Climate change and freshwater ecosystems: impacts across multiple levels of organization - PubMed (original) (raw)

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Climate change and freshwater ecosystems: impacts across multiple levels of organization

Guy Woodward et al. Philos Trans R Soc Lond B Biol Sci. 2010.

Abstract

Fresh waters are particularly vulnerable to climate change because (i) many species within these fragmented habitats have limited abilities to disperse as the environment changes; (ii) water temperature and availability are climate-dependent; and (iii) many systems are already exposed to numerous anthropogenic stressors. Most climate change studies to date have focused on individuals or species populations, rather than the higher levels of organization (i.e. communities, food webs, ecosystems). We propose that an understanding of the connections between these different levels, which are all ultimately based on individuals, can help to develop a more coherent theoretical framework based on metabolic scaling, foraging theory and ecological stoichiometry, to predict the ecological consequences of climate change. For instance, individual basal metabolic rate scales with body size (which also constrains food web structure and dynamics) and temperature (which determines many ecosystem processes and key aspects of foraging behaviour). In addition, increasing atmospheric CO(2) is predicted to alter molar CNP ratios of detrital inputs, which could lead to profound shifts in the stoichiometry of elemental fluxes between consumers and resources at the base of the food web. The different components of climate change (e.g. temperature, hydrology and atmospheric composition) not only affect multiple levels of biological organization, but they may also interact with the many other stressors to which fresh waters are exposed, and future research needs to address these potentially important synergies.

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Figures

Figure 1.

Figure 1.

Schematic of studies into climate change impacts in fresh waters arranged along gradients of control, replication and realism, highlighting the links between different levels of organization investigated and the approaches used.

Figure 2.

Figure 2.

Stream benthic food webs along a thermal gradient in the Estaragne Basin, French Pyrénées. Open circles denote basal resources; grey denotes primary consumers; black denotes predators. (a) 2370 m altitude, maximum water temperature (T_max) = 4.5°C, no. species (S) = 16, secondary production (2_P) = 4.9 g m−2 y−1. (b) 2150 m altitude, _T_max = 8.5°C, S = 25, 2_P_=6.55 g m−2 y−1. (c) 1850 m altitude, T_max = 13°C, S = 30, 2_P = 7.6 g m−2 y−1. Figures redrawn from Lavandier & Décamps (1983).

Figure 3.

Figure 3.

Hypothetical unimodal relationship between local species richness and temperature. In relatively equitable environments, where most species are close to their thermal optima, we might expect richness to decline with warming (trajectory B). However, this scenario is unlikely to be ubiquitous: in systems close to the physiological limits of existence for most organisms (e.g. in polar regions: trajectory A), increases in temperature may lead to rises in local richness following invasion by less cold-tolerant species. This scenario, however, implies a loss of global diversity as specialist cold stenotherms are replaced by the more diverse eurytherms.

Figure 4.

Figure 4.

Potential effects of elevated temperature and altered nutrient quality of resources on metabolic (a,b,c,d), foraging (e,f,g,h) and stoichiometric constraints (i,j,k,l) over multiple levels of biological organization (individual, population, community and ecosystem). The relationships with temperature relate primarily to the ectotherms that dominate freshwater communities. All axes are log–log scales. (a) Per capita BMR increases with body mass (indicated by the solid line) with the scaling exponent, β = ¾ (Peters 1983). Metabolic demands will rise with warming (Brown et al. 2004; Yvon-Durocher et al. 2010; dashed line). (b) Mass-dependence of population abundance (solid line), where a common exponent of β =−¾ is predicted (Brown et al. 2004). As individual metabolic rates rise, warming is likely to result in a decrease in total biomass, given steady-state conditions (Brown et al. 2004). (c) Body-mass–abundance relationships across trophic levels (solid line), where a scaling exponent β =−1 is predicted (Brown et al. 2004; Woodward et al. 2005). In addition to changes in total biomass (dashed line), warming should induce transient changes in body size spectra as large, rare species high in the food web are lost first (e.g. Petchey et al. 1999; dashed arrow). In contrast, in very cold systems under physiological stress, warming could stimulate productivity, allowing food chains to lengthen and the size spectrum to broaden (Lavandier & Décamps 1983; Friberg et al. 2009; Milner et al. 2009; solid arrow). (d) Relationship between rates of resource turnover and average consumer body mass (solid line). Resources flux faster through assemblages of small individuals: the exponent of this relationship follows that of mass-specific metabolic rates, β = −¼ (Brown et al. 2004). Thus, warming will elevate process rates and changes in community size structure will also have consequences at the ecosystem level (bi-directional arrow). (e) Per capita foraging capacity (solid line) increases with body mass with an exponent β < 1 (Persson et al. 2000; Bystrom & Andersson 2005). Warming will elevate individual foraging rates (dashed line) (Woodward & Hildrew 2002). (f) Critical resource density (CRD), whereby energy intake balances metabolic demands, increases with increasing body size (solid line). Within a population, this could give smaller individuals a competitive advantage (Persson 1985) as warming should increase the CRD required by consumers (dashed line) and may further favour small individuals in the population (solid arrow). (g) Predation matrix describing a food web with resources (rows) and consumers (columns) (e.g. Beckerman et al. 2006), ordered in body size bins. Circles denote realized feeding links, and those below the 1 : 1 line indicate consumers feeding on resources smaller than themselves (Petchey et al. 2008). Here, the largest consumer displays adaptive feeding on successively smaller resources (open circles) as a result of size-dependent foraging and higher metabolic offset with warming (solid arrow). (h) Mass-specific resource use decreases with body mass (solid line) and is likely to be displaced by warming (dashed line) in a comparable manner to the relationship predicted by MS (d). Similarly, associated changes in community size structure have consequences at the ecosystem level (bi-directional arrow). (i) Per capita rates of exploitation of a given resource may (a) increase with increasing consumer–resource stoichiometric imbalances (e.g. C : N or C : P ratios) if individuals feed in a compensatory manner (dotted line), or (b) are temporally impaired if consumers switch to alternative resources (dashed line) (e.g. Sterner & Elser 2002). (j) Increased inefficiencies resulting from consumer–resource stoichiometric imbalances should slow population biomass growth rates (e.g. Tuchman et al. 2002; dotted line). These effects might be mitigated to some extent if stoichiometric demands can be met by switching to alternative resources (e.g. herbivory versus detritivory, after Ledger & Hildrew 2001; dashed line). (k) Body mass–abundance relationships (solid line) comparable to those predicted by MS (c). The scaling exponent could increase if assimilation efficiency across trophic levels is reduced via lower nutritional quality of resources and suppressed biomass production (e.g. Tuchman et al. 2002; dashed line). (l) Ecosystem rates of resource turnover increase (at least transiently) with increasing stoichiometric imbalances due to the compensatory feeding performances of individuals (dotted line), or decrease due to resource switching and/or reduced biomass production (dashed line).

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