The potential impacts of global climate change on marine protected areas

The potential effects of global climate changeon marine protected areas do not appear to havebeen addressed in the literature. This paperexamines the literature on protected areas,conservation biology, marine ecology,oceanography, and climate change, and reviewssome of the relevant differences between marineand terrestrial environments. Frameworks andclassifications systems used in protected areadesign are discussed. Finally, a frameworkthat summarizes some of the importantoceanographic processes and their links to thefood chain are reviewed. Species abundance anddistribution are expected to change as a resultof global climate change, potentiallycompromising the efficacy of marine protectedareas as biodiversity conservation tools. Thisreview suggests the need for: furtherinterdisciplinary research and the use oflinked models; an increase in marine protectedareas for biodiversity conservation and asresearch sites for teasing apart fishingeffects from climate effects; a temporallyresponsive approach to siting new marineprotected areas, shifting their locations ifnecessary; and large-scale ecosystem/integratedmanagement approaches to address the competinguses of the oceans and boundary-less threatssuch as global climate change and pollution.     

The impact of climate change on the future distribution of priority crop wild relatives in Indonesia and implications for conservation planning

The analysis of climate change impact is essential to include in conservation planning of crop wild relatives (CWR) to provide the guideline for adequate long-term protection under unpredictable future environmental conditions. These resources play an important role in sustaining the future of food security, but the evidence shows that they are threatened by climate change. The current analyses show that five taxa were predicted to have contraction of more than 30 % of their current ranges: Artocarpus sepicanus (based on RCP 4.5 in both no dispersal and unlimited dispersal scenario and RCP 8.5 in no dispersal scenario by 2050), Ficus oleifolia (RCP 4.5 5 in both no dispersal and unlimited dispersal scenario by 2080), Cocos nucifera and Dioscorea alata (RCP 8.5 in both no dispersal and unlimited dispersal scenario by 2050), and Ficus chartacea (RCP 8.5 in both no dispersal and unlimited dispersal scenario by 2050 and 2080). It shows that the climate change impact is species-specific. Representative Concentration Pathways (RCP) of greenhouse gas (GHG) emission and dispersal scenarios influence the prediction models, and the actual future distribution range of species falls in between those scenarios. Climate refugia, holdout populations, and non-analogue community assemblages were identified based on the Protected Areas (PAs) network. PAs capacity is considered an important element in implementing a conservation strategy for the priority CWR. In areas where PAs are isolated and have less possibility to build corridors to connect each other, such as in Java, unlimited dispersal scenarios are unlikely to be achieved and assisted dispersal is suggested. The holdout populations should be the priority target for the ex situ collection. Therefore, by considering the climate refugia, PAs capacity and holdout populations, the goal of keeping high genetic variations for the long-term conservation of CWR in Indonesia can be achieved.     

Assessing New Zealand fern diversity from spatial predictions of species assemblages

The utility of explicit spatial predictions for biodiversity assessment is investigated with New Zealand fern flora. Distributions of 43 species were modelled from climatic and landform variables and predicted across New Zealand using generalised additive models (GAM). An original package of functions called generalised regression analysis and spatial prediction (GRASP) was developed to perform the analyses. On average, for the 43 models, the contributions of environmental variables indicate that mean annual temperature is the most important factor at this broad regional scale. Both annual solar radiation and its seasonality had higher correlations than temperature seasonality. Measures of water availability such as ratio of rainfall to potential evapotranspiration, air saturation deficit and soil water deficit presented significant contributions. Lithology was a better predictor than slope and drainage. These results are similar to those obtained from analyses of the distributions of New Zealand tree species and are consistent with the hypothesis that both tree and fern diversity are highest on sites conducive to high productivity. In order to identify hotspots of fern diversity, spatial predictions of individual species were summed up. The resulting map gave a very similar result to the direct prediction of their corresponding richness (number of species by plot out of 43 spp.). As a consequence, and where individual species models were not all available, the number of species within different species assemblages was directly modelled. Predicted richness hotspots of total species (out of 122 spp.), selected species (out of 43 and 21 spp.) and common species (out of 23 spp.) present very similar spatial patterns and are highly correlated. Richness of uncommon species (out of 39 spp.) was also accurately predicted, but presented a different spatial pattern. The number of rare species (out of 60 spp.) was not correctly modelled. Even though the lack of data for rare species clearly limits the application of this approach, fern community composition of more common species can be partially reconstructed from individual species predictions. This case study offers therefore a consistent approach not only for biodiversity hotspots identification, but also for setting targets to biodiversity assessment and restoration programs.     

