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The mechanisms causing extinction debts
Opinion
The mechanisms causing extinction debts Kristoffer Hylander and Johan Ehrle´n Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-106 91 Stockholm, Sweden
Extinction debts can result from many types of habitat changes involving mechanisms other than metapopulation processes. This is a fact that most recent literature on extinction debts pays little attention to. We argue that extinction debts can arise because (i) individuals survive in resistant life-cycle stages long after habitat quality change, (ii) stochastic extinctions of populations that have become small are not immediate, and (iii) metapopulations survive long after that connectivity has decreased if colonization–extinction dynamics is slow. A failure to distinguish between these different mechanisms and to simultaneously consider both the size of the extinction debt and the relaxation time hampers our understanding of how extinction debts arise and our ability to prevent ultimate extinctions. Delays in local and global extinctions It is a common notion that we are in the midst of a massextinction event caused by human-driven habitat loss, habitat modification, and climate change [1,2]. Compared with the predicted levels of extinction, relatively few species have as yet gone globally extinct [3]. Moreover, at regional and local scales the number of extinctions is surprisingly low given large-scale habitat loss [4,5]. Part of this discrepancy might be explained by overestimation of extinction rates [6]. However, an important explanation for differences between predicted and observed extinction rates is that both local and global extinctions are delayed [3,7,8]. To provide policy-makers and practitioners with efficient tools to halt losses, research thus needs not only to assess the size and distribution (among regions, habitats, or taxonomic groups) of this extinction debt, but also to examine the mechanisms behind and consequences of time-lagged species extinctions. An area is said to have an extinction debt when the number of species is greater than the equilibrium level predicted from the actual habitat loss or degradation [9]. Accordingly, extinction debts are mostly examined at the level of species richness, as evident from two recent reviews on extinction debts [9,10] and many case studies [11–13]. However, extinction debts in terms of species richness are ultimately the result of delayed extinctions of many different species and each species will respond individualistically to a given change. To elucidate the mechanisms underlying extinction debts, it is thus Corresponding author: Hylander, K. ([email protected]). Keywords: colonization credit; extinction; extinction debt; metapopulation; population; remnant population; time lag.
important to shift the focus from species richness and to explore mechanisms at the level of individual species. Multiple mechanisms might cause extinction debts The extinction debt concept was originally formulated under the theoretical frameworks of island biogeography and metapopulation dynamics, emphasizing the role of disrupted connectivity leading to lower colonization after stochastic extinctions, and this is still the most common use of the concept ([9], but see [10,14]). We argue that mechanisms acting at the levels of individuals and populations can also result in extinction debts and that this fact has not been explicitly considered in the literature (but see [10]). Neglecting the actual mechanisms that cause extinction debts might be a reason why management recommendations intended to prevent ultimate extinctions are often vague and do not target specific aspects of habitat restoration (quality, quantity, or connectivity). In this paper we first discuss the relationship between the size and duration of the extinction debt and argue that both are of key importance. We then examine how extinction debts at the level of individual species can arise from mechanisms acting at different organizational levels. Finally, we discuss the implications of these points for traitbased differences among species and conservation management. The aim of the paper is to draw attention to some neglected aspects and provide a framework that enhances our understanding of extinction debts. Extinction debts and relaxation time An important aspect when examining extinction debts is to simultaneously consider both the size of the extinction debt and the relaxation time (the duration of the extinction debt). This is because it is the combination of these two that determines the likelihood of finding extinction debts at any given time (Figure 1) [9,15]. For a single species, the size of an extinction debt has been defined as the difference between the current occupancy of a species (e.g., measured as the number of populations in an area) and the level of the occupancy at a new equilibrium when the extinction debt is paid [9]. Such measures of extinction debts implicitly assume that there is a reference level, or equilibrium, to which the effects of the perturbation can be compared. Here, we use the word equilibrium to denote periods of higher stability relative to periods or point events of great change, for example, the situation in a rainforest previously unaffected by logging that become fragmented by forestry clearfelling.
0169-5347/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tree.2013.01.010 Trends in Ecology & Evolution, June 2013, Vol. 28, No. 6
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Trends in Ecology & Evolution June 2013, Vol. 28, No. 6
Occupancy
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Figure 1. Principal relationship between the size of an extinction debt and the relaxation time (the time over which the debt is paid and a new equilibrium level is reached). The linear expression shown in the figure is just one simple example of many possible monotonic relationships. t0 is the time at which the habitat has just changed and no extinctions have taken place yet and te is the time at which all extinctions have occurred and a new equilibrium has been reached. Ot0 and Ote represent the occupancy (e.g., number of populations) at t0 and te, respectively.
