (Background), the Ca and Mg contents were highest in
the control forest both immediately after the fire and six years later. The proportions of
exchangeable Ca, Mg, Na, and K were similar for the burned plots (64:15:14:7), whereas Ca
made up for almost 75 % in the control forest on behalf of Na (73:14:8:5) (fig 8).
Calcium, magnesium, potassium, and sodium 1994-2001
The amounts of Ca and Mg were significantly less in the burned zones compared to the
control forest both in 1994 and 2001, however the accuracy given by the mean error is too low
to draw conclusions (tab 4, 5).
4500
4000
3500
ppm
3000
2500
2000
1500
Ca
Mg
1000
K
500
Na
0
CF 94
CF 01
Low 94
Low 01
High 94
High 01
Fig 8. The macro nutrients Ca, Mg, K, and Na in the topsoils 1994 and 2001. (CF= control
forest)
A considerable amount of nutrients has disappeared from the topsoil as runoff sediment and
erosion between 1994-2001. Between 1994-96 the total erosion was two hundred times more
in the high intensity zones than the low: 40.7 compared to 0.2 t/ha/year (Ubeda & Sala
1998:182). Nevertheless the amounts of Ca and Mg seem to have increased significantly in
the burned topsoils compared with after the fire in 1994. Note that the rates of Ca and Mg in
2001 had doubled in all soils, including the control forest, compared to the results from 1994.
Table 5. Trends for soil nutrient contents immediately after fire (1994): after 2 years (1996)
and 6 years (2001). Note the fluctuations for N. (*) indicates significant difference α= 0.05.
Zone/
1994=0 2001 = 6
Nutrient Year
Ca
Mg
K
Na
Corg(%) N (%)
C:N
Texture
after fire
+*
+*
+*
+/-*
-*
+/Control 0
Forest
+*
+*
+*
+
-*
--*
-*
+/Low
0
intensity 2
-*
-*
--*
+*
+*
+*
-*
-*
-*
+/High
0
intensity 2
-*
+/-*
Source: Ubeda 1998: data from 1994 and 1996; Simelton 2001, table 4.
Read horisontally to check what nutrient have increased (+), decreased (-), or not changed
(+/-) in the same fire intensity zone between 2001 and 1994, or between 2001 and 1996.
Between 1994 and 2001, K decreased in the high intensity. The effects of the expected
increase of K-content in the high intensity fire in 1994 (see temperature scale), had descended
27
below the values of both the control forest and low intensity in 2001 (the confidence intervals
overlap). On the other hand, since 1994 the K-content had increased in the low intensity
topsoil and the values of K in the reference forest had almost doubled since 1994 (tab 5, 6).
There were insignificant differences for Na between the different areas in 2001, however
between 1994 and 2001 there is a notable increase of Na in the fire-affected areas.
Table 6 Comparisons with the control forest serving as prefire condition, or index. *)
indicates significant difference α=0.05.
Zone/
Nutrient
Forest
(CF) vs
Low
intensity
(L)
High
Intensity
(H)
Low vs
High
1994(=0) 2001 (=6)
Ca
Mg
K
Na
Year 0
0
0
0
0
<*
<*
+/CF0:CF6 <<*
>*
<*
>
CF0: L0 >
CF0: L6 <*
<*
<*
<
>*
>
<
<
CF6:L6
<
<*
>
CF0: H0 +/CF0: H6 <*
<
<*
<
>*
>
<
CF6: H6 >*
<
<
<
>
L0: H0
<*
<*
>
<
L0: H6
L6: H6
>
>
>*
>
<*
<*
<
<*
H0 :L6
Source: Ubeda, 1998: data from 1994; Simelton, 2001.
Corg
0
>*
<*
>*
>*
>*
>>*
>*
>
>>*
>*
>>*
N
0
>*
<*
>*
>*
+/>>*
>>*
>*
>>*
>
>*
C:N
0
>*
>*
>*
>*
>*
>>*
>*
+/>>*
>>*
>*
Sum*
6
5
6
4
3
5
5
1
5
3
6
Read vertically – to check if the nutrient content in burned zones was higher (>),smaller (<),
or did not change (+/-) in relation to control forest (CF) the same years (0 to CF0), after six
years (6 to CF6), or changed over the years (6 to CF0).
Note: This test presupposes that both high and low intensity zones are equal to the control
forest, which is not the case. The exact amounts may also vary due to different methods for
chemical/ texture analyses. The table should be used for indicating trends only, particularly
when comparing the burned zones to the unburned forest six years earlier. The table shows
that relatively to 1994, the results for cations were higher in 2001, and lower for C and N in
all three zones. The control forest follows the same tendency.
Mineralisation (carbon, nitrogen)
C and N-contents, C:N-ratio 2001
Both the N- and organic C-contents were significantly different (α=0.05) in both the burned
zones and the control forest in May 2001 (fig 9, tab 4). The confidence intervals were narrow,
particularly for N, all three zones. The highest contents of N and C were found in the control
forest (0.19-1.06 N %; 4.40-24.59 Tot-C %). The low intensity-average was half of those
contents (0.10-0.72 N%; 1.34-22.04 Tot-C %). The high intensity fire had the lowest contents
(0.10-0.52 N%; 0.91-12.93 Tot-C %), and the average % C and N were one third of the
control forest. The C:N-ratio fluctuated more in the control forest (7-37) than in the burned
areas (10-19 in low intensity; 7-15 in high intensity). Somewhat unexpectedly did the average
C:N ratios vary less (between 10 and 16), and was only significantly lower in the high
intensity.
28
A C:N ratio between 10 and 15 indicates the humus type mull, a rapid mineralisation and well
incorporated organic matter to the soil (MOPT 1992:234) for all three zones.
N, C, and C:N-ratio 1994-2001
The N-contents in the two burned zones 2001 were one third of what they were in 1994. The
augmented amounts of N after the low intensity fire in 1994, show that the mineralisation
speed increased in relation to the unaffected control forest. Since the fire the N-contents in the
burned zones have been progressively decreasing compared to the forest. The N-content
seems to have decreased more rapidly in the high intensity than the low.
20
18
16
14
12
10
8
6
4
2
0
35
25
20
15
C
5
N
0
C:N
H 01
H 96
H 94
L 01
L 96
L 94
CF01
10
C:N-ratio
30
CF94
C org, Tot-N (%)
Note that the amount of organic matter in the unaffected control forest 2001 was half of its
value for 1994 (fig 9). This increased the mineralisation rate accordingly. Apart from effects
of seasonal variations (the samples were taken in July 1994 and May 2001), it is difficult to
explain such a drastic decline by other means than different methods for determining organic
carbon. Nevertheless, even if the values for C in 2001 were the double, would the burned
zones end up at half of the values in 1994.
Fig 9. Decreasing trends of nitrogen (N), organic carbon (Corg) and C:N for all three soils in
Llagostera between 1994 and 2001. The N- and C values of the control forest were generally
higher, and the lowest results were in the highest fire intensity zone. Note how the different C
and N-contents, as of the control forest and low intensity, can give similar C:N-ratio.