Potential impacts of climate change on the distributions and diversity patterns of European mammals

The Intergovernmental Panel on Climate Change (IPCC) predicts an increase in global temperatures of between 1.4°C and 5.8°C during the 21st century, as a result of elevated CO₂ levels. Using bioclimatic envelope models, we evaluate the potential impact of climate change on the distributions and species richness of 120 native terrestrial non-volant European mammals under two of IPCC’s future climatic scenarios. Assuming unlimited and no migration, respectively, our model predicts that 1% or 5–9% of European mammals risk extinction, while 32–46% or 70–78% may be severely threatened (lose > 30% of their current distribution) under the two scenarios. Under the no migration assumption endemic species were predicted to be strongly negatively affected by future climatic changes, while widely distributed species would be more mildly affected. Finally, potential mammalian species richness is predicted to become dramatically reduced in the Mediterranean region but increase towards the northeast and for higher elevations. Bioclimatic envelope models do not account for non-climatic factors such as land-use, biotic interactions, human interference, dispersal or history, and our results should therefore be seen as first approximations of the potential magnitude of future climatic changes.     

Predicting potential distribution and identifying priority areas for conservation of the Yellow-tailed Woolly Monkey (Lagothrix flavicauda) in Peru

Species distribution models (SDMs) provide conservationist with spatial distributions estimations of priority species. Lagothrix flavicauda (Humboldt, 1812), commonly known as the Yellow-tailed Woolly Monkey, is one of the largest primates in the New World. This species is endemic to the montane forests of northern Peru, in the departments of Amazonas, San Martín, Huánuco, Junín, La Libertad, and Loreto at elevation from1,000 to 2,800 m. It is classified as “Critically Endangered” (CR) by the International Union for Conservation of Nature (IUCN) as well as by Peruvian legislation. Furthermore, it is listed in Appendix I of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Research on precise estimates of its potential distribution are scare. Therefore, in this study we modeled the potential distribution area of this species in Peru, the model was generated using the MaxEnt algorithm, along with 80 georeferenced occurrence records and 28 environmental variables. The total distribution (high, moderate, and low) for L. flavicauda is 29,383.3 km², having 3,480.7 km² as high potential distribution. In effect, 22.64 % (6,648.49 km²) of the total distribution area of L. flavicauda is found within Natural Protected Areas (NPAs), with the following categories representing the largest areas of distribution: Protected Forests (1,620.41 km²), Regional Conservation Areas (1,976.79 km²), and Private Conservation Areas (1,166.55 km²). After comparing the predicted distribution with the current NPAs system, we identified new priority areas for the conservation of the species. We, therefore, believe that this study will contribute significantly to the conservation of L. flavicauda in Peru.     

Protected area networks and savannah bird biodiversity in the face of climate change and land degradation

The extent to which climate change might diminish the efficacy of protected areas is one of the most pressing conservation questions. Many projections suggest that climate‐driven species distribution shifts will leave protected areas impoverished and species inadequately protected while other evidence suggests that intact ecosystems within protected areas will be resilient to change. Here, we tackle this problem empirically. We show how recent changes in distribution of 139 Tanzanian savannah bird species are linked to climate change, protected area status and land degradation. We provide the first evidence of climate‐driven range shifts for an African bird community. Our results suggest that the continued maintenance of existing protected areas is an appropriate conservation response to the challenge of climate and environmental change.     

