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Mar Biol (2012) 159:2633–2639 DOI 10.1007/s00227-011-1863-8 ORIGINAL PAPER Origins and consequences of global and local stressors: incorporating climatic and non-climatic phenomena that buVer or accelerate ecological change Bayden D. Russell · Sean D. Connell Received: 6 October 2011 / Accepted: 19 December 2011 / Published online: 5 January 2012 © Springer-Verlag 2012 Abstract With research into the ecological eVects of climatic change intensifying over the past decade, there has been an eVort to increase the scale of experiments from a focus on individual organisms to incorporate the eVects of the structure and functioning of entire ecosystems. As the scale of investigation becomes increasingly broad, however, the number of seemingly contradictory outcomes also increases. In reality, however, change or persistence of ecological patterns represents interplay of processes across diverse scales of space and time. At one extreme, non-climatic inXuences can dominate local and short-term processes that protect systems against change or accelerate change. Here, we draw on case studies that demonstrate such contrasting situations, presenting examples where local conditions can either ameliorate or exacerbate the predicted eVects of climate change. By incorporating examples of stressors that originate and manifest at diVerent spatial scales, we also attempt to reWne some of the eVorts surrounding research into the eVects of climate change. Introduction The concept of scale has been central to ecological problem solving for over four decades (e.g. Greig-Smith 1952; MacArthur 1965). In the last 20 years, however, research that explicitly recognises the scales at which ecological pat- Communicated by U. Sommer. B. D. Russell (&) · S. D. Connell Southern Seas Ecology Laboratories, School of Earth & Environmental Sciences, The University of Adelaide, Adelaide, SA 5005, Australia e-mail: [email protected] terns, and the processes that drive them, has become increasingly common (Wiens 1989; Levin 1992; Schneider 2001). Indeed, understanding the functioning of phenomena that occurs across diVerent scales of space and time is essential to understand the processes that either buVer systems against change or facilitate change (Menge and Olson 1990; Denny et al. 2009). Nevertheless, it is often far from simple to integrate scale-dependent phenomena across global (e.g. regional weather patterns), local (e.g. microclimates caused by rocky shore topography) to micro-scales (e.g. temperature gradients around organisms). Yet, understanding how organisms respond to these diVerent environmental conditions, which act at diVerent scales, is needed if we are to accurately account for seemingly counter-intuitive changes in ecosystems, in particular where human activities alter environments (Folt et al. 1999; Crain et al. 2008). Much of the focus of how environmental conditions aVect the functioning of ecosystems has recently shifted to research into climate change per se. Early research into the ecological consequences of climate change reXected the global scale of the problem and primarily attempted to Wt broad-scale changes in environmental conditions, such as average global temperatures, to responses of organisms or populations. While observations of ecological responses to changing climatic conditions are increasingly common, this approach has lead to an increasing number of cases where population responses to changing environmental conditions are diVerent to what would be predicted. For example, alpine vegetation is generally predicted to retreat to higher altitudes with warming of global temperatures, yet in some locations they are doing the opposite (Crimmins et al. 2011). Such cases often limit progress in understanding what drives change in the distribution of species and the mechanisms that are driving these shifts. 123 2634 Increasingly, it is being recognised that the extent to which changes in ecosystems can be attributed to climate change is contingent on local conditions (Helmuth et al. 2010). Some of these interactions between climatic and local conditions are relatively intuitive, albeit with unexpected synergies. A good example of such predictions are that warming of the oceans is more likely to drive ecosystem shifts (or phase-shifts) in locations that have reduced resilience because of nutrient pollution (e.g. Carilli et al. 2009; Russell et al. 2009) or overWshing (e.g. Hughes et al. 2007; Ledlie et al. 2007). Some of these interactions are not intuitive, however, and have until recently gone unrecognised. For example, wave splash and tidal height on rocky shores can ameliorate the eVects of warming to reduce mortality below what would be predicted from regional average temperatures (Helmuth et al. 2006a). Here, we argue such seemingly discordant impacts of changing environmental conditions can be reconciled by explicitly recognising the scale of origin of environmental