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Resilience of floodplain ecosystems in a semi-arid environment
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Matthew J. ColloffA,C and Darren S. BaldwinB
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CSIRO Entomology, GPO Box 1700, Canberra, ACT 2601, Australia
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B
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991, Wodonga, Victoria 3690, Australia
Murray Darling Freshwater Research Centre and CSIRO Land and Water, PO Box
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Corresponding author: [email protected]
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Abstract. Implicit to loss of ecosystem resilience is that systems can shift from one
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stable state to another as a result of disturbance. We present a conceptual model of
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ecosystem resilience of floodplains and wetlands in a semi-arid environment, based
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on a single state characterised by fluctuating wet and dry phases driven by episodic
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floods and droughts. It might appear that such a single state is inherently unstable, but
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stability, and the measure of resilience, is conferred by the capacity of floodplains and
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wetlands to undergo drought and yet return to a functioning wet phase following
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inundation as well as to undergo flooding and return to the dry phase following flood
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recession. Floodplains and wetlands are driven by strong, periodic abiotic
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disturbances and their ecosystem functions and biogeochemical processes are highly
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rate-limited, spatiotemporally variable and driven by relatively species-poor
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assemblages of plants and animals adapted to withstand drought and flooding.
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Extreme drying due to climatic change and over-allocation of water resources
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represents the primary mechanism via which resilience is lost.
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Additional keywords: alternative stable state, flood, drought, ecosystem function,
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ecosystem engineer, ecosystem function.
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Introduction
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The resilience concept is becoming more prominent in the natural resource
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management literature, as well as in policy development and implementation. There is
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an increasing call for ‘management for resilience’, or ‘managing resilience into
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systems’ (Bengtsson et al. 2003; Kerkhoff and Enquist 2007). But it is usually unclear
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what it is that is being asked of managers and how they are supposed to achieve it. At
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the core of this issue is the practical, operational requirement of defining resilience of
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what to what (Carpenter et al. 2001). Before managers can get to such a definition
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they have to be clear on factors relating to resilience, and basic resilience
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characteristics of the ecosystems they are responsible for.
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The scope of this paper is primarily the floodplains of the Murray-Darling Basin,
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Australia, though the ecological principles apply to any floodplain that is subject to
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extended drought. Semi-arid floodplains occupy regions with mean annual rainfall
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between 250-500 mm per year, represented in the Murray-Darling Basin by the area
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west of the 500 mm annual average isohyet (1895-2006) approximating to an
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imaginary north-south line through the towns of Roma, Moree, Dubbo, Wagga Wagga
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and Bendigo. Of the 18 regions used in the CSIRO Sustainable Yields Audit (CSIRO,
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2008), all but the Border Rivers, Ovens, Goulburn-Broken and Campaspe regions are
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located all or in part in semi-arid regions. This constitutes some 40 major floodplain
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systems (Colloff and Jin, 2009) representing the vast majority of the 6.1 mn hectares
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of floodplain in the Murray-Darling Basin, the inundated area of which has declined
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to 1.5 mn ha in the decade to 2009, from 4.6 mn ha in the previous decade (Doody et
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al. 2009). Semi-arid floodplains of the Murray Darling include the Warrego and Paroo
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River catchments which contain one of the largest areas of wetlands in Australia and
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are in the top ten wetland systems for waterbirds (Kingsford et al. 2001).
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Floodplains in semi-arid areas are unique ecosystems because under natural
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conditions they apparently exist in two alternating phases. For most of the time they
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are in a dry phase which, at least superficially, is not substantively different than other
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surrounding terrestrial ecosystem. However, periodically these systems are inundated.
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Large, shallow floods driven by sporadic rainfall top up soil moisture, recharge the
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shallow groundwater aquifers and fill lakes and billabongs. This recharge provides the
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reservoirs of water upon which the biota depends until the next flood event (Figure 1).
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The flood and flow regime of semi-arid rivers is characterised by extreme variability
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and unpredictability (Bunn et al. 2006). Depending on location, the inundated phase
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may last for many months. Normally the inundation of a terrestrial ecosystem (or the
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drying out of an aquatic ecosystem) would be considered a significant disturbance to
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the ecosystem. However these systems seem to have evolved to cope with the phase
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change. For example, many aquatic plants have long-lived seed that can withstand
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extended periods of drought. Similarly, many animals possess drought-resistant stages
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in the life-cycle or the physiological capacity for diapause (Brock et al. 2003) or, like
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waterbirds, adopt highly-mobile strategies in order to track scarce resources.