A multi-trait approach for the identification and protection of European freshwater species that are potentially vulnerable to the impacts of climate change

We present a multi-trait approach to identify potentially vulnerable species of Ephemeroptera (mayflies), Plecoptera (stoneflies) and Trichoptera (caddisflies), collectively referred to as EPT, to the impacts of climate change (CC). The “climate change vulnerability score” (CCVS) is an aggregation of six autecological traits that are known to be associated with vulnerability to CC: endemism, micro-endemism, temperature preference, altitudinal preference, stream zonation preference, and life history. We assigned a vulnerability score (0 – invulnerable to 6 – highly vulnerable to climate change) to 1940 EPT species and discussed the applicability of the index at three spatial scales: (1) continental (Europe), (2) state (the German Federal State of North Rhine-Westphalia) and (3) a river basin (the Ruhr River). We identified 157 EPT species (ca. 8%) as highly vulnerable to climate change (CCVS ≥ 4), including 95 species of caddisflies, 60 species of stoneflies and two species of mayflies. These are mostly found in France and Italy (52 species each), Spain and Slovenia (36 and 34, respectively), and Austria and Switzerland (30 species each), of which 95 are caddisflies, 60 stoneflies, and 2 mayflies. Using data collected in routine regional sampling we show that although no endemic EPTs were found in the German Federal State of North Rhine-Westphalia, eight species can still be identified as relatively vulnerable to CC (CCVS of 3). Almost all of these species are occurring in the ‘mountainous’ regions of the state (>200 m a.s.l.), the Sauerland and the Eifel. The upper reaches of the Ruhr catchment have been found to be relatively rich in vulnerable species, including several locally rare species. This index can assist conservationists to identify “hotspots” in terms of climate vulnerability and climate change refuge areas that can be considered for protection or the application of restoration measures at a local and regional scale. Nevertheless, not all species have complete autecological information, which hinders our ability to fully recognize the areas of priority. To further stabilize and enhance the applicability of this method, it is essential to fill these knowledge gaps in the future.     

Multiple stressors,nonlinear effects and the implications of climate change impacts on marine coastal ecosystems

Global climate change will undoubtedly be a pressure on coastal marine ecosystems, affecting not only species distributions and physiology but also ecosystem functioning. In the coastal zone, the environmental variables that may drive ecological responses to climate change include temperature, wave energy, upwelling events and freshwater inputs, and all act and interact at a variety of spatial and temporal scales. To date, we have a poor understanding of how climate‐related environmental changes may affect coastal marine ecosystems or which environmental variables are likely to produce priority effects. Here we use time series data (17 years) of coastal benthic macrofauna to investigate responses to a range of climate‐influenced variables including sea‐surface temperature, southern oscillation indices (SOI, Z4), wind‐wave exposure, freshwater inputs and rainfall. We investigate responses from the abundances of individual species to abundances of functional traits and test whether species that are near the edge of their tolerance to another stressor (in this case sedimentation) may exhibit stronger responses. The responses we observed were all nonlinear and some exhibited thresholds. While temperature was most frequently an important predictor, wave exposure and ENSO‐related variables were also frequently important and most ecological variables responded to interactions between environmental variables. There were also indications that species sensitive to another stressor responded more strongly to weaker climate‐related environmental change at the stressed site than the unstressed site. The observed interactions between climate variables, effects on key species or functional traits, and synergistic effects of additional anthropogenic stressors have important implications for understanding and predicting the ecological consequences of climate change to coastal ecosystems.     