Source: Ubeda 1998: data from 1994 and 1996; Simelton 2001
Terrace levels 2001
Quite contrary to what could be expected, did the lowest terrace levels not show the highest
contents of any of the investigated nutrients, except for K in the control forest and high
intensity. It is possible that there was an accumulation of sand in the lower terrace level,
particularly in the high intensity topsoil. Sodium had accumulated in the lower terrace level of
the low intensity area, however there were no significant differences between the two fire
intensities. In all three areas the least amounts of N- and C were found in the lower terrace
level. The only similar patterns for the burned plots were in found at the middle position,
which had the lowest content of Na and of clay-particle size.
Summary
The topsoil with the low fire intensity had significantly higher amounts of K, C, and N than
the high fire intensity. Soil samples with ash were rich in exchangeable K, whereas soil
29
samples rich in organic matter had higher amounts of Ca and Mg. The mineralisation rates
were faster, and the amounts of C and N were significantly lower in the burned zones
compared with the control forest. There were different types of aggregates. Soil samples with
aggregates from the low fire intensity area had higher concentrations of nutrients than samples
with less aggregates from the same intensity, and than samples with aggregates from the high
intensity. There were no clear signs of surface textural- or nutrient
transportation/accumulation in the topsoils.
In a six years perspective the fire had important impacts. The fire intensity and post fire
erosion had small effects on the texture classes. However, the most evident effects were the
remaining losses of C and N content due to the fire. These effects were more profound in the
high intensity soil, and resulted in high mineralisation rates and drier topsoils.The nutrient
availbility which increased after the fire, seemed to remain longer in the low fire intensity
topsoil than the high.
30
7
Discussion
The discussion begins with some comments on the methods. It seemed most logical to
continue a discussion on consequences of fire starting from the vegetational point of view.
From there over to the physical and chemical processes, and finally fire risks and some
questions for future research. The intention is to discuss possible explainations to the results,
potential consequences of future fires and prescribed burning. It may be helpful to review the
fig 1.
Methods
The comparisons between the burned zones in this study were based on the previuos
classification of high and low fire intensity according to ash (see Background). The use of a
control forest or pre-fire status comparison do not presuppose that there was a balance in the
reference system, or that the preconditional status was similar in the three soils, when the fire
occured. The variability between the results from 1994 and 2001 (tab 4), show that even data
for a reference forest must be interpreted with care. Some variability of the results within one
fire intensity, are attributed the patchy vegetation and inequally burned spots. It is difficult to
estimate in one study how much the different laboratory methods have affected the
comparison over years for Ca, Mg, Na and C, N. However, there are some similar trends in all
three zones (fig 8, 9): The decreases in C and increases in Ca, Mg, and clay content are
proportional. The general increase of available nutrients in 2001 may be related to the clay
fraction.
The time of year for the soil samplings has been different, as was probably the weather before
the samplings. These factors have not been considered here, but they may influence on e.g.
pH, the nutrient availability, organic matter and C:N-ratio. Chemical weathering and
mineralisation processes normally slow down during the colder season and the nutrient
availability increases after rain (Wiklander 1976:119). During precipitation the most soluble
nutrients Na, Cl and NO3 are leached, whereas drought increases the pH and conductivity
(ibid p 136).
Other issues relate to how representative these 90 samples were of the area, and how
representative the 0-3 cm topsoil are of the soil. The soil sampling in 2001 was carried out by
3 persons. Each one picked soil from the same terrace level in each intensity. The relatively
uniform results between terrace levels and within each intensity, indicate that the sampling
probably would not have been less biased with a mapped random outlay. Many studies have
shown that fires’ main effects are on the topsoil (Ubeda 1998; Giovannini 1993). According to
Cerda (1998) the soil moisture may recover faster at 4-6 cm depth than 0-2 cm, at least if there
is litter. This could mean that topsoils show the “worst case” of post fire effects in a soil
profile. Moreover, in the soil samples from December 1996 (see App 3) the O(uppermost/topsoil) and A-horisons (subhorison) of the low and the high fire intensities were
quite different from each other. For example, in the high fire intensity the cation contents (Mg,
Na, and P) were higher in the subsoil than the topsoil, whereas the low intensity had a thicker
topsoil which contained higher amounts of the same nutrients than its subsoil. Only the K
showed the reverse locations. The CEC, C, N and C:N-ratios were higher in the O-horison for
both fire intensities. Obviuosly a deeper soil sample, incl subsoil, could have indicated
leaching of nutrients in this study. Furthermore, a considerable amount of soil had eroded,
31
particularly from the high intensity (Ubeda 1998), hence it is not the same topsoil layers that
are being compared in 1994 as in 2001.
Biological activity
The loss of vegetation after a fire is critical for soil recovery processes (Pradas et al. 1994).
This study makes no exception, however, it is challenging to separate the consequences
related to fire with the loss of vegetation. For example, the C:N-ratio, interpreted as mull
(MOPT 1992:234), was similar for all three topsoils. However, it is probably pointless to refer
to the burned topsoils as forest soils. ”Well incorporated organic matter” (ibid) gives a skewed
guide on the quality of the organic matter in the burned soils. Contrary to Luis-Calabuig &
Tarrega (1993) there were clear differences between the burned and unburned topsoils, as well
as between the burned areas, still six years later.
The organic matter
The organic matter content in 2001 was significantly lower in the burned topsoils (tab 4),
including litter as well as incorporated organic material. The amounts were lowest in the high
intensity. There can be several explanations: (1) More nutritive elements (N, P) including
carbon were lost during the fire by volatilisation in the higher intensity. This is related to the
temperature effect as well as by the position on the upper parts of the slope (fig 1) (Raison et
al. 1993; Giovannini & Lucchesi 1993). (2) Pine needles rather than plants, made up a great
part of the cover and organic carbon in the forest, whereas the absence of vegetation in the
burned zones could not provide slower decomposable needles/leaves (fig 6a, 7c, d). (3) More
elements and soil particles have been lost after the fire in the high intensity due to erosion and
run off (Ubeda 1998), which are indirectly related to fire intensity. (4) Climatic effects. In
cambisols in NW Spain, the organic composition of the surface and subsurface layers tended
to be similar to unburnt soils within one year after the fire (Carballas et al. 1993). However, in
Llagostera the Mediterranean winds give a drier and warmer environment than the humid
Atlantic winds. Also the relatively unaffected C- and N-contents in NW Spain (ibid) indicate
the importance of water for topsoil restauration.
The most evident consequence of small amounts of organic matter and an unrestored litter
layer were the topsoil moisture. Again, there is more than one reason to why the burned
topsoils were drier than the forest’s: The temperature of the fire desiccated the topsoil and
destroyed the structure (Giovannini 1997; Cerda 1998). The texture and lithology enable fast
drainage and evaporation (see below). Many summers have had water deficits (fig 4, 5). The
slopes face southwards (see 7a, b). The type of revegetation in Llagostera provides little
shadow and organic mulch, regardless of the fire intensity (fig 7c, d). The loss of organic
matter may decrease the cation exchange capacity (CEC) (Giovannini 1997), provoke a
decrease in water holding capacity of the surface layers (Carballas et al. 1993) and also
desiccate the topsoil (Cerda 1998). However, in some cambisols in NE Spain, the topsoil-CEC
was two times higher two years after a low intensity fire compared to both a severe burn and
an unaffected forest, and despite that the organic matter was three times higher in the forest
(Ubeda 1998).