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However, there is evidence that many of the floodplain ecosystems in the semi-arid
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regions in south-eastern Australia, especially those comprising forest and woodland,
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are in declining condition (Murray Darling Basin Commission and Brett Lane and
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Associates 2005; Cunningham et al. 2009, in press; Armstrong et al. 2009). The
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decline is due in part to river regulation and water diversions (Kingsford 2000) that
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have resulted in reduced flood duration, extent and frequency as well as shifts in the
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seasonality of flooding. Such changes in flood regimes have the potential to
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compromise the resilience of floodplains especially during periods of extended
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drought, as has been the case in southern Australia for well over a decade (Bureau of
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Meteorology 2010). Under these dry conditions species (both wet-adapted and dry-
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adapted) become locally extinct or their populations fall to levels that compromise
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their capacity to drive ecosystem functions. On subsequent flooding, the wetland biota
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fails to regenerate and temporary wetlands remain depauperate (Jenkins and Boulton,
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2007). They may take several flood events to recover (Figure 1). The dry phase biota
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and permanent biota are affected too, typically through large-scale death of trees and
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understorey vegetation, as well as loss of soil and sediment microbial diversity and
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abundance. If groundwater levels fall below the root zone of the major trees and
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understorey, then those species that depended on access to groundwater are likely to
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be succeeded by species that can survive on episodic rainfall. If lack of soil and
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groundwater recharge persists, the system is likely to undergo a shift to a new
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alternative stable state - permanent rangeland, consisting of semi-arid shrubs and
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grasses, including invasive native plants where soil moisture conditions more closely
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match their hydrological niche.
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The purpose of this paper is to explore factors that affect ecosystem resilience of
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floodplains, particularly in the face of ongoing drought conditions and a reduction of
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flooding through river regulation. Application to floodplain management of resilience
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thinking (in its ‘general’, environmental, social and economic form) has been
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elucidated by Capon et al. (2009), but there has been no conceptual floodplain
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ecosystem resilience model developed prior to the present paper. This purpose arose
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from the observations that many of these floodplain ecosystems are already highly
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modified by humans; may consist of several plant communities characterised by
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relatively few dominant species, which on the face of it suggests limited resilience
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and where shifts in stable state are driven by a small suite of strong abiotic variables,
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be they natural or anthropogenic in origin. In the context of floodplains and wetlands,
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we examine ecophysiological ‘performance’ and how it is affected by the abiotic
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disturbances of flooding and drought, as well as the constraints imposed on
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performance by biogeochemical ‘bottlenecks’.
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Resilience
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Resilience has multiple meanings and interpretations (reviewed by Brand and Jax
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2007). It has been used as a metaphor to stimulate research, as a theoretical
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framework and as an operational paradigm (Carpenter et al. 2001). In ecology, the
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term has two main uses: i) the capacity of an ecosystem to undergo disturbance but
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maintain core functions and controls (Holling 1973; Gunderson and Holling 2001); ii)
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the capacity of an ecosystem to resist disturbance and return to equilibrium afterwards
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(Pimm 1984; Tilman and Downing 1994; Suding et al. 2004). Holling (1973) defined
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resilience as ‘a measure of the ability of…systems to absorb changes in state
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variables, driving variables and parameters, and still persist’ and stability to mean ‘the
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ability of a system to return to an equilibrium state after a temporary disturbance. The
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more rapidly it returns, and with the least fluctuation, the more stable it is’. Holling
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(1973) and Holling and Meffe (1996) used these definitions to highlight contrasting
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approaches to natural resource management by juxtaposing stability, (‘equilibrium
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resilience’) as a command-and-control viewpoint of ecosystems (‘maintenance of a
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predictable world’) with ecosystem resilience that emphasises heterogeneity,
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unexpectedness and scale-dependency (‘keeping options open’).