基于MaxEnt模型模拟肯尼亚茜草科河骨木属植物的潜在分布及其在植物志中的应用初探

物种分布模型目前被广泛应用于生物学、生态学和保护生物学的各个领域。该文以肯尼亚茜草科河骨木属（Afrocanthium ）为例,利用最大熵模型（MaxEnt）模拟植物在当前气候情景下的潜在分布,并将这些分布图利用于正在编写的《肯尼亚植物志》中。结果显示,基于足够的原始标本记录,模型能够很好地模拟出每种植物的潜在分布区域。相比传统和新一代植物志仅提供标本信息点或是粗略分布图,《肯尼亚植物志》预采用的潜在分布图,将为志书使用者提供更加全面、实用的信息。     

Parapatric species and the implications for climate change studies: a case study on hares in Europe

Parapatry is a biogeographical term used to refer to organisms whose ranges do not overlap, but are immediately adjacent to each other; they only co‐occur – if at all – in a narrow contact zone. Often there are no environmental barriers in the contact zones, hence competitive interaction is usually advocated as the factor that modulates species distribution ranges. Even though the effects of climate change on species distribution have been widely studied, few studies have explored these effects on the biogeographical relationships between closely related, parapatric, species. We modelled environmental favourability for three parapatric hare species in Europe – Lepus granatensis, L. europaeus and L. timidus – using ecogeographical variables and projected the models into the future according to the IPCC A2 emissions scenario. Favourabilities for present and future scenarios were combined using fuzzy logic with the following aims: (i) to determine the biogeographical relationships between hare species in parapatry, that is L. granatensis/L. europaeus and L. europaeus/L. timidus and (ii) to assess the effects of climate change on each species as well as on their interspecific interactions. In their contact area L. granatensis achieved higher favourability values than L. europaeus, suggesting that if both species have a similar population status, the former species may have some advantages over the latter if competitive relationships are established. Climate change had the most striking effect on the distribution of L. timidus, especially when interspecific interactions with L. europaeus were taken into account, which may compromise the co‐existence of L. timidus. The results of this study are relevant not only for understanding the distribution patterns of the hares studied and the effects of climate change on these patterns, but also for improving the general application of species distribution models to the prediction of the effects of climate change on biodiversity.     

Improving species distribution models for climate change studies: variable selection and scale

Statistical species distribution models (SDMs) are widely used to predict the potential changes in species distributions under climate change scenarios. We suggest that we need to revisit the conceptual framework and ecological assumptions on which the relationship between species distributions and environment is based. We present a simple conceptual framework to examine the selection of environmental predictors and data resolution scales. These vary widely in recent papers, with light inconsistently included in the models. Focusing on light as a necessary component of plant SDMs, we briefly review its dependence on aspect and slope and existing knowledge of its influence on plant distribution. Differences in light regimes between north‐ and south‐facing aspects in temperate latitudes can produce differences in temperature equivalent to moves 200 km polewards. Local topography may create refugia that are not recognized in many climate change SDMs using coarse‐scale data. We argue that current assumptions about the selection of predictors and data resolution need further testing. Application of these ideas can clarify many issues of scale, extent and choice of predictors, and potentially improve the use of SDMs for climate change modelling of biodiversity.     

Ecological niches as stable distributional constraints on mammal species, with implications for Pleistocene extinctions and climate change projections for biodiversity

Aim Theoretical work suggests that species’ ecological niches should remain relatively constant over long‐term ecological time periods, but empirical tests are few. We present longitudinal studies of 23 extant mammal species, modelling ecological niches and predicting geographical distributions reciprocally between the Last Glacial Maximum and present to test this evolutionary conservatism. Location This study covered distributional shifts in mammal species across the lower 48 states of the United States. Methods We used a machine‐learning tool for modelling species’ ecological niches, based on known occurrences and electronic maps summarizing ecological dimensions, to assess the ability of ecological niches as modelled in one time period to predict the geographical distribution of the species in another period, and vice versa. Results High intertemporal predictivity between niche models and species’ occurrences indicate that niche conservatism is widespread among the taxa studied, particularly when statistical power is considered as a reason for failure of reciprocal predictions. Niche projections to the present for 8 mammal taxa that became extinct at the end of the Pleistocene generally increased in area, and thus do not support the hypothesis of niche collapse as a major driving force in their extinction. Main conclusions Ecological niches represent long‐term stable constraints on the distributional potential of species; indeed, this study suggests that mammal species have tracked consistent climate profiles throughout the drastic climate change events that marked the end of the Pleistocene glaciations. Many current modelling efforts focusing on anticipating climate change effects on species’ potential geographical distributions will be bolstered by this result — in essence, the first longitudinal demonstration of niche conservatism.     