The extinction debt observed at any given time will depend on the relationship between the size of the extinction debt and time since habitat change (Figure 1). This relationship is, in turn, determined by the sensitivity of the species to habitat change, that is, the maximum (initial) size of the extinction debt, as well as by how fast the debt is paid. Many studies do not clearly distinguish between these two aspects of the extinction debt [12,16,17]. This is problematic because both aspects simultaneously influence the size of the extinction debt observed at a given point in time, and because different species attributes might influence the expected total number of extinctions and the time it will take for these extinctions to occur. Magnitude of habitat change and extinction debts The expected new equilibrium occupancy after a habitat change will be negatively related to the magnitude of the habitat change (Figure 2a,b). Accordingly, the maximum size of the extinction debt will increase monotonically with habitat change, directly mirroring the shape of the relationship between occupancy change and habitat change (Figure 2c). By contrast, the time to extinction is expected to decrease with increasing habitat deterioration (Figure 2d). Because the risk of extinction for a given population is likely to increase monotonically with habitat deterioration whereas the time to extinction decreases, we might expect the highest probability of finding extinction debts at some intermediate level of habitat change (Figure 2a). This constitutes another important reason why it is important to simultaneously consider both the extinction debt and the relaxation time. Mechanisms of delayed extinctions Species persistence in an area can be understood as the result of processes acting at different hierarchical levels and influencing the survival of individuals, populations, or metapopulations. At the level of an individual, long-term persistence depends on survival rates during different 342
phases of the life cycle, which in turn depend on habitat quality. It is important to bear in mind that habitat quality does not only refer to abiotic conditions; biotic interactions are also important, and co-extinctions and trophic cascades might be important sources of extinctions [18]. Populations will persist as long as individuals survive or are replaced by recruits. Population survival is thus a function of the vital rates in different individuals. However, population attributes such as size and structure are also important for population survival because they influence demographic and environmental stochasticity. At the metapopulation level, persistence is possible if local population extinctions are balanced by establishment of new populations. However, if the patches of suitable habitat become too isolated, colonizations will no longer balance extinctions, and this will eventually lead to extinction of the whole metapopulation. It is thus important to note that processes at several organizational levels influence whether species will persist or become extinct in an area (Figure 3). It is equally important to recognize that these different mechanisms not only influence the probability of a species ultimately becoming extinct, but also the time to extinction. Individual vital rates Alteration of habitat quality will often ultimately lead to extinctions. However, if one or several life history stages of individuals is resistant to deteriorated habitat quality, population extinction can be delayed. In plants, long life spans of physiological individuals occur in trees and in small herbs [19]. In many clonal organisms, genetic individuals can attain very long life spans through the survival and proliferation of physiologically more or less independent ramets, such as in a rhizome network of the bracken fern or a moss carpet. Dormant life stages, including seed and spore banks and zooplankton egg-capsules, can also delay extinctions in unfavorable environments [20]. Populations persisting through the survival of long-lived individuals or dormant life stages in spite of a deteriorated environment and ceased recruitment have been termed remnant populations [21]. However, the resistance of individuals to deteriorated habitat quality need not be associated with particular life history stages. If vital rates in general are resistant to changes, then the average performance of individuals after a habitat change might only fall slightly below the level needed for individuals to replace themselves. Although the population is doomed to eventual extinction, this extinction will occur only after a considerable time lag. Stochastic population processes As described above, populations might persist for a considerable time after the conditions allowing long-term survival have been altered because individuals are persistent or because vital rates correspond to only slightly negative population growth rates. However, even if mean vital rates correspond to a positive population growth rate, demographic and environmental stochasticity might eventually lead to local extinctions. This is particularly true for small populations and for populations with fluctuating vital rates [22]. Besides experiencing a greater risk for extinction from stochastic events, small populations might
Opinion
Trends in Ecology & Evolution June 2013, Vol. 28, No. 6
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Figure 2. Size and duration of extinction debts as a function of habitat change. (a) Occupancy for a species in terms of the number of populations in the focal area at different times as a function of habitat change. t0 is the time at which the habitat has just changed before any extinctions has taken place; t1 and tx are different time intervals after habitat change; and te is the time at which a new equilibrium is reached, that is, when all extinctions have occurred. (b) Two examples of different occupancy versus habitat change relationships. The upper (red) curve illustrates a situation in which a small habitat change leads to only small changes in occupancy, whereas greater changes lead to a more rapid decrease in occupancy. The lower (blue) curve shows a species that is sensitive to small changes. (c) Size of the extinction debt (delta occupancy) as a function of habitat change. (d) Expected mean time to extinction as a function of habitat change. The thin lines in (c) and (d) illustrate that many monotonic relationships are possible.
also experience reduced mean vital rates due to Allee effects [23]. Small populations also face higher extinction risks due to genetic stochasticity in terms of inbreeding or loss of genetic variation [24]. The increased risk of stochastic extinction after habitat deterioration might, however, often be low and allow considerable persistence time [8]. As a consequence, populations that have recently experienced a decrease to a size below a critical level will experience an extinction debt. Processes at the metapopulation level Most studies of extinction debts are undertaken within an island biogeographic or metapopulation conceptual framework [9,17,25]. In a metapopulation at equilibrium, local extinctions are balanced by immigration and recolonization. The local populations within a metapopulation might also be rescued from extinction by immigrations from other subpopulations. A decrease in connectivity can lead to both lower recolonization rates after extinctions and higher extinction rates in patches that were previously rescued by immigrants [26]. This will result in a new lower equilibrium or extinction of the whole metapopulation. However, new equilibrium levels of patch occupancy in a metapopulation are often reached only after considerable delay if the extinction rate of local populations is low (see above) or if colonization rates are only slightly lower than the extinction rates (analogous to a slightly negative population growth rate). In a recently disturbed landscape, a species will therefore often be found in a higher proportion
of patches than the equilibrium level associated with the connectivity of the altered landscape; in other words, there is an extinction debt. The relative importance of processes at multiple levels The relative importance of mechanisms acting at different organizational levels in causing extinction debts is likely to depend on the type of habitat change, as well as on species traits. The example in Figure 3 of extinction debts in a stream network clearly illustrates how extinction debts can be the result of mechanisms at several levels. In our opinion, mechanisms at the level of individuals and populations have been given too little attention in the literature, whereas mechanisms at the metapopulation level have routinely been suggested as explanations for extinction debts. This is likely to be explained by a greater research focus on effects of fragmentation (in a broad sense) of natural environments, which inevitably involves changes in connectivity [9,12,27]. It is also true that processes at multiple levels often occur simultaneously. For example, connectivity changes are often closely associated with habitat loss and changes in habitat quality in real-world situations, such as forest fragmentation in the Amazon during the 20th century and the conversion of semi-natural grasslands to plowed fields or forests in late 19th century in northern Europe. Changes in habitat size and quality might also be the main cause of extinction debts (Figure 3). To prevent future extinctions, it is thus important to assess the relative contributions of changes in 343
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Figure 3. Mechanisms at different organization levels creating extinction debts, exemplified for an aquatic organism (e.g., freshwater pearl mussel) in a stream network. (a) Habitat quality changes (e.g., acid rain) affect the vital rates of individuals (e.g., cessation of reproduction). (b) Habitat quantity changes affect the size of local populations (e.g., many populations diminished because of canalization) making them prone to extinction due to environmental and genetic stochastisity. (c) Habitat connectivity change prevents dispersal (e.g., of trout, which disperse mussel larvae) and no rescue of populations or recolonization of extinct populations can occur. The maximum extinction debt is the difference in the number of populations at t0 and te, but the actual size of the extinction debt will decrease over time.