When vegetation is removed without a fire, the amount of organic matter is affected by
several factors. Some factors are similar to those induced by fire. Most significantly are the
amounts of organic C fixed through photosynthetic reactions. The vegetation removal reduce
the microbial activity (Altenburg et al. 1993; Gonzales et al.1993), which, similarly to a firesituation, might contribute to structural degradation, decreasing aggregate stability, and
increasing compaction. The removal of vegetation from a mollic epipedon (without fire)
32
decreased the organic C by 35 %, due to the lack of plant residues and roots returned to the
soil and an increase in soil temperature during the warmer season (Albaladejo et al. 1998).
Moreover, the evaporation increases from bare soils (Sandström 1998). However, the water
holding capacity did not change by vegetation removal (Albaladejo et al. 1998), which is often
the case after fires.
In Llagostera the different heights of the revegetation may depend on a relatively delayed start
after the severe fire due to erosion, and/or progressively higher amounts of plant available
nutrients in the low intensity in relation to the high (tab 4, 6). Pine saplings on the low
intensity slopes can be the result of a sapling bank, formed in the early post fire recovery
stage, or of pine seed germination after the first post-fire rainy period (Thanos 1997). Erosion
of the seed bank result in relatively smaller amounts of saplings, as in the high intensity. The
frequency of herbs in the low intensity zone, indicate that soil water was more available there
according to slope position rather than fire intensity. Similarly to Lahav & Steinberger (2000),
was the surficial microbial activity (ants, earthworms, insects) in both burned fields associated
with rock fragments (fig 7d). Stones and taller vegetation create reliable microhabitat with
lower soil temperatures and relatively higher moisture than open spaces. Moreover, the
mosaic litter can reduce the post fire erosion by water and wind (ibid), as well as form patchy
ash patterns in case of a new fire. Moist litter and low intensity fires can reduce the risk of
nutrient loss through volatilisation during a fire.
In summary, sources for soil moisture was highly affecting the restauration of the topsoil.
Other consequences of the low contents of organic matter were evidenced through the
relationships between organic matter, Ca and Mg. Lower amounts of organic matter
diminished the potential to store nutrients (see below), and were found in soil samples with
the densest aggregates, “pellets” (see aggregates).
Mineralisation (C, N)
The mineralisation was faster in the burned topsoils (fig 9, tab 4). In general the C:N-ratio
varies with the relation climate-vegetation-humus type (Cobertera 1993:257). In this case six
years after the fire, there were only significantly different C:N-ratios between the high fire
intensity and the unburned forest, although the vegetation and humus in both the burned areas
were totally different to the control forest. However, both Pinus and Erica are resinous
species, which produce acid förna with slower decomposition rates (ibid) than e.g. evergreen
deciduous. The similar ratios must be viewed in combination with low contents of N and
organic C in the burned zones. Obviuosly, a small increase in organic matter managed to slow
down the mineralisation, as in the low intensity 1994-96 (fig 9, tab 6), and perhaps achieve
some accumulation of synthesized humus. This did not happen in the high intensity topsoil
due to the erosion.
In a nearby forest, the C:N-ratio showed high variations in soil samples with black and white
ash, but the C and N-contents were higher in the black ash than the white (Sala et al. 1993:23).
Similarly in this study, some soil samples with black ash had very high contents of C and N
(H19, see aggregates below). Microbial activity may decrease by the sterilising effects of fires
(Driscoll et al. 1999). However, the descending C:N-ratios (fig 9) in this study suggest that the
mineralisation is limited by the absence of decomposable organic matter, which is related to
fire intensity.
33
Nitrogen
Inputs of N are related with vegetation (Driscoll et al. 1999) and rain (Mollison 1988). Due to
the limited input sources, the reestablishment of N becomes particularly related with fire
intensity. In experimental fires on granite with Ulex-vegetation (leguminous), N increased
until a temperature of 350°C. Above 600°C both C and N disappeared totally (Pradas et al.
1994), whereas the N-increase in a wildfire with Ulex-revegetation was not related with fire
intensity (Ubeda 1998). The N-losses through volatilisation in this type of pine and oak-forest
could reach 6 kg N per ton combustible (Alcañiz et al. 1996:116). Another calculation on
erosion of 5 mm topsoil with 0,4 % N-content, equals 50 t/ha soil, gives a total N-loss of 200
kg/ha (Raison et al. 1993). It is obvious that the N-fixing capacity of Ulex was disturbed at
least in the low intensity, but not extinguished in the Llagostera-fire. Although N-fixating
(leguminous) species were most frequent in the high intensity zone in Llagostera (Ubeda
1998), natural inputs and biological fixation had not made up for the N-losses after the fire in
2001(fig 9).
The losses of biologically active components, such as litter, growing vegetation and biota,
possibly also labile components of the organic fraction, alter the long term N equilibrium. The
natural inputs of N to a forest can be calculated from the amount of N fixed in litter, under
storey, tree and soil. The ratio between tree:soil can be used to predict the losses of N by fires.
If N-losses through volatilisation were limited to 50 % of the N-contents of the fuel, interfire
periods of 10 years would be needed to allow natural processes to replace the N lost during
burning (Raison et al. 1993). There is insufficient data to analyse the N-inputs by rain in
Llagostera. However, if there is a tendency towards a drier climate (fig 4, 5), which may
explain parts of the overall low N-contents in 2001, interfire periods needs to be even longer
to re-establish the soil-N.
Physical processes
Texture
The texture class, sandy loam, remained with a possible accumulation of sand in the burned
areas (tab 3). It is difficult to say whether the clay fraction has increased in the burned areas
since 1996, since the control forest shows a similar change. Although the Robinson pipette
method gave higher amounts of sand- and clay fractions than the Coulter Particle Size-method
used by Ubeda (1998), the ranges were within the same textural class as in 1996. The pipette
method can overestimate the silt fractions as a result of electrostatic interaction by organic and
inorganic substances (Ostwald 2000 cites Landon 1991). The flocculation of ash leachates in
combination with lost plasticity and water repellence can make aggregates difficult to dissolve
(Giovannini 1994), as the pellets and aggregates in this study. However, if clay particles form
the dense aggregates and the units are insufficiently dissolved in the textural analysis, the
larger particle size fractions could also increase. The increase of clay content from 1994 to
2001 may demonstrate that some aggregates have dissolved and returned to primary minerals.
Aggregates can e.g. disperse by raindrop impact, by contact with water causing changes in
electrostatic bonds. Obviously the big share of clay fractions in 2001 are not disintegrated
clays and silicates due to temperature (ibid), since the increase is recent. However, the
consequence of an increased clay fraction may be a general increase of available elements, as
in this study (tab 5).
The textural processes after fires have had different results in other cambisols/xerochrepts.