Geographic disparities and moral hazards in the predicted impacts of climate change on human populations

Aim It has been qualitatively understood for a long time that climate change will have widely varying effects on human well‐being in different regions of the world. The spatial complexities underlying our relationship to climate and the geographical disparities in human demographic change have, however, precluded the development of global indices of the predicted regional impacts of climate change on humans. Humans will be most negatively affected by climate change in regions where populations are strongly dependent on climate and favourable climatic conditions decline. Here we use the relationship between the distribution of human population density and climate as a basis to develop the first global index of predicted impacts of climate change on human populations. Location Global. Methods We use spatially explicit models of the present relationship between human population density and climate along with forecasted climate change to predict climate vulnerabilities over the coming decades. We then globally represent regional disparities in human population dynamics estimated with our ecological niche model and with a demographic forecast and contrast these disparities with CO₂ emissions data to quantitatively evaluate the notion of moral hazard in climate change policies. Results Strongly negative impacts of climate change are predicted in Central America, central South America, the Arabian Peninsula, Southeast Asia and much of Africa. Importantly, the regions of greatest vulnerability are generally distant from the high‐latitude regions where the magnitude of climate change will be greatest. Furthermore, populations contributing the most to greenhouse gas emissions on a per capita basis are unlikely to experience the worst impacts of climate change, satisfying the conditions for a moral hazard in climate change policies. Main conclusions Regionalized analysis of relationships between distribution of human population density and climate provides a novel framework for developing global indices of human vulnerability to climate change. The predicted consequences of climate change on human populations are correlated with the factors causing climate change at the regional level, providing quantitative support for many qualitative statements found in international climate change assessments.     

Potential impacts of climatic change on the breeding and non-breeding ranges and migration distance of European Sylvia warblers

Aim  To explore the potential impacts of climatic change on species with different migratory strategies using Sylvia warblers breeding in Europe as a ‘model’ species group. Location  Europe and Africa. Methods  Climate response surfaces and generalized additive models (GAMs) were used to model relationships between species recorded breeding and non‐breeding ranges and recent climate. Species potential future breeding and non‐breeding ranges were simulated for three scenarios of late 21st‐century climate. The simulated potential future and present ranges were compared in terms of their relative extent and overlap, as well as their location. The impact of any shifts in potential range location on migration distance were quantified. Results  Potential breeding ranges consistently showed a shift northwards, whereas potential non‐breeding ranges showed no consistent directional shift, even when trans‐Saharan migrants were considered separately from resident/short‐distance or partial migrants. Future potential range extent relative to simulated recent range extent varied considerably among species, although on average range extent increased. Overlap between future and recent simulated range was generally low, averaging < 36% for both breeding and non‐breeding ranges. Overlap was consistently less for range‐restricted than for widespread species. Migration distance increased generally, by about twice as much in the case of trans‐Saharan migrant species than for short‐distance migrants. In many cases potential future non‐breeding areas were simulated in regions far from the species present non‐breeding area, suggesting that new migration strategies and routes may need to be developed in response to climatic change. Main conclusions  Migratory species can be expected to suffer greater negative impacts from climatic change than species that are resident or undertake only short‐distance or partial migrations. Trans‐Saharan migrants face the greatest potential increases in migration distances, whereas range‐restricted species are expected to experience major population reductions because of the limited, or in some cases lack of, overlap between their present and potential future ranges.