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Implicit to loss of ecosystem resilience is that systems can shift from one stable state
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to another as a result of disturbance (Scheffer et al. 2001; Beisner et al. 2003), for
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example from woody riparian systems to grassland (Wolf et al. 2007), or from healthy
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coastal and estuarine ecosystems to hypoxic ones (Diaz 2001). An alternative stable
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state may be either non-degraded or heavily degraded (Suding et al. 2004). Resilient
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stable states may be desirable or undesirable, in contrast to sustainability, or
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ecosystem services, which contain assumptions of preference, and benefit to society
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(Carpenter et al. 2001). From a management perspective, this matters a great deal
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because it means resilience is an ecosystem property that can be either created or
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destroyed. It entails both the maintenance of resilience of a ‘preferred’ stable state in
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order to prevent the system entering a degraded, stable, less-preferred state, and also
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the breaking down of resilience of a degraded state in order to aid recovery to a
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preferred state that delivers a broader range of ecosystem functions and services.
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Resilience, a dynamic property of ecosystem structure and function, is by definition
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characterised by episodic events. This is described by the adaptive cycle, a general
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conceptual model of change in self-organising systems, based around succession,
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collapse and renewal. The cycle has phases of growth and exploitation (r),
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conservation (K), collapse (Ω) and reorganisation (α) (Holling and Gunderson 2002).
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Carpenter et al. (2001) gave examples of the manifestation of the adaptive cycle in
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some ecosystems but there are others where these processes are less apparent (Holling
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and Gunderson 2002). During the r phase, connectedness, potential and resilience are
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initially low, rising slowly and sporadically as the resources are used, species
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assemble and areas are colonised. In the K phase the system is vulnerable to major
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perturbations because its accumulated nutrients and biomass have become over-
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connected and the potential for change has peaked. Following perturbation, the rapid
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collapse or release phase (Ω) leads rapidly back to reorganisation (α) beginning the
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phase of growth, accumulation and sequestration of resources (r). This is the phase
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(α→r) at which the system is most vulnerable to change to an alternative degraded
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state, because resources can be lost from the system altogether. The relevance of the
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adaptive cycle to managers is that they may be responsible for managing different
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parts of the cycle in different parts of the system; with areas of restoration, mature
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communities, and those on the verge of collapse.
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Species Diversity, Ecological Function and Response Diversity
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The relationships between species diversity and ecosystem function are often viewed
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as the same as those between species diversity and resilience. They are related, but
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different. For many natural resource managers and scientists whose working
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definition of resilience focuses primarily the capacity of the system to recover from
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disturbance, the assumption is made that recovery is rendered more likely if there are
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more species in the system (Tilman and Downing, 1994). The evidence for this is
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equivocal, partly because there are relatively few well-understood empirical
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examples, but also because there are more mechanisms by which ecosystems attain
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resilience than by species diversity. A case in point is inland wetlands affected by
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acid sulfate soils (sulfidic sediments). Bottle Bend Lagoon near Mildura in south-
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eastern Australia was a classic billabong which contained a quite diverse aquatic
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community structure (McCarthy et al. 2006). A partial drawdown of the wetland in
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2002 resulted in exposure of acid sulfate soils to the atmosphere, oxidation of the
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sediment and ultimately acidification of the wetland. The pH of the wetland fell from
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circum-neutral to below 3, where it has remained for the last 7 years. The biodiversity
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is now quite low with few if any multi-cellular organisms alive in the wetland. A
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diverse community structure could not prevent the shift to an alternative (and quite
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resilient) stable state in the face of acidification.
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Models of species diversity and ecological function (synthesised by Petersen et al.
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1997) emphasise the relationship between stability and the ‘function space’ of species.
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The progression from the ‘species diversity equals stability’ model (MacArthur 1955),
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through Lawton’s (1994) ‘idiosyncratic effect’ model, Erlich and Erlich’s (1981)
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‘rivets’ model and Walker’s (1992; 1995) ‘drivers and passengers’ model, emphasises
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properties like niche breadth as species-related contributions to ecosystem functions.