Ubeda (1988) noted insignificant changes (the soils in this study as well as others). Carballas
et al. (1993) found small increases in the clay fraction in some surface layers, whereas the
34
sand fraction increased to the detriment of the clay fraction, in other topsoils the silt fraction
remained unaffected (Giovannini 1994). The considerable fraction of coarse grain size could
reflect the parent material, leucogranite (MOPT 1992:267). Granites are more sensitive to
erosion than e.g. schist and have a thicker weathering mantle (Sala & Rubio 2000), but the
natural erosion in these areas is normally low, except for heavy rainfalls (Ubeda & Sala 1998).
Ignifracts of the erodible granite may increase the sand fraction (Birkeland 1984:63-66), as
could outwash by intense rains. Previously, erosion in this area has mirrored the composition
of the fine earth fraction (Ubeda 1998), and in the recent years heavy rainstorms have washed
out some material, leaving ash compounds behind, particularly in the high intensity (Ubeda
pers. comm. 2001). There are also reasons to believe that the post-fire management started too
late and accentuated the previous erosion (ibid; Shakesby 1996). The topsoil is the result of
many processes. Erosion and runoff are also related with indirect consequences of fire
(Alcañiz et al. 1996), as soil organic content, humidity, structure and aggregation.
The relative variations in textural fractions of the control forest are similar to the burned zones
and the increase of some available nutrients accordingly. This suggests therefore that the
different methods for textural analysis caused the differences in fractions between years.Given
erosion was a less problem in Llagostera, leaching could be serious due to the texture as well
as the lack of organic compounds (see below).
Structure: aggregations and layers
Different types of aggregates were common in the burned topsoils, whereas layers occurred
mainly in the control forest and in some soil samples from the high intensity (CF2, CF5, CF9;
H9).
The soil samples with organic layers were particularly rich in Ca, Mg and organic matter, and
occurred mainly in the control forest. In an unburned forest, the humus type mull is described
as a “hydrophilous type of colloid that is surrounded by a water film and with great resistance
to flocculate and disperse”. The clay-humus colloids favour the formation of stable aggregate
and adsorption of nutritive elements (MOPT 1992:235). The thick carpets of organic content
in the forest (fig 6a) illustrate that the combined layers exist before the fire. Some layers (e.g.
H9) have probably formed because the sandy texture is easily dehydrated by heat (Giovannini
1997). Sandy soils have smaller specific areas than fine-textured soils and are therefore more
likely to be coated by the vaporised hydrophobic organic substances that move downwards
and condense at cooler underlying soil layers during fires (Robinchaud & Hungerford 2000).
Moreover, sandy textured soils produced more runoff during summer, especially those with a
water repellent E or AE horison (Pradas et al.1994; Giovannini & Lucchesi 1993). The less
frequent organic layers in the low fire intensity soil samples in 2001 may depend on that, due
to the lower temperature, the colloids were generally softer, moister and less dense than the
high intensity, and therefore more easily disintegrated.
The texture and structure of some aggregates were directly related to the fire intensity and the
content. The friable aggregates contained angular mineral particles and were found in the
both fire intensities. The shape had enabled their accumulation in the fine woody root
networks, whereas the finer particles may have been washed out by rain. Such selective
erosion produces material for new clay- and silt aggregates.
The denser “pellet” aggregates occurred in the high intensity topsoil. The soil samples had
slightly less organic content than the more porous friable ones. This type of aggregation can
have several backgrounds. The yellow colour of some soil solutions normally indicates iron.
35
The hydrolysis of Fe-containing minerals produces ferric oxides, which can coat sand- and silt
particles, and cement the fractions to aggregates. This process is common in cambisols
(Driessen & Dudal 1991:137-141). Given the low nitrogen content, it is also possible that
increasing soil temperatures due to sun exposure and the lack of microbial activity after fires
have accentuated aggregation (Albaladejo et al. 1998) in the higher intensity zone. Subangular
bloques are typical for semiarid organic poor soils and ochric/cambic epipedons, whereas
granular components prevail in biologically active soils that are rich in bases and organic
matter (Porta et al. 1994:248). The angular forms on minerals can also be the result of
ignifraction (Birkeland 1984:63-66), which is likely to occur where temperatures are higher.
Chemical processes
pH
The pH in the two burned topsoils were 0.5 values higher than in the control forest. This is a
combination of the acid förna in the forest (see above) and remaining effects after the fire. In
acid soils, as these three, is it interesting to know what produces basic reactions in the soil,
because the pH influences the humification and mineralisation processes. A slightly higher pH
in the high intensity topsoil may be the result of a fuller combustion and incorporation of
nutrient-rich ash into the soil (Giovannini 1997, Giovannini & Lucchesi 1993). Moreover,
evaporation is higher in the less vegetated burned topsoil, which increases the chances of ion
concentrations and thereby increasing pH (Wiklander 1976:136). To a major part the pH
conditions the soil structure and determines the availability of soil nutrients to plants (MOPT
1992:235). A slight acidity might indicate a deficiency of e.g. Ca, K, N, and Mg as well as
low bacterial activity (Porta et al. 1994:226).
Consequently the potential of pH to increase the nutrient availability in the burned fields,
lasted at least six years after the fire. However, the amounts of plant available nutrients were
less in the burned areas than in the forest.
Calcium, magnesium, potassium
There was a general increase in nutrients from 1994-2001 with one exception. In the high
intensity K decreased from having been the highest of the three soils after the fire (tab 5). The
chemical composition (fig 8) of the topsoils reflected the parent material to some extent (see
geology, site description). Granodiorite and leucogranite have rather similar proportions of
Ca, Mg, Na and K (IGME 1983). The K-inputs derive from muscovite and mica, which were
frequently noted in the soil samples. Some soil samples with black ash were also rich in K.
The K-content can be very variable (2-191 meq/100g soil) (Alcañiz et al. 1996:116).
According to another division of Spanish humus, are 90 % of its constituents in the following
distribution H>C>O, and the rest 10 %: N>P>K>Ca>Mg (Porta et al. 1994). With both these
comparisons the K-contents in the studied topsoils are low, including the forest (tab 4).
Ca, Mg and K were augmenting more rapidly initially after the high intensity fire than the low
(tab 4), and according to the temperature scale (see Introduction) because the fully combusted
white ash contributes more Ca, Mg and K (Alcañiz et al. 1996; Goudie & Viles 1997).
However, after six years the Ca, Mg and K contents in Llagostera were lower in the severely
burned topsoil. In natural conditions Mg is mobile, common in the subsoil and often deficient
in sandy textured soils (Mollison 1988:190-193) and K is also easily leached and transported
(Alcañiz et al. 1996:116). Only 1 % of the mineral-K is exchangeable, however, the rates
increase due to defixation, weathering, and drought (Wiklander 1976:180-196).
