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There is considerable interest in understanding how management may help species and populations cope with climate change (climate change adaptation). I used a population model describing the demography of a southern range-margin European Golden Plover Pluvialis apricaria population vulnerable to climate change to assess the potential benefits associated with site-based adaptation management. Two forms of management were simulated: (1) counteracting management to reduce the severity of the negative climate change impacts, simulated by increasing tipulid (cranefly) abundance, and (2) compensatory management to increase populations through an alternative mechanism, simulated by manipulating nest and chick predation rates. A 1 °C rise was estimated to require a doubling of cranefly abundance, or a 35% increase in nest and chick survival rates, to maintain a stable population. For a 2 °C rise, a four-fold increase in craneflies or an 80% increase in survival rates would be required for population stability. A model based on likely realistic estimates of the magnitude of benefit associated with both adaptation management options showed that combined, they may significantly reduce the severity of population decline and risk of extinction associated with a relatively large increase in temperature of 5.8 °C above 1960–90 levels. Site-based adaptation management may therefore increase the resistance of Golden Plovers to some degree of future climate change. This model framework for informing climate change adaptation decisions should be developed for other species and habitats.
There is increasing evidence that bird populations are already being affected by climate change (Jiguet et al. 2007, Green et al. 2008, Gregory et al. 2009), which increases confidence in projections of future population and range changes (Thomas et al. 2004, Jetz et al. 2007, Huntley et al. 2008). Given the magnitude of change anticipated by these projections, there is increasing interest in the potential for management to help species and populations cope with climate change (climate change adaptation). Much of this interest has focused on the potential for increasing connectivity to facilitate the movement of species to track their changing climate (Opdam & Wascher 2004, Vos et al. 2008, Heller & Zavaleta 2009). However, there is considerable uncertainty in the likely efficacy of this approach (e.g. Bailey 2007), which has led to a re-thinking of conservation priorities in the face of climate change (Hodgson et al. 2009, Green & Pearce-Higgins 2010).
One area of adaptation management that has been largely neglected in the literature is that of the potential for management to increase the resistance to climate change of populations at individual sites (Pearce-Higgins et al. 2011). Whilst adaptation to increase the connectivity of populations should facilitate the expansion of a species’ range along the advancing range margin in response to climate change (Opdam & Wascher 2004, Huntley et al. 2007), site management (also termed intensive management or building resistance in the literature; Heller & Zavaleta 2009) is aimed at preventing or delaying the loss of species at the retreating range margin. If such adaptation can increase the persistence of species in an increasingly unfavourable climate, then the loss of species distributions will be less severe than predicted (Pearce-Higgins et al. 2011). To be successful, site-based adaptation management requires both an understanding of the mechanisms by which climate change impacts upon a species, or at least an understanding of the main demographic drivers of population change, and research into the potential for management to reduce the severity of any such negative effects. Thus, there are strong parallels between this proposed framework for site-based adaptation management and the framework for effective conservation of threatened species (Norris 2004). Adaptation management can be separated into two forms: counteracting and compensatory (Green & Pearce-Higgins 2010). Counteracting management reduces the severity of the negative climate change impact, whilst compensatory management does not address the mechanism by which climate change impacts upon a species but attempts to increase productivity or survival rates by an alternative mechanism. This latter approach is increasingly being applied to other conservation issues (e.g. Wilcox & Donlan 2007) and may therefore have merit for climate change adaptation. Both options may be useful in different circumstances, and may potentially give rise to different population responses to climate change, as tested in this paper.