change and the spatial scale at which the impact manifests. Further, recognising the scale at which the impact of environmental change manifests allows recognition of how the eVects of changes that originate at the global scale can be altered by localscale conditions. Scale: origin versus impact Early research into climate change focussed not on the eVects of changing environmental conditions in ecosystems, but rather how climatic conditions themselves were likely to change and whether these changes could be attributed to human activities. As such, the scale of these investigations was both spatially and temporally large, investigating changes to global weather patterns across millennia. From an ecosystem perspective, the general view was that this ‘climate change’ is a global stressor, leading to predictions of impacts over very broad spatial scales. Therefore, early predictions of shifts in the geographical range of species focussed on contractions towards the poles (or higher altitudes) across hundreds of kilometres without consideration of the Wne scale variation in environmental conditions. Yet, it rapidly became apparent that many of these predictions were inaccurate and that the realised distribution of populations was being driven by Wner scale processes (Helmuth et al. 2010). As a result, it is increasingly being recognised that the scale of climate predictions is often discordant with the scale at which organisms experience environmental conditions. While overall warming is anticipated at the global scale, there will be substantial small-scale diVerences in the degree of warming both spatially and temporally (Easterling et al. 2000). Moreover, local conditions will either ameliorate or amplify the eVects 123 Mar Biol (2012) 159:2633–2639 of this warming (Denny et al. 2009). For example, contrary to expectations, intertidal mussels on the western coast of the USA can experience more extreme summer temperatures at more poleward locations than at lower latitudes because of the timing of low tides (Helmuth et al. 2006a). This apparent lack of agreement between predictions and observations occurs as a function of the disconnection between the scale of origin of the stressor (global) and the scale at which it manifests or impacts (local). By necessity, many of the predictions of future conditions are based on an ‘average’, which ignores Xuctuations around this mean and how local conditions will aVect it (Denny et al. 2009). Yet, the eVects of these stressors will be experienced at the level of the organism and therefore have ramiWcations at the scale of individuals and populations. While changes to environmental conditions may be at the global scale, such as increasing concentrations of carbon dioxide and temperature, how these changes will manifest in biological systems will be in part determined by the local context. Context dependency The way in which stressors originating at global scales manifest at local scales may be contingent on the physical conditions in that locality. In turn, heterogeneity in the physical environment at small spatial scales, even down to centimetres, can manifest in seemingly stochastic and often unpredictable biological responses (PandolW et al. 2011). While this type of complexity initially challenged our capacity to predict the ecological consequences of these interacting conditions, there is an increasing body of literature that demonstrates both the potential positive and the potential negative outcomes (e.g. reviews by Hawkins et al. 2009; Helmuth et al. 2010). For example, the seemingly random eVect of temperature stress in driving mortality of mussels on rocky shores can be reconciled by the identiWcation of micro-climates based on shore topography (Helmuth and Hofmann 2001). Even well-understood interactions between species, such as the rate at which Pisaster ochraceus consumes Mytilus californianus, cannot be predicted based on broad-scale temperatures, but rather require knowledge of site-speciWc environmental conditions (Broitman et al. 2009). In the open ocean, the reduced calciWcation of the coccolithophore Emiliania huxleyi under elevated concentrations of carbon dioxide is further reduced by ammonia, suggesting that the eVects of ocean acidiWcation will be contingent on local nutrient pollution (Lefebvre et al. 2011). Indeed, in some regions, the increased biomass associated with nutrient pollution has increased the acidiWcation of coastal waters (because of increased respiration, Cai et al. 2011), meaning that ecosystem responses may be diVerent in areas of oligotrophic Mar Biol (2012) 159:2633–2639 versus eutrophic waters. Therefore, recognising the scale at which diVerent stressors manifest (rather than the scale at which they originate) allows incorporation of conditions at that scale (both natural and anthropogenic) to be incorporated into models to forecast potential responses by ecosystems. Interacting stressors and synergies The eVects of changing global environmental