habitat quality, quantity, and connectivity to extinction debts. It is also important to recognize that the different mechanisms that can result in extinction debts are hierarchically nested. Metapopulation dynamics depends on population dynamics and a population will not become extinct until the last individual dies. We should therefore expect that it takes longer time to reach equilibrium at the metapopulation level than it takes for effects to be fully expressed at the level of individuals. This is easiest seen when comparing worst-case scenarios for changes in habitat quality versus changes in habitat connectivity. In the case of a devastating change in habitat quality, all individuals will die shortly after the alteration (e.g., wetland plants on a marsh after drainage of the water), meaning that the relaxation time is short and the extinction debt will be quickly paid. By contrast, if connectivity is reduced to the point at which colonization ceases entirely, then the size of the extinction debt will diminish only as local populations become extinct. As a result, the size of the extinction debt will often be greater for greater changes in connectivity over a considerable period of time, whereas for changes in habitat quality the extinction debt will often be greatest for intermediate levels of change (compare t1 and tx in Figure 2a). Trait-based differences and extinction debts It has been suggested that several species traits, including longevity, turnover rate, and dispersal capacity, correlate with the presence of an extinction debt [9,13,16,27,28]. 344
Although traits are characteristics of individuals, they can have effects on the size and relaxation times of extinction debts via different organizational levels. For example, life histories including dormant life stages can increase the relaxation time at the level of individuals, and species with good dispersal and recolonization capacities might have a longer relaxation time at the metapopulation level. A detailed examination of all proposed relationships between traits and extinction debts is beyond the scope of this paper. However, we argue that relationships between traits and extinction debts (and/or relaxation times) are more easily identified if linked to a specific mechanism. For example, dispersal capacity will influence neither the size of the extinction debt nor the relaxation time in the case of a habitat quality change, but it will be important if connectivity is altered (compare the first and third columns in Figure 3). For the research field to develop it is important that hypotheses about relationships between traits and extinction debts not only explicitly consider multiple mechanisms, but also make a clear distinction between extinction debt size and the relaxation time. Species traits can influence responses to a habitat change, in terms of both the change in occupancy (Figure 2c) and the time it takes to reach a new equilibrium (Figure 2d). Hence, the probability of finding extinction debts should be greatest for species with a combination of traits that simultaneously increase time to extinction (shallower slope in Figure 2d) and sensitivity to habitat changes, in terms of the probability of eventual extinction (steep slope in
Opinion Figure 2c). In cases in which traits influence the extinction debt size and the relaxation time in different directions, it might be difficult to predict their net effect. For example, it can be predicted that a species at a higher trophic level will be more affected by a given habitat loss than a species at a lower trophic level, and will thus show a greater potential extinction debt directly after such a change compared to a low-trophic species (a steeper slope in Figure 2c). However, it is also likely that the species at the higher trophic level will reach a new equilibrium faster because of a smaller population size, leading to a decrease in the duration of the extinction debt (a steep slope in Figure 2d). A failure to simultaneously consider both extinction debt and relaxation time is thus likely to lead erroneous predictions about relationships between traits and extinction debts. Management The existence of an extinction debt will sometimes also provide a possibility for restoration before the debt is paid [9,29]. We argue that for restoration to be successful, it is important to know to what extent the extinction debt is related to: (i) a deterioration in habitat quality leading to negative population growth rates and remnant populations; (ii) smaller populations susceptible to extinctions due to genetic deterioration or environmental or demographic stochasticity; or (iii) fragmentation and loss of connectivity leading to lower recolonization rates (Figure 3). It is evident from Figure 3 that fundamentally different processes can give rise to extinction debts, and management interventions should consider this. Processes at the individual level are predicted to be important after deteriorations in habitat quality due to climate change, pollution, or ceased or changed management. Studies of vital rates of individuals and growth rates of populations can provide some guidance in such situations. For many organisms with resilient life stages, it might be more crucial to focus conservation efforts on restoring and maintaining habitat quality than to increase landscape connectivity within the near future [30]. At the population level there will often be a time lag between reductions in population size following habitat loss and local extinctions. For such populations, increasing the amount of suitable habitat is likely to constitute the most efficient way to reduce the extinction risk [31,32]. Finally, for sites that have an extinction debt at the metapopulation level, measures to increase connectivity in the landscape are necessary [33]. Ultimately, in the very long run, sources for recolonization will be important for all species because ecosystems are dynamic and local extinctions are inevitable [34]. However, for practical conservation over shorter time frames, the relative returns on investments to increase habitat and quantity and connectivity will be closely linked to the assumed path to extinction (Figure 3). Concluding remarks In this paper we argue that studies of extinction debts have so far paid little attention to the fact that the likelihood of finding extinction debts after habitat changes is determined by both extinction debt size and relaxation time. In addition, studies have rarely considered that extinction
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Box 1. Directions for future research on extinction debts We propose that three important aspects should be considered to improve our ability to assess the size and relaxation time of extinction debts, to identify means to prevent extinctions, and to identify species with trait combinations that make them particularly likely to have extinction debts. Extinctions occur at the species level and species respond individualistically to habitat changes. To understand the mechanisms behind relationships between different types of habitat change and the size of extinction debts, we therefore need to complement studies at the community level focusing on species richness with studies focusing on processes in individual species. Both the initial size of extinction debts and their relaxation time influence the debts that we can actually observe at a given point in time. Some combinations of habitat changes and species traits may result in large but rapidly disappearing debts, whereas other combinations may result in smaller but more persistent debts. Moreover, a given trait may influence the size and relaxation time of extinction debts in opposite directions. Studies trying to link the size of extinction debts to habitats, disturbance types, or species traits will therefore benefit from considering effects on the size of the extinction debt and effects on its relaxation time separately. We thus need studies that monitor species over many years or data collected at different time intervals after habitat changes to assess how the size of an extinction debt develops over time (Figure 1). Extinction debts may be caused by mechanisms acting at the individual, population, and metapopulation levels. Distinguishing between mechanisms acting at different organizational levels will help us to understand how different types of habitat change are linked to extinction debts, and how differences among species in these relationships are linked to functional traits. Moreover, conservation efforts to prevent ultimate extinctions should critically depend on identifying the mechanisms that are mainly responsible for the extinction debt. To better understand the relative importance of mechanisms, studies focusing on metapopulation processes and connectivity of populations need to be complemented by studies of how processes at the levels of individuals and populations contribute to extinction debts. We suggest that demographic studies after habitat changes will be useful in investigating the role of individual- and population-level processes for extinction debts. We also propose that there is a need for more studies on extinction debts after many different types and intensities of habitat change.