I use the example of the European Golden Plover Pluvialis apricaria (hereafter Golden Plover) to illustrate how such site-based adaptation management may operate in practice. This species has a wide distribution across the tundras, heaths and peatlands of the northern Palaearctic from the UK and Ireland to central Siberia. Recent research on a population in the South Pennines, UK, located close to the southern range margin of the global distribution, has highlighted the potential for increasing summer temperatures to impact detrimentally upon Golden Plover populations through effects on their tipulid (cranefly) prey. During the breeding season, the growth and survival of young chicks is positively correlated with the abundance of emerged craneflies (Pearce-Higgins & Yalden 2004). The number of craneflies that emerge in any year is strongly negatively correlated with the previous summer temperature (Pearce-Higgins et al. 2010), as during a hot summer, the desiccation of the peat surface results in a high mortality of early cranefly larval instars (Coulson 1962). Accordingly, the abundance of the Golden Plovers is negatively correlated with August temperature with a 2-year lag. Thus, a hot summer will result in reduced cranefly emergence in the following year, and hence low Golden Plover productivity, resulting in few recruits and a population decline in the year after (Pearce-Higgins et al. 2010). Whilst climate change is likely to have a wide range of impacts upon particular populations (Mustin et al. 2007), impacts mediated through changing prey populations are likely to be among the most important and widespread (e.g. Sillett et al. 2000, Croxall et al. 2002, Frederiksen et al. 2006). Due to the projected detrimental impacts of climate change and understanding of the likely mechanism underpinning any such effects (Huntley et al. 2007, Pearce-Higgins et al. 2010), Golden Plovers in the UK form a good model system in which to explore the potential for climate change adaptation.
In this paper, I use an existing productivity model to assess how increasing adaptation management intensity may increase the resistance of the population to future climate warming, and what the potential limits to such management may be. Specifically, first, I modelled the potential for different levels of counteracting and compensatory management to alter the relationship between temperature and Golden Plover population growth, comparing the likely population responses to the two managements for a given temperature. This indicates the likely temperature limits to the effectiveness of different levels of both management options. Secondly, I reviewed the existing literature to assess the likely magnitude of counteracting and compensatory management that realistically may be achieved for Golden Plover, based on current knowledge. Thirdly, I modelled the likely population-level consequences of implementing such an adaptation management strategy under a high climate change scenario to assess whether adaptation management may indeed potentially increase the resilience of vulnerable populations to climate change.
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Research to assess the potential for management to increase the resistance of vulnerable populations to climate change is urgently required to inform current conservation practice (Pearce-Higgins et al. 2011). This paper makes one of the first attempts to do this. By simulating relatively simple consequences of the manipulation of habitat condition upon insect abundance, the theoretical principle of such management being able to increase the resistance of an insectivorous population of birds to increasing temperature has been supported. This suggests that counteracting management directly to address the mechanism by which climate change is likely to have a detrimental effect on a particular population may successfully reduce the severity of change. Thus, management to increase cranefly abundance is likely to benefit Golden Plover populations experiencing increases in August temperature. Similarly, the contention that varying levels of predator abundance and predator control management may increase the resistance of a population to climate change through compensatory management is also supported. In particular, such management was predicted to have a very large impact upon projected population trajectories at low temperatures because in such circumstances predation is a much more important limiter on Golden Plover productivity than cranefly abundance.
Combined, these two results suggest that in the short term, undertaking compensatory management through predator control is likely to result in the greatest immediate increase in Golden Plover abundance (Fletcher et al. 2010). However, as food availability becomes increasingly limiting as a result of temperature increases, habitat management to maximize food availability is likely to become more important. The validity of these predictions depends, however, upon a number of uncertainties: (1) the robustness of the model; (2) the effectiveness of management; and (3) the severity of future climate change.
First, the model is essentially a correlative one (Pearce-Higgins et al. 2010), which potentially imposes limits on its applicability into the future, although the model is underpinned by detailed ecological understanding (Pearce-Higgins & Yalden 2004). Importantly, it incorporates process error (based on fluctuations in August temperature), which reflects the previous variability in the time-series, as well as measurement error (Pearce-Higgins et al. 2010). Incorporating these errors usefully quantifies some of the uncertainty associated with projecting the future, although not all; the evolutionary adaptability of the species (Visser 2008) and the potential for climate change to impact upon populations in multiple ways (Mustin et al. 2007) remain unknown. These issues are discussed in detail in Pearce-Higgins et al. (2010) and the fact that the model has good predictive ability over a 34-year period does add confidence in relation to its usefulness for projecting into the future, with appropriately wide margins of uncertainty (Fig. 5).