conditions will manifest at similar scales to stressors that originate at local scales and have a long history of study, such as nutrient pollution or over-exploitation of herbivores. These local-scale stressors have produced environmental conditions that are diVerent to those naturally experienced by ecosystems (Lotze and Worm 2002) and have led to the well-documented loss of the dominant habitat-forming taxa across tropical and temperate ecosystems (e.g. Hughes 1994; Eriksson et al. 2002; Bellwood et al. 2004; Fabricius 2005; Thibaut et al. 2005; Airoldi and Beck 2007; Connell et al. 2008). In tropical systems, it is likely that the interaction between increasing concentrations of carbon dioxide, temperature and local-scale stressors will cause a synergistic negative eVect on coral reefs from two directions, the negative eVect on corals and the positive eVect on non-calcareous macroalgae (Langer et al. 2006; KuVner et al. 2008; Fabricius et al. 2011). Greater nutrient concentration on coastal reefs promotes overgrowth and smothering of reef-building corals by macroalgae (Fabricius 2005) and reduces the resilience of corals to bleaching at warmer temperatures (Carilli et al. 2009). In addition, over-exploitation of herbivorous Wsh allows macroalgae to dominate space following bleaching events (Hughes et al. 2007; Ledlie et al. 2007). The combination of these stressors is broadly predicted to cause a shift of coral reef ecosystems to be dominated by algae (Bellwood et al. 2004). In temperate marine systems, canopies of algae (c.f. reef-building corals) are the dominant habitat-formers that provide structure, survival of associated species and economic beneWt for human societies (Tegner and Dayton 2000; Steneck et al. 2002). On many coasts of the world, however, increasing nutrients from land-derived sources are driving phase-shifts where these canopies are replaced by small Wlamentous algal turfs (Eriksson et al. 2002; Airoldi and Beck 2007; Connell et al. 2008; Gorman et al. 2009). Recent research has demonstrated that increasing concentration of carbon dioxide and temperature alone may be suYcient to increase the productivity of these non-calcareous algae (Kubler et al. 1999; Connell and Russell 2010; Russell et al. 2011b). When these environmental conditions are increased concurrently with nutrients, however, the growth of opportunistic algae increases at a greater rate than would be expected from the addition of their independent eVects (Russell et al. 2635 2009). Superimposed upon this interaction between stressors of global and local origin is the observed poleward contraction of these canopy-forming algae (Ladah et al. 2003; Wernberg et al. 2011b) that may accelerate in regions where human activities have increased nutrient concentrations (Eriksson et al. 2002; Thibaut et al. 2005; Airoldi and Beck 2007; Connell et al. 2008). While organisms may show some resistance to independent stressors, their sensitivity is often altered under the concurrent application of multiple changes, resulting in eVects of a larger magnitude than anticipated from the study of independent stressors (Folt et al. 1999; Reynaud et al. 2003; Feely et al. 2004; Przeslawski et al. 2005). Therefore, on both tropical and temperate reefs, it is likely that the combination of stressors of global origin (e.g. increasing concentration of carbon dioxide and temperature) will interact with stressors of local origin (e.g. nutrient pollution and over harvesting) to reduce the resilience of these systems and to increase the frequency of ecosystem shifts from domination by one set of taxa to another, such as the shift from corals to macroalgae. Nevertheless, much work remains to be done on understanding which local biological and non-climatic processes buVer systems against broader scale changes in climate. Biological and physical amelioration Just as the interaction among multiple stressors can combine to have greater negative impacts on ecosystems, the presence of certain species or environmental conditions can ameliorate stressors. Individual organisms will respond to the local physical environment, not the average conditions over broader spatial scales (Hallett et al. 2004). In terrestrial systems, the eVects of regional climate on mortality of trees (Crimmins et al. 2011) and sheep (Hallett et al. 2004) are reduced by localised rainfall. Similarly, in marine systems, when maximum daily air temperatures coincide with high tides, the physiological stress experienced by intertidal organisms is reduced (Helmuth et al. 2002). Further, angle of the substratum can play a large role in determining the body temperature of intertidal organisms, vastly reducing physiological stress in some cases (Helmuth and Hofmann 2001). Therefore, seemingly large heterogeneity in the survival of individuals, and populations, can often be reconciled by physical amelioration over smaller scales (e.g. metres). Many physiological functions are under environmental