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In relation to the effect of species removal, exemplified by the models of Erlich and
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Erlich (1981) and Walker (1992; 1995), ecosystems remain resilient because they
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contain functional redundancy and niche overlap. From this collective viewpoint, an
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intrinsic property of ecosystems, embodied in the concept of resilience, is the extent to
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which when species are lost, other species will occupy the niche space. This is the
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property of response diversity (Elmqvist et al. 2003; Nyström 2006). Functional
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diversity in an ecosystem is the property whereby similar taxa have different
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functional attributes. Response diversity represents the variability in responses of taxa
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within functional groups to disturbance (Elmqvist et al. 2003). Response diversity is a
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component of ecological ‘memory’ in relation to recovery from perturbation, and
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appears important in systems where there are several ‘driver’ species with strong
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niche overlap like coral reefs (Nyström 2006) or grasslands subject to fire (Walker et
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al. 1999), but it is harder to see how it manifests in other systems where there is little
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or no niche overlap between ‘driver’ species. One way ‘ecological memory’ and
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resilience may become manifest in semi-arid floodplains is through life-history
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strategies whereby emergence from dormancy of seeds or invertebrate eggs from
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multiple generations may be staggered with some germinating or hatching
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immediately after rains or floods, and others doing so after later events, thus spreading
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the risk if post-emergence conditions become adverse. Brock et al. (2003) referred to
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these strategies as ‘resilience through dormancy’: not all species are present at the
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same site and not all species emerge from dormancy at the same time.
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These views of resilience and ecosystem function are focussed heavily on the effect of
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the presence and absence of species, their ecological roles and interactions. Although
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some distributions of function are likely to be more resilient than others (Allen et al.
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2005), one issue that has received little attention is the relative performance of species
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and the magnitude of their contribution to processes related to ecosystem ‘health’, in
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the sense of efficiency or optimality of ecosystem function.
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Species-level components that relate to functional redundancy and niche overlap are
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relatively easy to identify for some ecosystem functions (e.g. for insect pollinators,
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invertebrate and microbial decomposers, unicellular primary producers or soil
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cryptogamic crust organisms). But for ecosystem engineers (see below) in many
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ecosystems there may be little or no niche overlap. For example, semi-arid woodland
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and forest ecosystems may consist of only a few tree species of which one or two are
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dominant (e.g. in Australia, River Red Gum Forest, Mallee woodland, Grassy Box
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Woodland and Mulga). Similar limited assemblages may be found in coastal and
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estuarine systems, such as mangrove or salt marsh. In hummock grassland, the single
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most extensive Australian vegetation type, covering almost 1.4 million square
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kilometres (National Land and Water Resources Audit, 2001), only a few species of
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spinifex (Triodia) represent the vast majority of the plant biomass.
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We suggest that resilience of ecosystems containing few dominant plant species is due
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to the diversity of physical ecosystem engineering functions combined with their
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trophic interactions, and is moderated by ecophysiological performance and affected
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by abiotic disturbances.
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Ecosystem Engineers, Trophic Interactions and Performance
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Ecosystem engineers are organisms that modulate the physical environment and its
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resources, and thus create, maintain and change habitats and resources (Jones et al.
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1994; 1997; Wright and Jones 2006). Examples include long-lived tree species
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whereby dead leaves, branches and bark falling on the ground affect rainfall impact,
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evaporation and local hydrology (Tongway et al. 1989) and provide microbial and
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invertebrate habitat; and in aquatic environments form debris dams and ponds, reduce
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erosion; provide habitat for fish and influence sediment accumulation. Live roots
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affect substrate stabilisation; root-formed cavities provide habitat for mammals and
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reptiles, alter topography through root-heave and mounding, and influence soil
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texture, aeration and water infiltration. The trunk and bark affect stem-flow
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canalisation, influencing surface ponding as well as providing habitat in the form of
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hollows, tree holes and under bark. The canopy alters microclimate, affecting shade,
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shelter, temperature and humidity, as well as mitigating erosive effects of wind and
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rainfall. These processes become more diverse and cumulative over time and are
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major drivers of ecosystem heterogeneity. In the tree example, the magnitude and
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diversity of ecosystem engineering effects is related to age and biomass of the tree
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(McElhinny et al. 2010; Killey et al. 2010). In addition, trophic resources provided by
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leaves, bark, stem, flowers, nectar and roots interact with ecosystem engineering
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processes to provide even greater levels of complexity and connectivity. So in an
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adaptive cycle context, ecosystem engineers can be regarded as agents of increasing
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connectivity, potential for change and resilience. This implies that both population age
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structure of ecosystem engineers and primary factors affecting growth and
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productivity (‘performance’) are likely to be strong drivers of ecosystem
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heterogeneity. Thus, ecosystems in which abiotic or anthropogenic disturbance factors
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constrain growth of ecosystem engineers, or where age structure is strongly skewed
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towards younger individuals, or where an event such as mass flowering is curtailed,
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are less likely to reach a full ecosystem performance potential.