Secondly, the accuracy of the projections about the success of counteracting adaptation management depends upon the assumptions about the effects of management upon cranefly abundance. This is the least certain component of the model, as little information about the effects of land management upon craneflies has been published, and nothing that examines how management may affect the sensitivity of cranefly populations to temperature. To produce plausible estimates of the potential magnitude of management to increase cranefly populations, I have simply modelled cranefly abundance as a function of habitat, as this acts as a crude surrogate for the long-term effects of management upon soil moisture. Craneflies are therefore most abundant on wet sites but are at low densities on the wettest Sphagnum-dominated peatlands (Coulson 1962).
Extensive areas of the UK peatlands have been historically drained or suffered significant erosion as a result of inappropriate management (Bragg & Tallis 2001, Holden et al. 2004), leading to a shift from Sphagnum- and sedge-dominated bog to dwarf shrub- and grass-dominated vegetation (Coulson et al. 1990, Stewart & Lance 1991, Bragg & Tallis 2001), which our model suggests could have reduced cranefly abundance, potentially mimicking or exacerbating the likely effects of summer warming and drought as a result of climate change. Management to restore peatland hydrology and habitat condition (Holden et al. 2004) may therefore reverse these effects. However, there is considerable uncertainty regarding the length of time required for such management to be effective, ranging from 12 years (Wilcock 1979) to in excess of 25 years (Van Seters & Price 2001), which may be most achievable on sites with shallow slopes and low hydraulic conductivity (Holden et al. 2004). Because of these uncertainties, I have not attempted to incorporate a likely time-lag over which peatland restoration will increase cranefly abundance, but instead have simply compared simulated Golden Plover population trends from Snake Summit based upon cranefly densities estimated from its current vegetation with simulated trends from an equivalent site with 100% bog vegetation where cranefly abundance is predicted to be 39% greater. Whilst such a change may be argued as being different from increasing the quality of all habitats, it is currently the only plausible way of deriving an estimate of the potential magnitude of benefit associated with such adaptation management, which is projected to make the population resistant to an increase in August temperature of about 0.4 °C (Fig. 2). Pearce-Higgins et al. (2010) suggested that some aspects of peatland restoration, such as the blocking of drainage ditches, might further increase the resilience of cranefly populations to increasing temperature and alter the slope of the relationship between temperature and cranefly abundance. This has yet to be parameterized but, once done, could be easily incorporated into this model and would be likely to result in a greater apparent benefit of counteracting adaptation management than that suggested here.
The second potential component of management examined was that of compensatory adaptation, mediated through simulated predator control to increase Golden Plover nest survival rates. There is considerable evidence from observations of nest and chick survival (Parr 1992, Pearce-Higgins & Yalden 2003), the spatial association between Golden Plover abundance and grouse moor management (Tharme et al. 2001, Pearce-Higgins et al. 2009), and the results of experimental manipulation (Fletcher et al. 2010) that Golden Plover populations benefit from predator control. Although none of these studies directly relates management intensity to productivity as output by the model (daily nest or chick survival rates, or the number of fledglings per pair), I also produce an estimate of the proportion of pairs successfully raising a fledgling, equivalent to the breeding success measure of Fletcher et al. (2010), who estimated that 18 ± 8% of Golden Plover pairs successfully fledged young on non-predator control sites, but that 75 ± 8% were successful under predator control management. These estimates are reassuringly similar to the 23 and 71% of pairs modelled to successfully fledge young when August temperature is fixed to the 1971–2005 mean of 17.1 °C from the scenarios of the highest and lowest rates of nest and chick predation, respectively. The overall estimate of 69% of pairs fledging chicks under the adaptation management scenario, again with August temperature fixed at 17.1 °C, therefore realistically estimates likely productivity on an intensively managed grouse moor. This means that the implementation of this high level of predator control could result in population stability being achieved at 19.9 °C. This is a 1.9 °C increase on the estimate based on current management (Fig. 3), although as the site is already a grouse moor (Pearce-Higgins & Yalden 2003), to achieve such a rate of increase would require a particularly high intensity of nest predator control.
