Development and assessment of indices to determine stream fish vulnerability to climate change and habitat alteration

Understanding the future impacts of climate and land use change are critical for long-term biodiversity conservation. We developed and compared two indices to assess the vulnerability of stream fish in Missouri, USA based on species environmental tolerances, rarity, range size, dispersal ability and on the average connectivity of the streams occupied by each species. These two indices differed in how environmental tolerance was classified (i.e., vulnerability to habitat alteration, changes in stream temperature, and changes to flow regimes). Environmental tolerance was classified based on measured species responses to habitat alteration, and extremes in stream temperatures and flow conditions for one index, while environmental tolerance for the second index was based on species’ traits. The indices were compared to determine if vulnerability scores differed by index or state listing status. We also evaluated the spatial distribution of species classified as vulnerable to habitat alteration, changes in stream temperature, and change in flow regimes. Vulnerability scores were calculated for all 133 species with the trait association index, while only 101 species were evaluated using the species response index, because 32 species lacked data to analyze for a response. Scores from the trait association index were greater than the species response index. This is likely due to the species response index's inability to evaluate many rare species, which generally had high vulnerability scores for the trait association index. The indices were consistent in classifying vulnerability to habitat alteration, but varied in their classification of vulnerability due to increases in stream temperature and alterations to flow regimes, likely because extremes in current climate may not fully capture future conditions and their influence on stream fish communities. Both indices showed higher mean vulnerability scores for listed species than unlisted species, which provided a coarse measure of validation. Our indices classified species identified as being in need of conservation by the state of Missouri as highly vulnerable. The distribution of vulnerable species in Missouri showed consistent patterns between indices, with the more forest-dominated, groundwater fed streams in the Ozark subregion generally having higher numbers and proportions of vulnerable species per site than subregions that were agriculturally dominated with more overland flow. These results suggest that both indices will identify similar habitats as conservation action targets despite discrepancies in the classification of vulnerable species. Our vulnerability assessment provides a framework that can be refined and used in other regions.     

Large-scale climate change vulnerability assessment of stream health

Freshwater streams are critical resources that provide multiple benefits to humans and aquatic biota alike. As climate changes, it is projected that changes to the hydrological cycle and water temperatures will affect individual biota and aquatic ecosystems as a whole. The goal of this study was to determine the extent of climate change impacts on stream ecosystems as represented by four commonly used stream health indicators (Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT), Family Index of Biotic Integrity (FIBI), Hilsenhoff Biotic Index (HBI), and fish Index of Biotic Integrity (IBI)). Seven watersheds in Michigan were selected based on stream thermal regimes. The Soil and Water Assessment Tool was used to simulate streamflow and pollutant loads. Important variables for each thermal class were selected using a Bayesian variable selection method and used as inputs to adaptive neuro-fuzzy inference systems models of EPT, FIBI, HBI, and IBI. Finally, an ensemble of climate models from the Coupled Model Intercomparison Project Phase 5 were used to determine the impacts of climate on the stream health in 2020–2040 compared to 1980–2000. The risk of declining stream health was determined using cumulative distribution functions. A stream temperature regression model was also developed to assess potential changes in stream thermal regimes, which could cause shifts in composition of aquatic communities. Several flow regime variables, including those related to flow variability, duration of extreme events, and timing were mainly affected by changing climate. At the watershed scale, most indicators were relatively insensitive to changing climate and the magnitude of stream health decline was low. However, at the reach scale, there are many instances of high risk and large magnitude of declines in the stream health indicators. At the same time, several streams experienced changes in thermal class, mostly transitioning from cold-transitional and cool streams to warm streams. This research demonstrated the applicability of the stream health modeling process in performing a climate change impacts assessment.     