control. In particular, rates of consumption can be strongly determined by physical conditions (Sanford 1999; O’Connor 2009) and may alter the predicted eVects of climate in determining ecological functions (Helmuth et al. 2006b; Gaedke et al. 2010). Where predictions of phase-shifts from domination by habitat-forming species in response to 123 2636 environmental stressors centre on increased productivity in the taxa that replace them, this increase in consumption by herbivores may ameliorate the eVects of changing climatic conditions (O’Connor 2009; Connell et al. 2011); for example, in southern Australia, predictions of phase-shifts from kelp forests to small Wlamentous turf-forming algae centre on increased productivity and domination by turfs with increased carbon dioxide, temperature and nutrients (Connell and Russell 2010; Russell et al. 2011a, b). With this increase in temperature, however, there should theoretically be an increase in herbivory, potentially leading to consumption of this additional primary productivity, thus enabling the system to resist the phase-shift. Therefore, recognising that production and consumption are often at least partly controlled by abiotic conditions (Sanford 2002; Lopez-Urrutia et al. 2006; O’Connor 2009) may allow measures of local environmental conditions to be integrated into predictions of how changes to environmental conditions will manifest at diVerent scales, from the physiology of individuals up to the functioning of ecosystems (Helmuth et al. 2006b). Implementing conservation measures to protect habitatforming species may also have a positive feedback that ameliorates the eVects of stressors over local scales. Habitatformers, or biogenic habitats, are often seen as ecosystem engineers (sensu Jones et al. 1994, 1997) because they can substantially alter the physical conditions in close proximity to their populations. Importantly, habitat-formers can Wll this role across environmental gradients, reducing environmental stress for other organisms that rely on them for habitat (Crain and Bertness 2006). In terrestrial systems, habitats such as forests, which alter regimes of light, temperatures and can even create their own localised weather patterns, are readily recognised to Wll this function (review by McAlpine et al. 2009). In marine systems, habitats such as kelp forests, seagrass beds and coral reefs also alter physical conditions, Wlling the same role as that of terrestrial forests. For example, in intertidal habitats, canopies of algae, such as Ascophyllum nodosum, retain moisture at low tide and ameliorate desiccation stress for benthic invertebrates (Bertness et al. 1999). In subtidal systems, algal canopies can reduce the eVects of eutrophication by limiting the growth of alternative taxa that are their competitors (Eriksson et al. 2006). Furthermore, it also seems that large stands of canopy-forming algae may have the capacity to buVer against some of the negative eVects associated with increased concentrations of carbon dioxide, such as ocean acidiWcation, using carbon dioxide in photosynthesis and increasing pH over small scales (Middelboe and Hansen 2007; Hurd et al. 2009). Likewise, primary productivity on coral reefs can increase the pH by »0.4 units during daylight hours (e.g. Jokiel et al. 2008). While this buVering eVect is likely to be over small spatial scales, probably only 123 Mar Biol (2012) 159:2633–2639 metres to tens of metres, they may be disproportionately positive on species that inhabit these locations, especially for particularly susceptible life stages (e.g. larvae and juveniles). Scale dependency Most experimental studies on the eVects of climate change to date have understandably focused on the most easily manipulated life stage of species in controlled laboratory or mesocosm experiments. There have been multiple criticisms levelled at such laboratory experiments, especially that the organisms within the experiments are thought not to function as they would in their natural environment. Therefore, while such experiments are informative on one scale, such as the physiological responses of individuals to microclimates, they cannot replicate the scales over which diVerent environmental conditions dominate local ecologies. Indeed, the diVerent processes that determine ecosystem function vary over a range of spatial and temporal scales, and caution must be used when ‘scaling-up’ experiments of limited spatial or temporal extent to make inferences about ecosystem processes (Thrush et al. 1997). Therefore, because much of our understanding of the functioning of ecosystems is based on laboratory or Weld experiments with experimental units that are limited in size, how these experimental outcomes add to our understanding of generality in ecology requires an understanding of the regional context surrounding the experiments (Thrush et al. 2000; Connell and Irving 2008). For example, seemingly contradictory outcomes among multiple spatially constrained