debts can arise due to fundamentally different mechanisms, associated with the vital rates of individuals, the size of populations, and their susceptibility to stochastic extinctions, or the colonization processes maintaining metapopulations. We have also argued that as a consequence, attempts to link species life cycles and traits to the prevalence of extinction debts need to consider that effects can occur both via debt size and relaxation time, as well as through mechanisms acting at different organizational levels. Although the different mechanisms rarely act in isolation and environmental changes often simultaneously affect habitat quality, quantity, and connectivity, awareness of the complexity and the specifics of each case is likely to promote our understanding and aid in optimizing management to prevent ultimate extinctions. We suggest that future research on extinction debts should focus more on the species level, on how debts develop over time since habitat change, and on the mechanisms causing debts (Box 1). We hope that the ideas presented here will inspire researchers to take a more mechanistic approach to studies of extinction debts and encourage conservationists to 345
Opinion elaborate mitigation actions that correspond to the prime cause of such debts. Acknowledgments We thank Johan Dahlgren, Mats Dynesius, Ove Eriksson, and two anonymous reviewers for valuable comments on previous drafts of the manuscript.
References 1 Pimm, S.L. et al. (1995) The future of biodiversity. Science 269, 347–350 2 Barnosky, A.D. et al. (2011) Has the Earth’s sixth mass extinction already arrived? Nature 471, 51–57 3 Stork, N.E. (2010) Re-assessing current extinction rates. Biodivers. Conserv. 19, 357–371 4 Larsen, T.B. (2008) Forest butterflies in West Africa have resisted extinction . . . so far (Lepidoptera: Papilionoidea and Hesperioidea). Biodivers. Conserv. 17, 2833–2847 5 Sang, A. et al. (2010) Indirect evidence for an extinction debt of grassland butterflies half century after habitat loss. Biol. Conserv. 143, 1405–1413 6 He, F.L. and Hubbell, S.P. (2011) Species–area relationships always overestimate extinction rates from habitat loss. Nature 473, 368–371 7 Hanski, I. and Ovaskainen, O. (2000) The metapopulation capacity of a fragmented landscape. Nature 404, 755–758 8 Dullinger, S. et al. (2012) Extinction debt of high-mountain plants under twenty-first-century climate change. Nat. Clim. Change 2, 619– 622 9 Kuussaari, M. et al. (2009) Extinction debt: a challenge for biodiversity conservation. Trends Ecol. Evol. 24, 564–571 10 Jackson, S.T. and Sax, D.F. (2010) Balancing biodiversity in a changing environment: extinction debt, immigration credit and species turnover. Trends Ecol. Evol. 25, 153–160 11 Krauss, J. et al. (2010) Habitat fragmentation causes immediate and time-delayed biodiversity loss at different trophic levels. Ecol. Lett. 13, 597–605 12 Cousins, S.A.O. and Vanhoenacker, D. (2011) Detection of extinction debt depends on scale and specialisation. Biol. Conserv. 144, 782–787 13 Vellend, M. et al. (2006) Extinction debt of forest plants persists for more than a century following habitat fragmentation. Ecology 87, 542– 548 14 Tilman, D. et al. (1994) Habitat destruction and the extinction debt. Nature 371, 65–66 15 Diamond, J.M. (1972) Biogeographic kinetics – estimation of relaxation-times for avifaunas of Southwest Pacific Islands. Proc. Natl. Acad. Sci. U.S.A. 69, 3199–3203
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16 Saar, L. et al. (2012) Which plant traits predict species loss in calcareous grasslands with extinction debt? Divers. Distrib. 18, 808– 817 17 Marini, L. et al. (2012) Traits related to species persistence and dispersal explain changes in plant communities subjected to habitat loss. Divers. Distrib. 18, 898–908 18 Colwell, R.K. et al. (2012) Coextinction and persistence of dependent species in a changing world. Annu. Rev. Ecol. Evol. Syst. 43, 183–203 19 Garcia, M.B. et al. (2011) No evidence of senescence in a 300-year-old mountain herb. J. Ecol. 99, 1424–1430 20 Mergeay, J. et al. (2007) Extinction, recolonization, and dispersal through time in a planktonic crustacean. Ecology 88, 3032–3043 21 Eriksson, O. (1996) Regional dynamics of plants: a review of evidence for remnant, source-sink and metapopulations. Oikos 77, 248–258 22 Lee, A.M. et al. (2011) Demographic stochasticity, Allee effects, and extinction: the influence of mating system and sex ratio. Am. Nat. 177, 301–313 23 Dennis, B. (2002) Allee effects in stochastic populations. Oikos 96, 389– 401 24 Nieminen, M. et al. (2001) Experimental confirmation that inbreeding depression increases extinction risk in butterfly populations. Am. Nat. 157, 237–244 25 Mouquet, N. et al. (2011) Extinction debt in source–sink metacommunities. PLoS ONE 6, e17567 26 Hanski, I. and Ovaskainen, O. (2002) Extinction debt at extinction threshold. Conserv. Biol. 16, 666–673 27 Lindborg, R. et al. (2012) Effect of habitat area and isolation on plant trait distribution in European forests and grasslands. Ecography 35, 356–363 28 Purschke, O. et al. (2012) Linking landscape history and dispersal traits in grassland plant communities. Oecologia 168, 773–783 29 Wearn, O.R. et al. (2012) Extinction debt and windows of conservation opportunity in the Brazilian Amazon. Science 337, 228–232 30 Alvarez-Yepiz, J.C. et al. (2011) Persistence of a rare ancient cycad: effects of environment and demography. Biol. Conserv. 144, 122–130 31 Halley, J.M. and Iwasa, Y. (2011) Neutral theory as a predictor of avifaunal extinctions after habitat loss. Proc. Natl. Acad. Sci. U.S.A. 108, 2316–2321 32 Martin, T.G. et al. (2011) Browsing down our natural heritage: deer impacts on vegetation structure and songbird populations across an island archipelago. Biol. Conserv. 144, 459–469 33 Saura, S. and Rubio, L. (2010) A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape. Ecography 33, 523–537 34 Vandermeer, J. and Perfecto, I. (2007) The agricultural matrix and a future paradigm for conservation. Conserv. Biol. 21, 274–277