High community turnover and dispersal limitation relative to rapid climate change

Aim Many competing hypotheses seek to identify the mechanisms behind species richness gradients. Yet, the determinants of species turnover over broad scales are uncertain. We test whether environmental dissimilarity predicts biotic turnover spatially and temporally across an array of environmental variables and spatial scales using recently observed climate changes as a pseudo‐experimental opportunity. Location Canada. Methods We used an extensive database of observation records of 282 Canadian butterfly species collected between 1900 and 2010 to characterize spatial and temporal turnover based on Jaccard indices. We compare relationships between spatial turnover and differences in an array of relevant environmental conditions, including aspects of temperature, precipitation, elevation, primary productivity and land cover. Measurements were taken within 100‐, 200‐ and 400‐km grid cells, respectively. We tested the relative importance of each variable in predicting spatial turnover using bootstrap analysis. Finally, we tested for effects of temperature and precipitation change on temporal turnover, including distinctly accounting for turnover under individual species’ potential dispersal limitations. Results Temperature differences between areas correlate with spatial turnover in butterfly assemblages, independently of distance, sampling differences or the spatial resolution of the analysis. Increasing temperatures are positively related to biotic turnover within quadrats through time. Limitations on species dispersal may cause observed biotic turnover to be lower than expected given the magnitude of temperature changes through time. Main conclusions Temperature differences can account for spatial trends in biotic dissimilarity and turnover through time in areas where climate is changing. Butterfly communities are changing quickly in some areas, probably reflecting the dispersal capacities of individual species. However, turnover is lower through time than expected in many areas, suggesting that further work is needed to understand the factors that limit dispersal across broad regions. Our results illustrate the large‐scale effects of climate change on biodiversity in areas with strong environmental gradients.     

Amazon's vulnerability to climate change heightened by deforestation and man‐made dispersal barriers

Species migrations in response to climate change have already been observed in many taxonomic groups worldwide. However, it remains uncertain if species will be able to keep pace with future climate change. Keeping pace will be especially challenging for tropical lowland rainforests due to their high velocities of climate change combined with high rates of deforestation, which may eliminate potential climate analogs and/or increase the effective distances between analogs by blocking species movements. Here, we calculate the distances between current and future climate analogs under various climate change and deforestation scenarios. Under even the most sanguine of climate change models (IPSL_CM4, A1b emissions scenario), we find that the median distance between areas in the Amazon rainforest and their closest future (2050) climate analog as predicted based on just temperature changes alone is nearly 300 km. If we include precipitation, the median distance increases by over 50% to >475 km. Since deforestation is generally concentrated in the hottest and driest portions of the Amazon, we predict that the habitat loss will have little direct impact on distances between climate analogs. If, however, deforested areas also act as a barrier to species movements, nearly 30% or 55% of the Amazon will effectively have no climate analogs anywhere in tropical South America under projections of reduced or Business‐As‐Usual deforestation, respectively. These ‘disappearing climates’ will be concentrated primarily in the southeastern Amazon. Consequently, we predict that several Amazonian ecoregions will have no areas with future climate analogs, greatly increasing the vulnerability of any populations or species specialized on these conditions. These results highlight the importance of including multiple climatic factors and human land‐use in predicting the effects of climate change, as well as the daunting challenges that Amazonian diversity faces in the near future.     

气候变化背景下野生动物脆弱性评估方法研究进展

脆弱性评估是研究气候变化影响野生动物的重要内容,识别野生动物脆弱性,是适应和减缓气候变化影响的关键和基础。开展气候变化背景下野生动物的脆弱性评估工作,目的是为了确定易受气候变化影响的物种和明确导致物种脆弱性的因素,其评估结果有助于人类认识气候变化对野生动物的影响,为野生动物适应气候变化保护对策的制定提供科学依据。对野生动物而言(物种),脆弱性是物种受气候变化影响的程度,包括暴露度、敏感性和适应能力三大要素。其中,暴露度是由气候变化引起的外在因素,如温度、降雨量、极值天气等;敏感性是受物种自身因素影响,如种间关系、耐受性等;适应能力是物种通过自身调整来减小气候变化带来的影响,如迁移或扩散到适宜生境的能力、塑性反应和进化反应等。对近期有关气候变化背景下野生动物脆弱性评估方法予以综述,比较每种评估方法所选取指标的差异,总结在脆弱性评估中遇到的不确定性指标的处理方法,以及脆弱性评估结果在野生动物适应气候变化对策中的应用。通过总结野生动物脆弱性评估方法,以期为气候变化背景下评估我国野生动物资源的脆弱性提供参考方法。     