experiments on the drivers of loss of kelp forests in Australia (dominated by Ecklonia radiata) can be reconciled by incorporating the diVerent biogeographic regions and ocean current systems into explanatory models; elevated nutrient concentrations are more likely to drive loss of kelp forests on the southern coast (Russell et al. 2005; Connell and Irving 2008; Wernberg et al. 2011a), while increased herbivory drive canopy loss on the east coast (Connell and Vanderklift 2007; Ling 2008; Wernberg et al. 2011a). Similarly, understanding the environmental drivers of loss and recovery of giant kelp (Macrocystis pyrifera) forests in the north-eastern PaciWc can only be reconciled by understanding regional oceanography (e.g. upwelling and El Nino, Dayton et al. 1992; Edwards and Estes 2006). An understanding of how regional biogeography aVects environmental conditions can also aid in reconciling both the currently observed and potential future eVects of climate change. At its most simple, environmental conditions, such as temperature, are likely to change at diVerent rates depending on regional conditions (Easterling et al. 2000), altering rates of biological change. For example, observed Mar Biol (2012) 159:2633–2639 warming of coastal waters on the east and west coasts of Australia over the past 50 years seems to be related to the relative strength of the two main continental boundary currents and has driven diVerential rates of poleward shifts of algal assemblages (Wernberg et al. 2011b). More complex interactions among processes of diVerent scale are, however, also likely. For instance, increasing concentrations of carbon dioxide, and therefore more acidic water, has been shown to be detrimental to a broad range of taxa (e.g. invertebrates, review by Fabry et al. 2008; calcareous algae, Gao et al. 1993, Martin and Gattuso 2009, Russell et al. 2009). Kelp forests can, however, locally increase pH (Middelboe and Hansen 2007), potentially buVering these negative eVects over small scales. Yet, to predict the ability of kelp forests to buVer the eVects of climate change over broad scales, we also need an understanding of processes under which kelp forests are likely to persist or decline. The mechanisms that drive loss of kelp canopies diVer between regions (e.g. the diVerent bioregions in Australia and New Zealand, upwelling dynamics in the USA), but tend to be meso-scale processes. Therefore, to gain a full understanding of the small-scale dynamics among locations, we also need to know the broader scale processes that will modify them (Connell and Irving 2008). We argue that the value of experiments may be improved by including information on the context dependency of the outcomes. Explicit recognition of this scaledependent information progresses our understanding of impacts in ecosystems in two ways. First, knowledge of the scale of the environmental conditions which cause the greatest impact in a system will then also allow identiWcation of the key organisms and life stages that will be aVected (Russell et al. 2011a). Second, recognition of the scale at which diVerent stressors manifest allows explicit incorporation of a range of stressors into the experiments and models. Such multi-factorial studies would then allow identiWcation of the relative strength of stressors, originating at global- (thousands of kilometres) to meso- (hundreds to tens of kilometres) to local-scales (hundreds of metres to kilometres), in either the maintenance or degradation of diVerent systems. Therefore, while the study of climatic stressors on small scales provides insights into how well single species will respond, an understanding of local-toglobal scale interactions between multiple stressors in biological communities is required to identify how ecosystems will function under predicted changes in our climate. Conclusions The scales of observation for environmental stressors may need more consideration than we currently allow (Hallett et al. 2004). Much of the recent discussion on the eVects of 2637 climate change in biological systems focuses on broadscale conditions, yet this often leads to the failure to detect and predict ecological dependences at medium to small spatial and temporal scales. Importantly, forecasts of ecological responses over large geographical scales require an understanding of how environmental conditions vary at relevant scales. Therefore, forecasts that incorporate interactions between climatic and non-climatic impacts, demonstrating how these eVects vary according to context (i.e. variation in abiotic and biotic conditions), will be essential to accurately predict the ecological consequences of changing environmental conditions. Demonstrations of an eVect of one or two climate variables (e.g. elevated carbon dioxide and temperature) without showing the local conditions in which these eVects occur are diYcult to interpret because they lack realism and context. 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