The mechanisms causing extinction debts Kristoffer Hylander and Johan Ehrle´n Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-106 91 Stockholm, Sweden
Extinction debts can result from many types of habitat changes involving mechanisms other than metapopulation processes. This is a fact that most recent literature on extinction debts pays little attention to. We argue that extinction debts can arise because (i) individuals survive in resistant life-cycle stages long after habitat quality change, (ii) stochastic extinctions of populations that have become small are not immediate, and (iii) metapopulations survive long after that connectivity has decreased if colonization–extinction dynamics is slow. A failure to distinguish between these different mechanisms and to simultaneously consider both the size of the extinction debt and the relaxation time hampers our understanding of how extinction debts arise and our ability to prevent ultimate extinctions. Delays in local and global extinctions It is a common notion that we are in the midst of a massextinction event caused by human-driven habitat loss, habitat modification, and climate change [1,2]. Compared with the predicted levels of extinction, relatively few species have as yet gone globally extinct [3]. Moreover, at regional and local scales the number of extinctions is surprisingly low given large-scale habitat loss [4,5]. Part of this discrepancy might be explained by overestimation of extinction rates [6]. However, an important explanation for differences between predicted and observed extinction rates is that both local and global extinctions are delayed [3,7,8]. To provide policy-makers and practitioners with efficient tools to halt losses, research thus needs not only to assess the size and distribution (among regions, habitats, or taxonomic groups) of this extinction debt, but also to examine the mechanisms behind and consequences of time-lagged species extinctions. An area is said to have an extinction debt when the number of species is greater than the equilibrium level predicted from the actual habitat loss or degradation [9]. Accordingly, extinction debts are mostly examined at the level of species richness, as evident from two recent reviews on extinction debts [9,10] and many case studies [11–13]. However, extinction debts in terms of species richness are ultimately the result of delayed extinctions of many different species and each species will respond individualistically to a given change. To elucidate the mechanisms underlying extinction debts, it is thus Corresponding author: Hylander, K. ([email protected]). Keywords: colonization credit; extinction; extinction debt; metapopulation; population; remnant population; time lag.
important to shift the focus from species richness and to explore mechanisms at the level of individual species. Multiple mechanisms might cause extinction debts The extinction debt concept was originally formulated under the theoretical frameworks of island biogeography and metapopulation dynamics, emphasizing the role of disrupted connectivity leading to lower colonization after stochastic extinctions, and this is still the most common use of the concept ([9], but see [10,14]). We argue that mechanisms acting at the levels of individuals and populations can also result in extinction debts and that this fact has not been explicitly considered in the literature (but see [10]). Neglecting the actual mechanisms that cause extinction debts might be a reason why management recommendations intended to prevent ultimate extinctions are often vague and do not target specific aspects of habitat restoration (quality, quantity, or connectivity). In this paper we first discuss the relationship between the size and duration of the extinction debt and argue that both are of key importance. We then examine how extinction debts at the level of individual species can arise from mechanisms acting at different organizational levels. Finally, we discuss the implications of these points for traitbased differences among species and conservation management. The aim of the paper is to draw attention to some neglected aspects and provide a framework that enhances our understanding of extinction debts. Extinction debts and relaxation time An important aspect when examining extinction debts is to simultaneously consider both the size of the extinction debt and the relaxation time (the duration of the extinction debt). This is because it is the combination of these two that determines the likelihood of finding extinction debts at any given time (Figure 1) [9,15]. For a single species, the size of an extinction debt has been defined as the difference between the current occupancy of a species (e.g., measured as the number of populations in an area) and the level of the occupancy at a new equilibrium when the extinction debt is paid [9]. Such measures of extinction debts implicitly assume that there is a reference level, or equilibrium, to which the effects of the perturbation can be compared. Here, we use the word equilibrium to denote periods of higher stability relative to periods or point events of great change, for example, the situation in a rainforest previously unaffected by logging that become fragmented by forestry clearfelling.
0169-5347/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tree.2013.01.010 Trends in Ecology & Evolution, June 2013, Vol. 28, No. 6
341
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Trends in Ecology & Evolution June 2013, Vol. 28, No. 6
Occupancy
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Figure 1. Principal relationship between the size of an extinction debt and the relaxation time (the time over which the debt is paid and a new equilibrium level is reached). The linear expression shown in the figure is just one simple example of many possible monotonic relationships. t0 is the time at which the habitat has just changed and no extinctions have taken place yet and te is the time at which all extinctions have occurred and a new equilibrium has been reached. Ot0 and Ote represent the occupancy (e.g., number of populations) at t0 and te, respectively.