36
The Ca and Mg were particularly related with organic colloids (see aggregates in the low
intensity; Sala et al. 1993:23). Contrary, drier soils increases the solubility of K (Wiklander
1976:180-196) which can be reflected in firstly, the burned, dry topsoils, and secondly, the
soil samples with angular aggregates without ash. The ratios Ca:K and Ca + Mg:K = 8-20
indicate assimilation of P-anions, K and Mg (Cobertera 1993:94-100). However, in this case
the relation of the polyvalent Ca and Mg to the monovalent K exceeds 20 in all topsoils, i.e. K
and Mg may exist in non-assimilable forms. The relation could also point out that Ca and Mg
(positive) exchange K, are bound between clay laminates (negative) and K is leached. This
process could also explain why there are higher proportions of Ca and Mg in the forest, where
there are more organic compounds.
In 1996 (App 3) the uppermost level of the high intensity contained more K than the
subhorison. Possibly nutrients in the topsoil were lost through runoff or erosion until that
time, when the topsoil was less stabile and vegetated. Since there was no accumulation of K in
the lower terrace levels (2001) it is likely that K has leached from the humus-poor and coarse
textured topsoil in the severely burned zone since 1996, rather than eroded in runoff
sediments. Conversely, leaching processes may have started relatively sooner in the low
intensity soil due to comparatively less soil erosion and higher organic content in the topsoil,
which resulted in a higher K-content in the subsurface than the topsoil in 1996. Consequently,
even in few years, soil formation processes have been relatively delayed due to the higher
intensity fire.
The nutrient contents of the topsoils depended to some degree on the aggregates, which were
related to fire intensity. Ca and Mg were particularly common in soils organic compounds,
whereas the dense aggregates had less plant available nutrients. After fires on sandy texture
soils, the formation of organic aggregates has potential to release nutrients with different
ratios, and prevent rapid leaching.
Sodium & conductivity
The conductivity was highest in the control forest and lowest in the high intensity topsoil.
Since the Na contents and concentrations were slightly higher in the burned areas (tab 4, fig
8), salts of Ca, Mg, and other elements obviously make up the salt-content in the forest or that
soluble salts are leaching (Caballas et al. 1993). It may also mean that Na, which is normally
very soluble, is trapped between aggregates in the burned zones and cannot be extracted by
water (Giovannini 1994). Unless the humus in the forest holds a lot of salt, most literature
speaks for that conductivity should be higher in the burned zones. For example, the
conductivity increased as a consequence of the accumulation of elements that had been bound
to organic matter (Carballas 1997:251). This is likely to happen after a fire. Weathering
reactions including soluble salts and carbonates in some types of congruent dissolution can
also increase the conductivity (Porta 1994:649). Na-content was derived from vegetation on
calcareous soil (Solera 1999). In this case carbonates are excluded since the parent material is
granitic, but the vegetation was similar to Llagostera. The fluctuations of Na between the
terrace levels may depend on that the sampling areas of the slopes were too short (perhaps
there would be different results with soil from the very crest and bottom), or that nutrients are
leached, transported and accumulated deeper in the horizon rather than in the upper three
centimetres.
Airborne additions of Na, as well as Mg and Cl, can also have strong influences in coastal
areas (Wiklander 1976:141). 1993, 1994 and 1998 were three years with high evaporation and
little precipitation (fig 4, 5). The prevailing wind was ESE during the whole period
37
(Meteorological data, GRAM). This enabled an increase of wind transported Na from the
Mediterranean, 10-15 km east of the burned area (fig 3b, 6b), to be adsorbed on leaves both of
revegetation and dense forest. However, this process needs precipitation to initiate stem fall
and through fall of the elements to the soil. The winters of 1996 and 1997 were rainy.
Consequently the relatively higher amounts of Na in the burned plots may be accredited the
sparse revegetation, where airborne particles can reach the soil more easily, and particularly
on the crest where the high intensity zone is located (fig 6b).
In summary, the ash impact achieved a significant increase of exchangeable K that lasted at
least 6 years after a low intensity wildfire. The high intensity fire had negative effects on plant
available nutrients, which were lower than the control forest. The loss of vegetation may
increase the amounts airborne salts and particles in the topsoils. Six years was not enough
time for soil recovery.
New fire risks and future research
Regardless of how little decomposable litter the revegetation, usually dry and woody,
provides, it soon becomes a new fire risk. Although this particular forest is in a sparsely
populated area, it is next to trafficated road. Fires are easily spread across low vegetation with
low bulk density. The ability of a fuel to ignite after having been submitted to calorific energy
varies. In flammability index the revegetation species (fig 7c, d), Erica arborea had high
flammability risk from spring to fall, Cistus salvifolius had less risk than C. monspeliensis.
The Quercus spp were slightly more flammable than the Pinus spp, and 2-3 year old pine
needles made a higher risk than one year old (Valette 1997). However, another index gave
Quercus spp lower rates (2) than both Pinus spp and the mentioned revegetation species (6-7)
(Fecsa 1996:52). Nevertheless, there are other complications to forest fires in the
Mediterranean areas. Firstly, the affected areas are increasing and secondly, all burned forests
are not replaced (Conacher & Sala 1998). It is beyond scope to relate the environmental
effects, however, some questions will be raised:
What is the function of tar in forming water repellent humus? Can combinations of stands be
designed that decrease the amounts/effects of hydrophobic substances?
How can re-establishment after severe fires be improved so that erosion and fire risks are
reduced while a protective humus layer formed?
What incentives/restrictions should forest owners have to better maintain their forests and
reduce fire risks?
How will climatic changes affect soil recovery processes after fires, e.g. N-inputs,
decomposition and accumulation rates?
More research is needed long-term effects of wildfires and interactions among soil-vegetationfauna. Research that also aims to find alternatives to prescribed burning for areas where this is
not possible. One fruitful way to increase the understanding and make top-science reach a
wider audience is to involve students of physical geography and biogeography in forest- and
fire related surveys, in cooperation with the fire brigade and forest guards, as GRAM at
Barcelona University.
38
8
Conclusions
Six years after low and high intensity fires in Llagostera the following conclusions can be
made from this study:
•
•
•
Firstly, post fire recovery processes are definitely not finished after 3 years! It would be
easy to follow up on some of the short-term post fire research, and thereby increase the
understanding of the recovery processes.
The texture class remained similar, regardless of fire intensity and the early post-fire
erosion (1994-96). There was no distinct accumulation of nutrients or particle fraction that
could indicate topsoil erosion from the upper to the lower terrace levels.
Soil samples with different types of aggregates and layers were related to fire intensity,
organic content and plant available nutrients. Aggregates can be important nutrient
stores.The remnants of undecomposed black ash suggest that hydrophobic properties
remain at least for six years.
•
•
The pH remained higher in the burned topsoils than the forest, due to ash impacts.
The C:N-ratios in the burned topsoils were nearly equal to the control forest. However,
• The nitrogen content was half or less than half of the control forest.
• The organic matter content had not restored to the conditions of the control forest. The
augmented total carbon effect remained longer after low intensity fire than high.
• It is impossible to conclude that only the fire intensity is responsible for the low
organic matter content, however in combination with the low N-content even the
effects of low fire intensities are undisputable even 6 years afterwards.
•
The amount of available nutrients were less in the topsoil with a high fire intensity, except
for Na. The only significant remaining increased post-fire effect was of K in the low
intensity. Ca and Mg were lower in the burned zones than in the control forest, most
probably due to the lack of organic matter.