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In functionally performing ecosystems the same species may be present as in ones
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performing less well. In fact loss of species is perhaps less of an indicator of
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ecosystem performance than a symptom that decline has been under way for some
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time. What is likely to differentiate ‘better performing’ from ‘less performing’ is the
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relative abiotically-driven ecophysiological constraints on the ecosystem engineers in
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the system. For example, although River red gums in Barmah Forest on the River
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Murray may be in reasonably good condition (for the most part), there appears to have
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been a reduction in frequency and extent of flowering events at some localities due to
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decreased flood frequency. The ecological significance of reduced flowering is that
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nectar supply is curtailed, with knock-on effects for those species dependent on the
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labile carbon nectar source (birds, insects, mammals, soil microorganisms). In terms
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of ‘health’ there is a continuum from the effects of disturbance that result in reduction
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in flowering frequency and extent, to effects that result in wholesale loss of trees,
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whereafter the population can only recover from the seed bank. With loss of the
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seedbank, there is no natural regeneration and restoration is required to re-establish
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populations.
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If predictors of ecosystem performance (or ‘health’ or ‘function’) include fluctuations
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in populations of ecosystem engineers and their ecophysiological performance, then
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measurements such as age structure, recruitment and vegetation condition may
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represent useful surrogates for the assessment of resilience. In this model resilience
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would represent a function of the ecophysiological plasticity (or variability) of
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populations of ecosystem engineers to withstand ecosystem-scale stresses without loss
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of function.
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Stable States and the Nature of Disturbances - Threats to Floodplain Ecosystem
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Functions and Resilience
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Two viewpoints have developed regarding the nature, existence and description of
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alternative stable states in ecological communities (reviewed by Beisner et al. 2003).
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One comes from population ecology and assumes a relatively constant environment,
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in which variables such as population density are the source of change to alternative
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stable states. Different states exist simultaneously under the same environmental
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conditions, and the community can be shifted from one state to the other by a large
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perturbation event (Figure 2a). The other, arising from ecosystem ecology, regards the
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environment as dynamic and assumes changes in ecological parameters (including
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abiotic parameters) are the major drivers of alternative stable states (Scheffer et al.,
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2001) (indicated in Figure 2d by a shift in state parameters). Parameters (or ‘slow-
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moving state variables’) are the underlying determinants of the ‘behaviour’ of the
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state variables. We consider that semi-arid floodplains exist in a single state,
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alternating between wet and dry phases driven by episodic floods and droughts
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(Figure 2a-c). It might appear that such a single state is inherently unstable but
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stability, is conferred by the capacity of floodplains to alternate between phases, i.e. to
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undergo drought and yet return to a functioning wet phase following inundation and
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then to return to the dry phase following flood recession. This capacity is in part a
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measure of the resilience of the ecosystem. It follows that resilience and stability are
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likely to be compromised following prolonged drought.
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Didham et al. (2005) noted that examples of alternative stable states that are resilient
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to restoration tend to be in communities or ecosystems that are subject to significant
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abiotic gradients (Table 1). Systems with weak abiotic gradients and disturbances
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such as coral reefs, large deep lakes and tropical forests tend not to exhibit multiple
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stable states (they give exceptions). They suggest that strongly abiotically-influenced
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systems might be more prone to enter resilient alternative states, following a lower
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level of perturbation, and be more difficult to restore than systems that are weakly
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structured by abiotic regimes. They then go on to explore whether disturbance-
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structured communities consisting of species with non-random under-dispersion of
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traits are more likely to undergo catastrophic phase-shifts. Under-dispersion of traits
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is basically lack of functional redundancy or lack of niche overlap: ‘trait under-
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dispersion should give rise to a relatively small number of alternative community
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states characterised by different dominant species, and these species will be more
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likely to resist displacement by newly arriving propagules that share very similar
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traits’ (Didham et al. 2005).
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Abiotic parameters like nutrient status, water availability, light, pH, salinity, oxygen
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concentration and temperature impact on a relatively small suite of physiological
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processes that drive growth, reproduction and development. This is the ‘bottleneck’ of
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ecosystem function, governed by hard-edged laws of biogeochemical transformations,
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chemical reaction kinetics, rate-limiting processes, enzyme-catalysed reactions and
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gene expression. Table 2 shows changes in state that are governed by a single abiotic
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parameter that impacts on the ecophysiological performance of ecosystem engineers,
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and results in stable state transformations. These examples are amongst the most stark
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and catastrophic in terms of undesirability of alternative stable state. This is because
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the degraded states are highly resilient, and therefore intractable to restoration and
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management. For example, changes in two parameters, salt and pH, account for more
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than 12 million square kilometres of land and water degradation (UNEP 1999). From
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a floodplain perspective, restoration options are few and costly (or non-existent) for
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wetlands containing acid sulfate soils (Baldwin and Fraser 2009), land affected by
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dryland salinity or acidified lakes.