The extinction debt observed at any given time will depend on the relationship between the size of the extinction debt and time since habitat change (Figure 1). This relationship is, in turn, determined by the sensitivity of the species to habitat change, that is, the maximum (initial) size of the extinction debt, as well as by how fast the debt is paid. Many studies do not clearly distinguish between these two aspects of the extinction debt [12,16,17]. This is problematic because both aspects simultaneously influence the size of the extinction debt observed at a given point in time, and because different species attributes might influence the expected total number of extinctions and the time it will take for these extinctions to occur. Magnitude of habitat change and extinction debts The expected new equilibrium occupancy after a habitat change will be negatively related to the magnitude of the habitat change (Figure 2a,b). Accordingly, the maximum size of the extinction debt will increase monotonically with habitat change, directly mirroring the shape of the relationship between occupancy change and habitat change (Figure 2c). By contrast, the time to extinction is expected to decrease with increasing habitat deterioration (Figure 2d). Because the risk of extinction for a given population is likely to increase monotonically with habitat deterioration whereas the time to extinction decreases, we might expect the highest probability of finding extinction debts at some intermediate level of habitat change (Figure 2a). This constitutes another important reason why it is important to simultaneously consider both the extinction debt and the relaxation time. Mechanisms of delayed extinctions Species persistence in an area can be understood as the result of processes acting at different hierarchical levels and influencing the survival of individuals, populations, or metapopulations. At the level of an individual, long-term persistence depends on survival rates during different 342
phases of the life cycle, which in turn depend on habitat quality. It is important to bear in mind that habitat quality does not only refer to abiotic conditions; biotic interactions are also important, and co-extinctions and trophic cascades might be important sources of extinctions [18]. Populations will persist as long as individuals survive or are replaced by recruits. Population survival is thus a function of the vital rates in different individuals. However, population attributes such as size and structure are also important for population survival because they influence demographic and environmental stochasticity. At the metapopulation level, persistence is possible if local population extinctions are balanced by establishment of new populations. However, if the patches of suitable habitat become too isolated, colonizations will no longer balance extinctions, and this will eventually lead to extinction of the whole metapopulation. It is thus important to note that processes at several organizational levels influence whether species will persist or become extinct in an area (Figure 3). It is equally important to recognize that these different mechanisms not only influence the probability of a species ultimately becoming extinct, but also the time to extinction. Individual vital rates Alteration of habitat quality will often ultimately lead to extinctions. However, if one or several life history stages of individuals is resistant to deteriorated habitat quality, population extinction can be delayed. In plants, long life spans of physiological individuals occur in trees and in small herbs [19]. In many clonal organisms, genetic individuals can attain very long life spans through the survival and proliferation of physiologically more or less independent ramets, such as in a rhizome network of the bracken fern or a moss carpet. Dormant life stages, including seed and spore banks and zooplankton egg-capsules, can also delay extinctions in unfavorable environments [20]. Populations persisting through the survival of long-lived individuals or dormant life stages in spite of a deteriorated environment and ceased recruitment have been termed remnant populations [21]. However, the resistance of individuals to deteriorated habitat quality need not be associated with particular life history stages. If vital rates in general are resistant to changes, then the average performance of individuals after a habitat change might only fall slightly below the level needed for individuals to replace themselves. Although the population is doomed to eventual extinction, this extinction will occur only after a considerable time lag. Stochastic population processes As described above, populations might persist for a considerable time after the conditions allowing long-term survival have been altered because individuals are persistent or because vital rates correspond to only slightly negative population growth rates. However, even if mean vital rates correspond to a positive population growth rate, demographic and environmental stochasticity might eventually lead to local extinctions. This is particularly true for small populations and for populations with fluctuating vital rates [22]. Besides experiencing a greater risk for extinction from stochastic events, small populations might
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Figure 2. Size and duration of extinction debts as a function of habitat change. (a) Occupancy for a species in terms of the number of populations in the focal area at different times as a function of habitat change. t0 is the time at which the habitat has just changed before any extinctions has taken place; t1 and tx are different time intervals after habitat change; and te is the time at which a new equilibrium is reached, that is, when all extinctions have occurred. (b) Two examples of different occupancy versus habitat change relationships. The upper (red) curve illustrates a situation in which a small habitat change leads to only small changes in occupancy, whereas greater changes lead to a more rapid decrease in occupancy. The lower (blue) curve shows a species that is sensitive to small changes. (c) Size of the extinction debt (delta occupancy) as a function of habitat change. (d) Expected mean time to extinction as a function of habitat change. The thin lines in (c) and (d) illustrate that many monotonic relationships are possible.
also experience reduced mean vital rates due to Allee effects [23]. Small populations also face higher extinction risks due to genetic stochasticity in terms of inbreeding or loss of genetic variation [24]. The increased risk of stochastic extinction after habitat deterioration might, however, often be low and allow considerable persistence time [8]. As a consequence, populations that have recently experienced a decrease to a size below a critical level will experience an extinction debt. Processes at the metapopulation level Most studies of extinction debts are undertaken within an island biogeographic or metapopulation conceptual framework [9,17,25]. In a metapopulation at equilibrium, local extinctions are balanced by immigration and recolonization. The local populations within a metapopulation might also be rescued from extinction by immigrations from other subpopulations. A decrease in connectivity can lead to both lower recolonization rates after extinctions and higher extinction rates in patches that were previously rescued by immigrants [26]. This will result in a new lower equilibrium or extinction of the whole metapopulation. However, new equilibrium levels of patch occupancy in a metapopulation are often reached only after considerable delay if the extinction rate of local populations is low (see above) or if colonization rates are only slightly lower than the extinction rates (analogous to a slightly negative population growth rate). In a recently disturbed landscape, a species will therefore often be found in a higher proportion
of patches than the equilibrium level associated with the connectivity of the altered landscape; in other words, there is an extinction debt. The relative importance of processes at multiple levels The relative importance of mechanisms acting at different organizational levels in causing extinction debts is likely to depend on the type of habitat change, as well as on species traits. The example in Figure 3 of extinction debts in a stream network clearly illustrates how extinction debts can be the result of mechanisms at several levels. In our opinion, mechanisms at the level of individuals and populations have been given too little attention in the literature, whereas mechanisms at the metapopulation level have routinely been suggested as explanations for extinction debts. This is likely to be explained by a greater research focus on effects of fragmentation (in a broad sense) of natural environments, which inevitably involves changes in connectivity [9,12,27]. It is also true that processes at multiple levels often occur simultaneously. For example, connectivity changes are often closely associated with habitat loss and changes in habitat quality in real-world situations, such as forest fragmentation in the Amazon during the 20th century and the conversion of semi-natural grasslands to plowed fields or forests in late 19th century in northern Europe. Changes in habitat size and quality might also be the main cause of extinction debts (Figure 3). To prevent future extinctions, it is thus important to assess the relative contributions of changes in 343
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Figure 3. Mechanisms at different organization levels creating extinction debts, exemplified for an aquatic organism (e.g., freshwater pearl mussel) in a stream network. (a) Habitat quality changes (e.g., acid rain) affect the vital rates of individuals (e.g., cessation of reproduction). (b) Habitat quantity changes affect the size of local populations (e.g., many populations diminished because of canalization) making them prone to extinction due to environmental and genetic stochastisity. (c) Habitat connectivity change prevents dispersal (e.g., of trout, which disperse mussel larvae) and no rescue of populations or recolonization of extinct populations can occur. The maximum extinction debt is the difference in the number of populations at t0 and te, but the actual size of the extinction debt will decrease over time.