Evaluating drivers of vulnerability to climate change: a guide for insect conservation strategies

Ongoing global climate change presents serious challenges in conservation biology, forcing us to revisit previous tools and principles based on how species may respond to novel climatic conditions. There is currently a major gap between predictions of species vulnerability and management strategies, despite the fact that linking these areas is fundamental for future biodiversity conservation. Herein, we evaluate what drives vulnerability to climate change in three Iberian endemic water beetles, representing three independent colonizations of the same habitat, employing comparative thermal physiology, species distribution models and estimations of species dispersal capacity. We derive conservation strategies for each species based on their differential capacity to persist and/or potential to shift their ranges in response to global warming. We demonstrate that species may be affected by climatic warming in very different ways, despite having broadly similar ecological and biogeographical traits. The proposed framework provides an effective complement to traditional species vulnerability assessments, and could aid the development of more effective conservation strategies in the face of global warming.     

Landscape fragmentation affects responses of avian communities to climate change

Forecasting the consequences of climate change is contingent upon our understanding of the relationship between biodiversity patterns and climatic variability. While the impacts of climate change on individual species have been well‐documented, there is a paucity of studies on climate‐mediated changes in community dynamics. Our objectives were to investigate the relationship between temporal turnover in avian biodiversity and changes in climatic conditions and to assess the role of landscape fragmentation in affecting this relationship. We hypothesized that community turnover would be highest in regions experiencing the most pronounced changes in climate and that these patterns would be reduced in human‐dominated landscapes. To test this hypothesis, we quantified temporal turnover in avian communities over a 20‐year period using data from the New York State Breeding Atlases collected during 1980–1985 and 2000–2005. We applied Bayesian spatially varying intercept models to evaluate the relationship between temporal turnover and temporal trends in climatic conditions and landscape fragmentation. We found that models including interaction terms between climate change and landscape fragmentation were superior to models without the interaction terms, suggesting that the relationship between avian community turnover and changes in climatic conditions was affected by the level of landscape fragmentation. Specifically, we found weaker associations between temporal turnover and climatic change in regions with prevalent habitat fragmentation. We suggest that avian communities in fragmented landscapes are more robust to climate change than communities found in contiguous habitats because they are comprised of species with wider thermal niches and thus are less susceptible to shifts in climatic variability. We conclude that highly fragmented regions are likely to undergo less pronounced changes in composition and structure of faunal communities as a result of climate change, whereas those changes are likely to be greater in contiguous and unfragmented habitats.     

Dispersal limitations increase vulnerability under climate change for reptiles and amphibians in the southwestern United States

Species conservation plans frequently rely on information that spans political and administrative boundaries, especially when predictions are needed of future habitat under climate change; however, most species conservation plans and their requisite predictions of future habitat are often limited in geographical scope. Moreover, dispersal constraints for species of concern are not often incorporated into distribution models, which can result in overly optimistic predictions of future habitat. We used a standard modeling approach across a suite of 23 taxa of amphibians and reptiles in the North American deserts (560,024 km² across 13 ecoregions) to assess impacts of climate change on habitat and combined landscape population dispersal simulations with species distribution modeling to reduce the risk of predicting future habitat in areas that are not available to species given their dispersal abilities. We used 3 general circulation models and 2 representative concentration pathways (RCPs) to represent multiple scenarios of future habitat potential and assess which study species may be most vulnerable to changes forecasted under each climate scenario. Amphibians were the most vulnerable taxa, but the most vulnerable species tended to be those with the lowest dispersal ability rather than those with the most specialized niches. Under the most optimistic climate scenario considered (RCP 2.6; a stringent scenario requiring declining emissions from 2020 to near zero emissions by 2100), 76% of the study area may experience a loss of >20% of the species examined, while up to 87% of the species currently present may be lost in some areas under the most pessimistic climate scenario (RCP 8.5; a scenario wherein greenhouse gases continue to increase through 2100 based on trajectories from the mid-century). Most areas with high losses were concentrated in the Arizona and New Mexico Plateau ecoregion, the Edwards Plateau in Texas, and the Southwestern Tablelands in New Mexico and Texas, USA. Under the most pessimistic climate scenario, all species are predicted to lose some existing habitat, with an average of 34% loss of extant habitat across all species. Even under the most optimistic scenario, we detected an average loss of 24% of extant habitat across all species, suggesting that changing climates may influence the ranges of reptiles and amphibians in the Southwest.     