•
The revegetation was homogenous and similar in both areas; only faster in low intensity. It
provided little input of organic matter, little shade, and made a high fire risk.
The post fire development can at least be related with slope position, fire intensity,
revegetation, soil humidity, time.
•
Consequently,
The burned topsoils had not recovered in six years. The lack of litter seemed to be the most
critical factor. The recovery of soil and vegetation was more retarded after the higher intensity
fire than the low. Although the new vegetation makes a seriuos fire risk, a new fire, perhaps
even a prescribed, within this time frame would affect the long term recovery and soil
formation processes in these soils.
39
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42
Appendix 1 Ca, Mg, Na, K; texture; pH,
conductivity, and C:N, 2001
Calcium, Magnesium, Sodium, and Potassium. May 2001
Low intensity
Ca
Sample
Upper level
Mg
(ppm)
Na
High intensity
K
Ca
Mg
(ppm)
Na
Control forest
K
Ca
Mg
(ppm)
Na
K
1
3065
649
1696
424
3403
1060
439
325
3984
983
379
288
2
3935
757
1834
384
3260
904
557
248
6454
819
349
321
3
3629
995
461
343
3063
879
1225
210
5787
675
329
289
4
2601
1227
396
256
4233
1233
745
275
3544
561
197
236
5
3058
799
634
345
2961
671
275
277
8883
1482
1962
413
6
2099
808
295
294
3294
750
547
272
3769
781
399
210
7
3780
945
856
569
2279
552
390
216
2241
423
367
269
8
4086
927
1011
549
3612
784
767
288
3777
585
230
320
9
2565
684
451
423
2861
596
377
192
7157
1713
980
324
10
3638
982
910
601
3518
447
299
212
6104
1099
344
331
Middle level 11
2107
589
275
370
2304
524
308
230
4228
1260
429
269
12
2862
624
713
373
2058
574
465
286
4345
1218
565
377
13
5397
1134
504
406
2052
505
644
184
4340
937
520
315
14
2941
661
523
338
2456
523
935
360
3987
791
469
275
15
2943
506
323
409
2258
381
187
213
6082
1123
221
269
16
3255
599
423
336
1845
455
992
311
4989
1355
511
330
17
4107
820
507
347
2330
501
310
343
2830
713
228
183
18
3111
788
377
318
2394
413
483
272
4010
926
401
241
19
2677
640
359
222
3708
574
859
360
4648
1199
0
417
20
3065
592
306
369
2536
478
228
280
3612
851
1308
377
Lower level 21
3547
703
581
353
2077
418
242
233
3189
670
329
324
22
2242
497
213
244
2624
602
721
344
2225
538
271
217
23
2283
512
276
265
1817
346
570
257
3468
690
206
252
24
1680
367
254
213
1847
358
262
247
3118
657
556
477
25
1251
278
182
124
1604
380
224
182
3489
787
418
392
26
1358
364
229
260
2269
521
1466
336
3946
665
211
289
27
1624
340
1564
223
2052
405
818
203
4164
731
741
359
28
3371
688
489
269
1981
420
602
229
6107
887
481
343
29
2869
756
1268
317
2611
638
715
293
3724
434
71
271
30
2134
502
710
243
3250
783
338
373
5333
759
275
320
Average
2909
691
621
340
2619
589
566
268
4451
877
458
310
Standard dev
911
229
445
106
670
214
314
56
1483
310
382
67
Conf. Interval
333
84
163
39
244
78
114
21
541
113
139
24
Average/terrace position:
Upper level
3246
877
854
419
3248
788
562
252
5170
912
554
300
Middle level
3247
695
431
349
2394
493
541
284
4307
1037
465
305
Lower level
2236
501
577
251
2213
487
596
270
3876
682
356
324
SD upper
669
173
536
119
517
240
288
43
2032
416
540
56
CI upper
423
109
339
75
327
152
182
27
1285
263
341
36
SD middle
905
180
133
53
507
63
300
61
856
221
344
72
CI middle
572
114
84
34
321
40
190
39
541
140
217
45
SD lower
806
168
481
61
491
145
377
64
1121
127
196
75
CI lower
510
106
304
39
310
91
238
41
709
80
124
47
Fine earth texture, May 2001
43
Sand (%)
Silt (%)
Clay (%)
Texture
High composite
High, upper level
High, middle level
High, lower level
72.58
68.11
78.10
82.01
16.33
16.86
12.93
8.81
11.10
15.04
8.98
9.19
sandy loam
sandy loam
sandy loam
loamy sand
Low composite
Low, upper level
Low middle level
Low lower level
68.55
58.67
68.44
68.30
17.99
22.28
21.25
17.63
13.47
19.06
10.32
14.08
sandy loam
sandy loam
sandy loam
sandy loam
Control forest
composite
74.85
12.39
12.77
sandy loam
Fire intensity,
Terrace level
44
Conductivity and pH, May 2001
Low intensity
Fire intensity
Terrace level
Sample
High intensity
Control forest
µS/cm)
Cond (µ
pH
µS/cm)
Cond (µ
pH
µS/cm)
Cond (µ
pH
Upper level 1
88
6.44
80
6.61
313
5.52
2
80
6.50
63
6.47
227
6.19
3
85
6.22
102
6.65
196
6.20
4
229
5.56
125
6.42
103
6.29
5
91
6.45
66
6.49
243
5.74
6
150
5.73
56
6.14
173
6.27
7
96
6.50
63
6.40
132
5.67
8
95
6.70
59
6.63
139
6.14
9
10
69
166
6.47
6.56
76
60
6.48
6.45
219
228
5.79
5.67
Middle level 11
70
6.22
41
6.54
162
6.13
12
69
6.50
71
6.56
187
5.98
13
87
6.16
83
6.49
130
5.82
14
83
6.17
68
6.40
118
5.95
15
50
6.55
45
6.44
125
6.22
16
85
6.68
38
6.40
234
5.93
17
64
6.46
81
6.49
118
6.03
18
75
6.44
79
6.44
108
5.94
19
90
6.69
64
6.46
137
6.23
20
107
7.14
73
6.38
115
6.40
Lower level 21
67
6.49
65
6.70
132
5.79
22
87
6.47