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The lack of water, through both reduction in flood frequency (mostly as a
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consequence of river regulation) and on-going drought conditions has dramatically
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affected the condition of river red gums in the floodplains of semi-arid regions of
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southern Australia (MDBC and Brett Lane and Associates 2005; Cunningham et al.
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2009, in press). As noted above river red gums play an ecological engineering role in
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these ecosystems and we have suggested they impart ecological resilience to these
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ecosystems. However, notwithstanding the dramatic decline in river red gum
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condition, most of these environments have not yet reverted to an alternative stable
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state (e.g. terrestrial grassland or woodlands). We believe that that another factor is in
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play a role in imparting resilience to these ecosystems – notably soil carbon. Soil
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carbon can be considered a slow moving state variable (sensu Scheffer et al. 2001). In
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a well watered environment, soil moisture would be high, leading to healthy
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vegetation and abundant supply of litter to the soil. The resultant high soil carbon
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concentrations, enhanced by the breakdown of litter by a diverse soil micro- and
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meio-fauna, leads to better retention of water in the soil, which in a positive feedback
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mechanism maintains vegetation in a healthy condition (Figure 3). Understory
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vegetation also helps to maintain soil moisture (limiting evaporation from the soil) as
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well as limiting erosion. As the environment begins to dry there is a pulse of litter fall
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as a physiological response to desiccation, which acts as a temporary buffer for soil
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carbon. However as further drying occurs, soil moisture is lowered, health and
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productivity of the vegetation declines, reducing the litter load to the soil which
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ultimately leads to a decrease in soil carbon; which in turn impacts negatively on the
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soils ability to retain moisture – a negative feedback response. In addition die-off of
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understory vegetation would expose the soil surface, increasing the rate of
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evaporation and erosion. Therefore, at least conceptually, we can see a link between
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soil carbon and alternative stable states in floodplain ecosystems in semi-arid regions.
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The veracity of this model is currently under active investigation through funding
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from the Commonwealth Environmental Research Facilities Program (CERF, 2010).
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Conclusions
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Floodplains and wetlands do not fit the classical model of ecosystem resilience as a
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single stable state driven by biodiversity and functional redundancy and whereby loss
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of resilience is indicated by the transition to an alternative stable state. Rather they
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exist as a single state with two alternative phases, the wet phase and the dry phase
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interspersed by floods and droughts; each phase with its characteristic dominant biota.
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The stability of the system is represented by it capacity to fluctuate between the
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phases. This may appear counter-intuitive at first sight, but the measure of resilience
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that is most likely to prove ecologically meaningful is expressed by the capacity to
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undergo drought and yet return to a functioning wet phase following inundation and
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the capacity to undergo flooding and yet return to the dry phase following drawdown
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of floodwaters. Thus floodplains and wetlands are driven by strong, periodic abiotic
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disturbances characterised by dramatic changes in water availability, temperature and
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oxygen potential. Ecosystem functions and biogeochemical processes are highly rate-
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limited, spatiotemporally variable and driven not by high biodiversity, functional
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redundancy and niche overlap but by a relatively depauperate assemblage of plants
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and animals adapted to withstand drought and flooding and including several
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ecosystem engineers that provide structural elements of habitat diversity for other
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biota. In particular, we argue the ecosystem engineering role played by mature river
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red gums, and by other widespread floodplain trees in the Murray-Darling Basin
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(Coolibah, Eucalyptus coolabah, and black box, E. largiflorens), is an important
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factor in imparting resilience to floodplains under water stress. Resilience is also
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strengthened by a positive feedback loop linking soil carbon concentration to soil
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moisture and vegetation condition.
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Acknowledgements
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We acknowledge support from the Commonwealth Environmental Research Facilities
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(CERF) Significant Projects Program and CSIRO Water for a Healthy Country
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National Research Flagship. Earlier drafts of this paper were greatly improved by
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thoughtful suggestions from Dr Nick Abel (CSIRO Sustainable Ecosystems), Dr
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Gavin Rees (Murray-Darling Freshwater Research Centre and CSIRO Land and
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Water) and Nadeem Samnakay (Murray-Darling Basin Authority).