Identifying priority areas for reducing species vulnerability to climate change

Aim The dimensions of species vulnerability to climate change are complex, and this impedes efforts to provide clear advice for conservation planning. In this study, we used a formal framework to assess species vulnerability to climate change quantifying exposure, sensitivity and adaptive capacity and then used this information to target areas for reducing vulnerability at a regional scale. Location The 6500‐km² Mount Lofty Ranges region in South Australia. Methods We quantified the vulnerability of 171 plant species in a fragmented yet biologically important agro‐ecological landscape, typical of many temperate zones globally. We specified exposure, using three climate change scenarios; sensitivity, as the adverse impact of climate change on species’ spatial distribution; and adaptive capacity, as the ability of species to migrate calculated using dispersal kernels. Priority areas for reducing vulnerability were then identified by incorporating these various components into a single priority index. Results Climate change had a variable impact on species distributions. Those species whose range decreased or shifted geographically were attributed higher sensitivity than those species that increased geographic range or remained unchanged. The ability to adapt to range changes in response to shifting climates varies both spatially and between species. Areas of highest priority for reducing vulnerability were found at higher altitudes and lower latitudes with increasing severity of climate change. Main conclusions Our study demonstrates the use of a single spatially explicit index that identifies areas in the landscape for targeting specific conservation and restoration actions to reduce species vulnerability to climate change. Our index can be transferred to other regions around the world in which climate change poses an increasing threat to native species.     

Assessing vulnerability of giant pandas to climate change in the Qinling Mountains of China

Climate change might pose an additional threat to the already vulnerable giant panda (Ailuropoda melanoleuca). Effective conservation efforts require projections of vulnerability of the giant panda in facing climate change and proactive strategies to reduce emerging climate‐related threats. We used the maximum entropy model to assess the vulnerability of giant panda to climate change in the Qinling Mountains of China. The results of modeling included the following findings: (1) the area of suitable habitat for giant pandas was projected to decrease by 281 km² from climate change by the 2050s; (2) the mean elevation of suitable habitat of giant panda was predicted to shift 30 m higher due to climate change over this period; (3) the network of nature reserves protect 61.73% of current suitable habitat for the species, and 59.23% of future suitable habitat; (4) current suitable habitat mainly located in Chenggu, Taibai, and Yangxian counties (with a total area of 987 km²) was predicted to be vulnerable. Assessing the vulnerability of giant panda provided adaptive strategies for conservation programs and national park construction. We proposed adaptation strategies to ameliorate the predicted impacts of climate change on giant panda, including establishing and adjusting reserves, establishing habitat corridors, improving adaptive capacity to climate change, and strengthening monitoring of giant panda.     

Environmental and spatial effects on coastal stream fishes in the Atlantic rain forest

Contemporary and historical factors influence assemblage structure. The environmental and spatial influences acting on fish organization of rain forest coastal streams in the Atlantic rain forest of Brazil were examined. Fish (and functional traits such as morphology, diet, velocity preference, body size), environmental variables (pH, water conductivity, dissolved oxygen, temperature, stream width, flow, depth, substrate), and altitude were measured from 59 stream reaches. Asymmetric eigenvector maps were used to model the spatial structure considering direction of fish movements. Elevation played an important role—fish abundance, biomass, and richness all decrease with increasing elevation. Fish communities are influenced by both environmental and spatial factors, but downstream movements were shown to be more important in explaining the observed spatial variation than were bidirectional and upstream movements. Spatial factors, as well as environmental variables influenced by the spatial structure, explained most of the variation in fish assemblages. The strong spatial structuring is probably attributable to asymmetric dispersal limitation along the altitudinal profile: Dispersal is likely to be more limiting moving upstream than downstream. These fish assemblages reflect scale-dependent processes: At the stream-reach scale, fish respond to local environmental filters (habitat structure, water chemistry, and food supply), which are in turn influenced by a larger scale, namely the altitudinal gradient expected in steep coastal mountains. Thus, environmental drivers are not independent of spatial factors, and the effects of local factors can be confounded across the altitudinal gradient. These results may have implications for conservation, because downstream reaches are often neglected in management and conservation plans.     