91
6.75
147
4.93
23
144
6.04
73
6.67
241
5.33
24
64
6.33
60
6.66
169
5.49
25
44
6.47
82
6.18
266
5.85
26
73
6.38
99
6.33
167
6.00
27
71
6.30
57
6.61
185
5.96
28
92
6.10
89
6.17
172
6.08
29
136
6.35
114
6.54
109
6.68
30
56
6.13
50
6.68
146
5.86
72
6.49
171
5.94
20
7
0.15
0.06
54
20
0.34
0.13
Average/intensity
92
6.37
Standard deviation (SD), Confidence Interval (CI)
39
0.29
SD
14
0.11
CI
Average/terrace position
Upper level
172
5.95
167
5.93
197
5.95
Middle level
147
5.88
160
5.80
143
6.06
Lower level
153
6.09
140
6.17
173
5.8
45
Carbon, nitrogen (%), C:N. May 2001
Low intensity
Middle level
Control Forest
Tot- N % Tot C % C org C:N Tot- N % Tot C % C org C:N Tot- N % Tot C % C org C:N
Sample
Upper level
High intensity
1
0.36
8.60 4.99 13.85
0.10
1.49 0.86 9.07
0.33
9.22 5.26 16.18
2
0.23
5.73 3.32 14.77
0.11
1.56 0.90 8.59
0.55
12.39 4.98 9.06
3
0.30
7.81 4.53 15.10
0.14
2.30 1.33 9.53
0.53
11.15 5.53 10.43
4
0.10
3.20 1.86 18.56
0.20
4.40 2.55 12.76
0.29
6.20 7.40 25.97
5
0.13
2.92 1.69 13.55
0.37
7.41 4.30 11.62
0.70
16.83 6.74 9.70
6
0.16
3.99 2.31 14.91
0.07
1.01 0.59 8.37
0.25
5.44 4.85 19.42
7
0.25
4.75 2.75 11.23
0.17
3.49 2.02 12.27
0.19
4.40 7.12 37.46
8
0.20
5.28 3.06 15.71
0.13
2.95 1.71 13.67
0.43
8.73 7.93 18.43
9
0.17
3.43 1.99 12.04
0.14
2.92 1.69 12.10
1.06
24.59 7.02 6.65
10
0.33
7.03 4.08 12.55
0.14
2.96 1.71 12.24
0.55
13.34 7.10 13.03
11
0.31
8.36 4.85 15.90
0.11
1.23 0.71 6.79
0.51
8.09 3.94 7.73
12
0.23
5.33 3.09 13.43
0.12
2.01 1.17 10.14
0.44
10.18 5.88 13.37
13
0.72
22.04 12.78 17.76
0.18
2.81 1.63 9.04
0.46
11.55 5.24 11.40
14
0.35
10.24 5.94 17.21
0.17
2.89 1.68 10.16
0.36
8.50 5.89 16.37
15
0.24
6.95 4.03 16.80
0.13
2.12 1.23 9.46
0.65
15.80 5.49 8.44
16
0.20
4.94 2.87 14.33
0.13
2.25 1.30 10.02
0.32
7.32 5.81 18.45
17
0.35
8.70 5.04 14.62
0.13
2.23 1.29 10.35
0.36
9.19 6.00 16.91
18
0.35
10.36 6.01 17.42
0.15
2.88 1.67 11.52
0.42
10.38 6.68 16.10
19
0.15
2.75 1.60 11.00
0.52
12.93 7.50 14.42
0.33
7.54 8.37 25.35
20
0.22
5.70 3.31 15.03
0.18
3.31 1.92 10.97
0.28
6.38 6.36 22.73
21
0.28
5.84 3.39 12.10
0.15
2.62 1.52 10.13
0.32
6.93 5.88 18.66
22
0.21
4.31 2.50 11.89
0.20
3.62 2.10 10.77
0.24
7.06 6.25 26.02
23
0.19
3.35 1.94 10.21
0.13
2.27 1.31 10.51
0.45
11.63 6.10 13.70
24
0.15
3.36 1.95 13.42
0.15
2.29 1.33 9.14
0.33
8.92 5.30 16.07
25
0.08
1.34 0.78 10.36
0.07
0.91 0.53 8.12
0.27
6.43 4.71 17.77
26
0.13
2.14 1.24 9.91
0.08
1.19 0.69 8.59
0.47
10.44 4.98 10.60
27
0.12
2.18 1.26 10.54
0.11
1.85 1.07 9.76
0.45
10.97 5.66 12.57
28
0.16
4.28 2.48 16.02
0.10
1.51 0.88 8.76
0.68
16.67 5.08 7.47
29
0.09
1.41 0.82 9.62
0.16
3.03 1.76 10.98
0.30
6.73 6.37 21.24
30
0.12
3.68 2.13 17.79
0.10
1.81 1.05 11.05
0.64
15.70 6.41 10.02
Average/intensity
0.23
5.66 3.29 13.92
0.15
2.87 1.67 10.36
0.44
10.29 6.01 15.91
11.23 6.39 16.63
Lower level
Average/terrace position :
Av upper
0.22
5.27 3.06 14.23
0.16
3.05 1.77 11.02
0.49
Av middle
0.31
8.54 4.95 15.35
0.18
3.47 2.01 10.29
0.41
9.49 5.97 15.68
Av lower
0.15
3.19 1.85 12.19
0.12
2.11 1.22 9.78
0.41
10.15 5.67 15.41
Standard deviation (SD), Confidence interval (CI)
SD
0.13
3.96 2.30 2.63
0.09
2.27 1.31 1.72
0.18
4.30 0.99 6.89
CI
0.05
1.45 0.84 0.96
0.03
0.83 0.48 0.63
0.07
1.57 0.36 2.52
SD upper
0.09
2.00 1.16 2.10
0.08
1.84 1.07 1.93
0.26
6.07 1.12 9.36
CI upper
0.06
1.26 0.73 1.33
0.05
1.16 0.68 1.22
0.16
3.84 0.71 5.92
SD middle
0.16
5.33 3.09 2.11
0.12
3.38 1.96 1.93
0.11
2.72 1.12 5.70
CI middle
0.10
3.37 1.96 1.34
0.08
2.14 1.24 1.22
0.07
1.72 0.71 3.60
SD lower
0.06
1.43 0.83 2.78
0.04
0.83 0.48 1.07
0.15
3.70 0.62 5.67
CI lower
0.04
0.91 0.53 1.76
0.03
0.53 0.31 0.68
0.10
2.34 0.39 3.59
46
Appendix 2 Topsoil description, 1996
Description O and A1-horizons Nov-Dec 1996 (after Ubeda 1998:44-51; USDA).
The description has the following order: Primary constituents: texture of fine earth, rock
fragments, structure (degree, type, size), consistens.
Control forest
A - 0-7 cm (incl 0-3 cm leaves and humus), sandy loamy sand (77/20/3), few rockfragments;
weak medium angular blocky; non sticky, non plastic; common fine pores, common medium
roots.
Total-C: 4.6 %; Total-N: 0.17 %; C:N: 27; % organic matter: 7.8 %.
Ca: 2.8 meq/100gr; Mg: 1.1 meq/100 gr; Na: 0.8 meq/100 gr; K: 170 ppm; P: 1.6 ppm
CEC: 10.34 meq/100 gr.
Low intensity
O - 0-2 cm halfburned pine needles on top of halfburned and fresh humus.
sandy loamy sand (74/25/2);
Total-C: 13.9 %; Total-N: 0.38 %; C:N: 36 ; organic matter: 24 %.
Ca: 11.9 meq/100gr; Mg: 4.4 meq/100gr; Na: 2.6 meq/100 gr; K: 113.2 ppm; P: 57.7 ppm
CEC: 23.19 meq/100gr.
A - 2-6 cm sandy loam (68/28/4), few rockfragments; weak very fine subangular blocky; non
sticky. non plastic; common fine pores, common fine roots.