habitat quality, quantity, and connectivity to extinction debts. It is also important to recognize that the different mechanisms that can result in extinction debts are hierarchically nested. Metapopulation dynamics depends on population dynamics and a population will not become extinct until the last individual dies. We should therefore expect that it takes longer time to reach equilibrium at the metapopulation level than it takes for effects to be fully expressed at the level of individuals. This is easiest seen when comparing worst-case scenarios for changes in habitat quality versus changes in habitat connectivity. In the case of a devastating change in habitat quality, all individuals will die shortly after the alteration (e.g., wetland plants on a marsh after drainage of the water), meaning that the relaxation time is short and the extinction debt will be quickly paid. By contrast, if connectivity is reduced to the point at which colonization ceases entirely, then the size of the extinction debt will diminish only as local populations become extinct. As a result, the size of the extinction debt will often be greater for greater changes in connectivity over a considerable period of time, whereas for changes in habitat quality the extinction debt will often be greatest for intermediate levels of change (compare t1 and tx in Figure 2a). Trait-based differences and extinction debts It has been suggested that several species traits, including longevity, turnover rate, and dispersal capacity, correlate with the presence of an extinction debt [9,13,16,27,28]. 344
Although traits are characteristics of individuals, they can have effects on the size and relaxation times of extinction debts via different organizational levels. For example, life histories including dormant life stages can increase the relaxation time at the level of individuals, and species with good dispersal and recolonization capacities might have a longer relaxation time at the metapopulation level. A detailed examination of all proposed relationships between traits and extinction debts is beyond the scope of this paper. However, we argue that relationships between traits and extinction debts (and/or relaxation times) are more easily identified if linked to a specific mechanism. For example, dispersal capacity will influence neither the size of the extinction debt nor the relaxation time in the case of a habitat quality change, but it will be important if connectivity is altered (compare the first and third columns in Figure 3). For the research field to develop it is important that hypotheses about relationships between traits and extinction debts not only explicitly consider multiple mechanisms, but also make a clear distinction between extinction debt size and the relaxation time. Species traits can influence responses to a habitat change, in terms of both the change in occupancy (Figure 2c) and the time it takes to reach a new equilibrium (Figure 2d). Hence, the probability of finding extinction debts should be greatest for species with a combination of traits that simultaneously increase time to extinction (shallower slope in Figure 2d) and sensitivity to habitat changes, in terms of the probability of eventual extinction (steep slope in
Opinion Figure 2c). In cases in which traits influence the extinction debt size and the relaxation time in different directions, it might be difficult to predict their net effect. For example, it can be predicted that a species at a higher trophic level will be more affected by a given habitat loss than a species at a lower trophic level, and will thus show a greater potential extinction debt directly after such a change compared to a low-trophic species (a steeper slope in Figure 2c). However, it is also likely that the species at the higher trophic level will reach a new equilibrium faster because of a smaller population size, leading to a decrease in the duration of the extinction debt (a steep slope in Figure 2d). A failure to simultaneously consider both extinction debt and relaxation time is thus likely to lead erroneous predictions about relationships between traits and extinction debts. Management The existence of an extinction debt will sometimes also provide a possibility for restoration before the debt is paid [9,29]. We argue that for restoration to be successful, it is important to know to what extent the extinction debt is related to: (i) a deterioration in habitat quality leading to negative population growth rates and remnant populations; (ii) smaller populations susceptible to extinctions due to genetic deterioration or environmental or demographic stochasticity; or (iii) fragmentation and loss of connectivity leading to lower recolonization rates (Figure 3). It is evident from Figure 3 that fundamentally different processes can give rise to extinction debts, and management interventions should consider this. Processes at the individual level are predicted to be important after deteriorations in habitat quality due to climate change, pollution, or ceased or changed management. Studies of vital rates of individuals and growth rates of populations can provide some guidance in such situations. For many organisms with resilient life stages, it might be more crucial to focus conservation efforts on restoring and maintaining habitat quality than to increase landscape connectivity within the near future [30]. At the population level there will often be a time lag between reductions in population size following habitat loss and local extinctions. For such populations, increasing the amount of suitable habitat is likely to constitute the most efficient way to reduce the extinction risk [31,32]. Finally, for sites that have an extinction debt at the metapopulation level, measures to increase connectivity in the landscape are necessary [33]. Ultimately, in the very long run, sources for recolonization will be important for all species because ecosystems are dynamic and local extinctions are inevitable [34]. However, for practical conservation over shorter time frames, the relative returns on investments to increase habitat and quantity and connectivity will be closely linked to the assumed path to extinction (Figure 3). Concluding remarks In this paper we argue that studies of extinction debts have so far paid little attention to the fact that the likelihood of finding extinction debts after habitat changes is determined by both extinction debt size and relaxation time. In addition, studies have rarely considered that extinction
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Box 1. Directions for future research on extinction debts We propose that three important aspects should be considered to improve our ability to assess the size and relaxation time of extinction debts, to identify means to prevent extinctions, and to identify species with trait combinations that make them particularly likely to have extinction debts. Extinctions occur at the species level and species respond individualistically to habitat changes. To understand the mechanisms behind relationships between different types of habitat change and the size of extinction debts, we therefore need to complement studies at the community level focusing on species richness with studies focusing on processes in individual species. Both the initial size of extinction debts and their relaxation time influence the debts that we can actually observe at a given point in time. Some combinations of habitat changes and species traits may result in large but rapidly disappearing debts, whereas other combinations may result in smaller but more persistent debts. Moreover, a given trait may influence the size and relaxation time of extinction debts in opposite directions. Studies trying to link the size of extinction debts to habitats, disturbance types, or species traits will therefore benefit from considering effects on the size of the extinction debt and effects on its relaxation time separately. We thus need studies that monitor species over many years or data collected at different time intervals after habitat changes to assess how the size of an extinction debt develops over time (Figure 1). Extinction debts may be caused by mechanisms acting at the individual, population, and metapopulation levels. Distinguishing between mechanisms acting at different organizational levels will help us to understand how different types of habitat change are linked to extinction debts, and how differences among species in these relationships are linked to functional traits. Moreover, conservation efforts to prevent ultimate extinctions should critically depend on identifying the mechanisms that are mainly responsible for the extinction debt. To better understand the relative importance of mechanisms, studies focusing on metapopulation processes and connectivity of populations need to be complemented by studies of how processes at the levels of individuals and populations contribute to extinction debts. We suggest that demographic studies after habitat changes will be useful in investigating the role of individual- and population-level processes for extinction debts. We also propose that there is a need for more studies on extinction debts after many different types and intensities of habitat change.