The third uncertainty about these projections, as with any attempt to look at the future effects of climate change on biodiversity, is over the likely magnitude of future climate change. For the purposes of illustration, I have simply extrapolated the current linear trend for increasing August temperature from 1971 to 2005 into the future, resulting in a projected 5.2 °C rise about the 1971–2005 mean by 2100, or 5.8 °C above 1960–90 levels. This means that the magnitude of climate change examined in this paper is towards the high end of the projections produced by UKCP09, with a 7% probability of being reached under a low emissions scenario, an 18% probability under a medium emissions scenario and a 33% probability under a high emissions scenario (UKCP09 2010). When modelling the potential effectiveness of adaptation management it is appropriate to use a pessimistic scenario to appraise whether management is capable of achieving real long-term benefit and, accordingly, there was a significant benefit simulated to be associated with adaptation management. It is, however, possible to examine the outputs another way, as the Golden Plover population is projected to remain largely stable until about 2035 under the maximal adaptation scenario (Fig. 5; projected population at 2035 = 80% of 2006 level, 95% CI 19–223%). This is equivalent to a 2.0 °C rise in August temperature from 1960 to 1990 levels, emphasizing the need for effective mitigation to reduce the likely severity of future climate change and increase the likely success of adaptation management.
Much modelling of future climate change impacts upon biodiversity has concerned species distributions in relation to spatial variation in climate (e.g. Thomas et al. 2004, Huntley et al. 2007), which provide only a projection of potential large-scale patterns of range change. Correspondingly, the focus of adaptation management from such an approach therefore becomes managing potential shifts in a species’ range (Opdam & Wascher 2004, Vos et al. 2008). This could be seen as management to enable the predictions from bioclimatic models to be realized, by facilitating the colonization of potential new areas of habitat as they become climatically suitable. However, as demonstrated in this paper, adaptation management may also significantly increase the persistence of a species in an increasingly unfavourable climate. Such management therefore in effect prevents the realization of predictions from bioclimatic models, by enabling species ranges to continue to exist in areas from which the models predict they should be lost. Although such an approach is regarded by some as risky and likely to be increasingly costly and challenging to maintain (Heller & Zavaleta 2009, Scott et al. 2010), the results of this modelling exercise for Golden Plover suggest that site-based adaptation management may increase the persistence of species within an increasingly unfavourable climate. Indeed, for some species with small and isolated ranges, this may be the only adaptation option facing conservationists. However, as also indicated by our results, depending upon the future severity of climate change, such management may only be effective for a limited period. Whilst it could be argued that such limited effectiveness renders the management unsuccessful in the long term, it may still provide benefit by increasing the number of potential colonizers for sites further north (Green & Pearce-Higgins 2010). Furthermore, it is difficult at present to judge with certainty which adaptation management strategies are likely to be successful and which are not.
The development of a modelling framework, such as that presented here, may be used as a quantitative basis on which to make such decisions. Given the likely limited conservation resources relative to the magnitude of the conservation problem (Scott et al. 2010), developing robust decision-making processes is likely to become increasingly important. Furthermore, in combination with future monitoring, predictive models may be used to assess when the magnitude of climate change exceeds the ability of adaptation management to infer resistance, indicating when such management is no longer sustainable (Pearce-Higgins in press). On this basis, further research should be conducted to better understand the likely limits of such adaptation, and to extend this approach to a wider range of species. Additional field studies are required to understand more fully the potential consequences of management on bird populations, and particularly whether such management can alter the relationship between climate and species demography.