Total-C: 1.3 %; Total-N: 0.08 %; C:N: 16; organic matter: 2.3 %.
Ca: 4.3 meq/100gr; Mg: 2.3 meq/100gr; Na: 1.8 meq/100 gr; K: 123.2 ppm; P: 16.4 ppm
CEC: 9.10 meq/100 gr.
High intensity
O – 0-0.5 cm
Total-C: 1.6 %; Total-N: 0.07 %; C:N: 22; organic matter: 2.7 %
Ca: 5.0 meq/100gr; Mg: 1.9 meq/100gr; Na: 1.7 meq/100 gr; K: 34.3 ppm; P: 1.6 ppm
CEC: 12.18 meq/100gr.
A – 0.5-3 cm sandy loam (62/36/2). few rockfragments; weak fine granular; slightly sticky,
slightly plastic; few fine pores, few fine roots 1-2 mm.
Total-C: 0.6 % ; Total-N: 0.04 %; C:N: 16; organic matter: 1.05 %
Ca: 5.4 meq/100gr; Mg: 2.9 meq/100gr; Na: 26.1 meq/100gr. K: 26.1 ppm; P: 12.4 ppm
CEC: 8.49 meq/100 gr.
47
Appendix 3 Laboratory analysis
1) Soil preparation
air dried for two days. Soil aggregates, but not minerals, were carefully crushed and sieved at
2 mm (diameter) to separate fine earth.
2) Texture
Robinson pipette (Ubeda & Sala 1995:16-20). The same amount of each soil sample were
mixed, 20 gr. The fine earth-mix put with H2O2 (20 %) to eliminate organic aggregates in a
sandbath of 60°C. When the efervence had stops, the organic matter is eliminated. A solution
of 40 ml NaPO3 + 300 ml distilled water was kept on a volteador over the night to disperge the
particles. The soilsamples were sieved through two sizes (coarse sand 0.2 and fine sand 0.05
mm), in to a 1000 ml-test tube.
The time it takes for silt and clay fractions to descend in the 1000 ml depending on the
temperature. which gives a constant time to make the extractions at certain heights. It is
important not to disturb the solution with the pipette. The first extraction of 20 ml coarse loam
(0.05-0.02 mm), was taken immediately with the pipette at 20 cm from the surface of the
liquid. The fine loam (0.02-0.002 mm) after 4 min 22 sec, 20 ml at 10 cm from the surface.
The clay and dispersants (<0.002 mm). at 10 cm from the surface after 7 hr 16 min. The
samples were weighed before and after they were put in oven 105 °C for 24 hours to
evaporate the water.
The fraction is calculated: The total weight of the sample (g) = coarse sand + fine sand
((coarse loam – 0.0284)*50. The constant 0.0284 is the assumed weight of the dispersants.
The number 50 is multiplied by 20 ml of the suspension to get the total test tube 1000 ml.
% sand = ((coarse sand/total weight) * 100) + ((fine sand/total weight) * 100)
% loam = ((coarse loam – fine loam)*50/total weight*100) + (((fine loam – clay)*50)/total
weight*100)
% clay = ((clay – 0.0284) * 50/total weight * 100
Texture classification according to the texture-triangle USDA (1998:2-29).
3) pH (H2O)
20 g fine earth was mixed with 50 ml destilled water. After 30 minutes the pH meter (Crison
507) was calibrated at pH 7.02 and put in the suspension until the pH was stabilised (appr. 5
min). The tools were cleaned with destilled water between each measure. It is important that
all samples have the same temperature. The Crison pH- and conductivity meter automatically
calibrate the results to the temperature. (Ubeda & Sala 1995:38-39)
4) Electrical conductivity
measured with conductimeter (Crison 524), as pH (Ubeda & Sala. 1995:39-41)
5) Organic C
Weigh i) an empty porcelain pot, then ii) the pot with approximately 2 gr fine earth. After
calcination in oven 450°C for 8 hours. iii) weigh the pot and the burned soil. The common
temperature is 1100ºC, however 450°C is a locally adapted method for determining organic C
in acid soils. Combustion in 450 °C destroys the organic carbonates but not the inorganic
48
ones. This method would give very different values of Total C and the Corg-contents and
change the C:N-ratio in calcareous soils (Unpublished stud material. Ubeda pers. comm.
2001).
The organic matter is calculated:
Organic matter (%) = Organic C x 1.724 (Cobertera 1993:248)
6) Phosphorous
Osmond-Bray (Practiques d´edafologia p 34-35). The method determines assimilable
phosphorous until 200 ppm presence of Fe. It is less sensible to variations in acidity and
arsenic. Two samples were made from each soil sample (n=190). 1 gr of fine earth was put in
an ehrlenmeyer glass of 100 ml with 20 ml of extractant (NH4F 0.003N and HCl 0.1N equal
parts), mixed and filtered after 40 seconds.
Two reactants were prepared: A: A mix of a) 10 g (NH4)2MoO4 om 85 ml destilled water + b)
170 ml HCl in 16 ml destilled water. B: 50 ml of destilled water with 8 g of the mix of a) 2.5 g
1, 2, 4 aminonaftolsulfonic acid. b) 5 g of N2SO3, and c) 146.25 g of Na2S2O5.
The blank was: 12 ml destilled water + 10 drops of reactant A + 10 drops of reactant B.
The solution of the patron was 2 ml of 50 ppm P2O5 + 10 ml destilled water + 10 drops of
reactant A + 10 drops of reactant B.
Each sample: 2 ml with the filtered extract + 10 ml destilled water + 10 ml reactant A + 10 ml
reactant B.
The photometer Zuzi 4200 was calibrated at wavelenth 600 nm with 1) the blank. 2) 2 patrons
and 3) sample interpolation. It is important that the interpolation is 30 minutes after mixing
the solutions. If the samples turn too blue, it is obviously too late.
The concentration of P2O5 (ppm) is calculated: (50*reading of sample/reading of patron 50
ppm).
7) Carbon/nitrogen
Elemental analysis (EA). Soil preparation: 3-4 tablespoons fine earth was pulverised with 6
balls at speed 6 in Fritsch pulverisor and stored in 5 ml test tubes. At the laboratory 2 000-6
000 μg was weighed and folded in aluminum-folie with V2O5 as oxidising agent. Two
analyses were made from each sample.
The relation C:N is calculated:
Total organic C (%) / Total N (%) (Cobertera 1993:257-258).
8) Assimilable potassium
Ammonic acetate at pH 7 atomic adsorption analysis (AAS).
Preparation: 5 gr fine earth + 100 ml NaOH 1N (=77.08 g NaCH3COOO.3H2O/l distilled
water) was put in glasses on volteador for 24 hours. The solution was extracted twice. the
second extraction by pipette 50 ml + distilled water. Added 1 drop of NHO3 to prevent
precipitation of cations. Stored in fridge. It is important that the filters are changed between
each sample and the tools cleaned with distilled water.
9-11) Assimilable calcium, magnesium, and sodium
plasma with induction (ICP). See 8) potassium above.
49