debts can arise due to fundamentally different mechanisms, associated with the vital rates of individuals, the size of populations, and their susceptibility to stochastic extinctions, or the colonization processes maintaining metapopulations. We have also argued that as a consequence, attempts to link species life cycles and traits to the prevalence of extinction debts need to consider that effects can occur both via debt size and relaxation time, as well as through mechanisms acting at different organizational levels. Although the different mechanisms rarely act in isolation and environmental changes often simultaneously affect habitat quality, quantity, and connectivity, awareness of the complexity and the specifics of each case is likely to promote our understanding and aid in optimizing management to prevent ultimate extinctions. We suggest that future research on extinction debts should focus more on the species level, on how debts develop over time since habitat change, and on the mechanisms causing debts (Box 1). We hope that the ideas presented here will inspire researchers to take a more mechanistic approach to studies of extinction debts and encourage conservationists to 345
Opinion elaborate mitigation actions that correspond to the prime cause of such debts. Acknowledgments We thank Johan Dahlgren, Mats Dynesius, Ove Eriksson, and two anonymous reviewers for valuable comments on previous drafts of the manuscript.
References 1 Pimm, S.L. et al. (1995) The future of biodiversity. Science 269, 347–350 2 Barnosky, A.D. et al. (2011) Has the Earth’s sixth mass extinction already arrived? Nature 471, 51–57 3 Stork, N.E. (2010) Re-assessing current extinction rates. Biodivers. Conserv. 19, 357–371 4 Larsen, T.B. (2008) Forest butterflies in West Africa have resisted extinction . . . so far (Lepidoptera: Papilionoidea and Hesperioidea). Biodivers. Conserv. 17, 2833–2847 5 Sang, A. et al. (2010) Indirect evidence for an extinction debt of grassland butterflies half century after habitat loss. Biol. Conserv. 143, 1405–1413 6 He, F.L. and Hubbell, S.P. (2011) Species–area relationships always overestimate extinction rates from habitat loss. Nature 473, 368–371 7 Hanski, I. and Ovaskainen, O. (2000) The metapopulation capacity of a fragmented landscape. Nature 404, 755–758 8 Dullinger, S. et al. (2012) Extinction debt of high-mountain plants under twenty-first-century climate change. Nat. Clim. Change 2, 619– 622 9 Kuussaari, M. et al. (2009) Extinction debt: a challenge for biodiversity conservation. Trends Ecol. Evol. 24, 564–571 10 Jackson, S.T. and Sax, D.F. (2010) Balancing biodiversity in a changing environment: extinction debt, immigration credit and species turnover. Trends Ecol. Evol. 25, 153–160 11 Krauss, J. et al. (2010) Habitat fragmentation causes immediate and time-delayed biodiversity loss at different trophic levels. Ecol. Lett. 13, 597–605 12 Cousins, S.A.O. and Vanhoenacker, D. (2011) Detection of extinction debt depends on scale and specialisation. Biol. Conserv. 144, 782–787 13 Vellend, M. et al. (2006) Extinction debt of forest plants persists for more than a century following habitat fragmentation. Ecology 87, 542– 548 14 Tilman, D. et al. (1994) Habitat destruction and the extinction debt. Nature 371, 65–66 15 Diamond, J.M. (1972) Biogeographic kinetics – estimation of relaxation-times for avifaunas of Southwest Pacific Islands. Proc. Natl. Acad. Sci. U.S.A. 69, 3199–3203
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16 Saar, L. et al. (2012) Which plant traits predict species loss in calcareous grasslands with extinction debt? Divers. Distrib. 18, 808– 817 17 Marini, L. et al. (2012) Traits related to species persistence and dispersal explain changes in plant communities subjected to habitat loss. Divers. Distrib. 18, 898–908 18 Colwell, R.K. et al. (2012) Coextinction and persistence of dependent species in a changing world. Annu. Rev. Ecol. Evol. Syst. 43, 183–203 19 Garcia, M.B. et al. (2011) No evidence of senescence in a 300-year-old mountain herb. J. Ecol. 99, 1424–1430 20 Mergeay, J. et al. (2007) Extinction, recolonization, and dispersal through time in a planktonic crustacean. Ecology 88, 3032–3043 21 Eriksson, O. (1996) Regional dynamics of plants: a review of evidence for remnant, source-sink and metapopulations. Oikos 77, 248–258 22 Lee, A.M. et al. (2011) Demographic stochasticity, Allee effects, and extinction: the influence of mating system and sex ratio. Am. Nat. 177, 301–313 23 Dennis, B. (2002) Allee effects in stochastic populations. Oikos 96, 389– 401 24 Nieminen, M. et al. (2001) Experimental confirmation that inbreeding depression increases extinction risk in butterfly populations. Am. Nat. 157, 237–244 25 Mouquet, N. et al. (2011) Extinction debt in source–sink metacommunities. PLoS ONE 6, e17567 26 Hanski, I. and Ovaskainen, O. (2002) Extinction debt at extinction threshold. Conserv. Biol. 16, 666–673 27 Lindborg, R. et al. (2012) Effect of habitat area and isolation on plant trait distribution in European forests and grasslands. Ecography 35, 356–363 28 Purschke, O. et al. (2012) Linking landscape history and dispersal traits in grassland plant communities. Oecologia 168, 773–783 29 Wearn, O.R. et al. (2012) Extinction debt and windows of conservation opportunity in the Brazilian Amazon. Science 337, 228–232 30 Alvarez-Yepiz, J.C. et al. (2011) Persistence of a rare ancient cycad: effects of environment and demography. Biol. Conserv. 144, 122–130 31 Halley, J.M. and Iwasa, Y. (2011) Neutral theory as a predictor of avifaunal extinctions after habitat loss. Proc. Natl. Acad. Sci. U.S.A. 108, 2316–2321 32 Martin, T.G. et al. (2011) Browsing down our natural heritage: deer impacts on vegetation structure and songbird populations across an island archipelago. Biol. Conserv. 144, 459–469 33 Saura, S. and Rubio, L. (2010) A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape. Ecography 33, 523–537 34 Vandermeer, J. and Perfecto, I. (2007) The agricultural matrix and a future paradigm for conservation. Conserv. Biol. 21, 274–277