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References
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Table 1. Ecosystem characteristics of resilience and stability in relationship to degree
588
of abiotic disturbance.
589
Strong abiotic disturbance
Low species diversity
Weak abiotic disturbance
High species diversity
Dependent on very few ecosystem engineer
species with major effects
Dependent on many ecosystem engineers
with major effects
Subject to major abiotic perturbation
Subject to minor abiotic perturbation
Alternative stable states common
Alternative stable states rare
Degraded state resilient to restoration
Degraded state less resilient to restoration
e.g. semi-arid grasslands and woodlands,
wetlands, salt marshes, mangroves, shallow
lakes
e.g. coral reefs, tropical and temperate
rainforests, deep lakes
590
19
Table 2. Examples of biogeochemical processes, drivers and parameters relating to ecophysiological effects in natural ecosystems associated
with changes to alternative stable states.
Process
Changes in flood regimes
Driver
Water diversions, climate
Parameter
Water
Ecophysiological effect
Succession of terrestrial plants
change
System/state change
Reduction in wetland area -
Reference
Kingsford and Thomas 2002
permanent terrestrial
grasslands and woodlands
Reduced soil water
Overgrazing: reduced
infiltration
macropores; crusting
Eutrophication and algal
Runoff from agriculture
Water
Reduced water uptake by
Rangelands to semi-desert
Rietkerk et al. 2004
Shifts in decomposition; cell
Clear to turbid lakes, reduced
Carpenter et al. 1999
and tissue death due to algal
aquatic biodiversity
plant roots
Nutrients
blooms
toxins
Dryland salinity
Vegetation clearance
Salt
Osmotic disruption
Woodland to chenopod
Wong et al. 2007
shrubland
Hypoxia
Runoff with high labile
Oxygen
Inhibition of aerobic respiration
carbon content
Acid sulfate sediments
Drying, oxidation of pyrite,
Productive to unproductive
Diaz 2001
estuaries
pH
Direct cell and tissue damage
re-wetting
Billabongs to acid sulfate
Baldwin and Fraser 2009
swamps
Acid rain
Industrial pollution
pH
Direct cell and tissue damage
Lake and forest degradation
Likens et al. 1996
Coral bleaching
carbonic acid and
pH,
Calcium carbonate fixation
Hard corals to soft corals and
Nyström 2006
temperature increase of
Temperature,
disrupted
algae
Temperature
Succession of terrestrial
Grassland to shrubland
seawater;
Changes in fire regimes
Grazing intensity and
reduced fire frequency
shrubs
20
Anderies et al., 2002
Figure 1. Conceptual model of wet and dry phases and biomass responses to flood and
extended drought on floodplains and in wetlands in semi-arid environments.
Biomass
Biotic collapse after
extended drought
Dry phase
biota
Flow volume
Major flood drives recharge
Wet phase
biota
Minor flood too small to
drive recharge
Average return
period
Extended
drought
Commence-toflood volume
Decadal time scale
21
Average
return period
Figure 2. Model of phases shifts within a single state for a semi-arid floodplain
ecosystem. Balls represent the biotic variables, black for the dry-phase biota and
white for the wet phase biota. The difference in size represents changes in abundance
and diversity. The cup represents the ecosystem state parameters, in this case floods
or droughts (modified from two-dimensional ball-and-cup models of Beisner et al.
2003). The alternation between dry (a), wet (b) and back to dry (c) phases represent a
single state, the stability and resilience of which is conferred by the capacity to
transition between phases. An alternative stable state (d) occurs only when the
ecosystem ceases to fluctuate between wet and dry phases due to permanent drought
and cessation of flooding.
a)
b)
Change in state parameters flood
Dry phase
Wet phase
Wet phase
c)
d)
Change in state parameters permanent cessation of flooding
Change in state parameters drought
Dry phase
Alternative stable state terrestrial ecosystem
22
Figure 3. Conceptual feedback loop between soil carbon, soil moisture, soil biota and
vegetation condition. Arrows represent both self-reinforcing systems (positive
feedback) and negative reinforcing ones (negative feedback).
Soil Carbon
Soil Moisture
Soil Biota
Vegetation
Nutrient Cycling
23