Dispersal response to climate change: scaling down to intraspecific variation

Range shift, a widespread response to climate change, will depend on species abilities to withstand warmer climates. However, these abilities may vary within species and such intraspecific variation can strongly impact species responses to climate change. Facing warmer climates, individuals should disperse according to their thermal optimum with consequences for species range shifts. Here, we studied individual dispersal of a reptile in response to climate warming and preferred temperature using a semi‐natural warming experiment. Individuals with low preferred temperatures dispersed more from warmer semi‐natural habitats, whereas individuals with higher preferred temperatures dispersed more from cooler habitats. These dispersal decisions partly matched phenotype‐dependent survival rates in the different thermal habitats, suggesting adaptive dispersal decisions. This process should result into a spatial segregation of thermal phenotypes along species moving ranges which should facilitate local adaptation to warming climates. We therefore call for range shift models including intraspecific variation in thermal phenotype and dispersal decision.     

Exploring the homogeneity of terrestrial subterranean communities at a local spatial scale

1. Although caves are generally perceived as isolated habitats, at the local scale, they are often interconnected via a network of fissures in the bedrock. Accordingly, caves in close proximity are expected to host the same, or very similar, animal communities. 2. We explored the extent to which subterranean arthropod communities are homogenous at a local spatial scale of less than 1 km², along with which cave-specific environmental features result in a departure from the expected homogeneous pattern. We approached this question by studying richness and turnover in terrestrial invertebrate communities of 27 caves in a small karst massif in the Western Italian Alps. 3. Specialised subterranean species were homogeneously distributed among caves and were not influenced by seasonality. The only factor driving their distribution was the distance from the cave entrance, with deeper caves yielding a greater diversity of species. 4. Significant spatio-temporal turnover in species not specialised to subterranean life was observed. In summer, there was a significant homogenisation of the community and a more even distribution of species among sites; in winter, these species were missing or found exclusively at greater depths, where environmental conditions were more stable. Furthermore, caves at lower elevations yielded, on average, a greater diversity and abundance of these species. 5. This study demonstrated that the theoretical expectation of no turnover in community composition in caves in close proximity is not always met. Turnover can be mostly attributed to seasonal patterns and sampling depth; thus, our findings have implications for planning sampling and monitoring activities in caves.     

The importance of landscape and habitat properties in explaining instantaneous and long‐term distributions of large branchiopods in subtropical temporary pans

1. The notion that the spatial configuration of habitat patches has to be taken into account to understand the structure and dynamics of ecological communities is the starting point of metacommunity ecology. One way to assess metacommunity structure is to investigate the relative importance of environmental heterogeneity and spatial structure in explaining community patterns over different spatial and temporal scales. 2. We studied metacommunity structure of large branchiopod assemblages characteristic of subtropical temporary pans in SE Zimbabwe using two community data sets: a community snapshot and a long‐term data set covering 4 years. We assessed the relative importance of environmental heterogeneity and dispersal (inferred from patch occupancy patterns) as drivers of community structure. Furthermore, we contrasted metacommunity patterns in pans that occasionally connect to the river (floodplain pans) and pans that lack such connections altogether (endorheic pans) using redundancy models. 3. Echoes of species sorting and dispersal limitation emerge from our data set, suggesting that both local and regional processes contribute to explaining branchiopod assemblages in this system. Relative importance of local and regional factors depended on the type of data set considered. Overall, habitat characteristics that vary in time, such as conductivity, hydroperiod and vegetation cover, best explained the instantaneous species composition observed during a snapshot sampling while long‐term species composition appeared to be linked to more constant intrinsic habitat properties such as river connectivity and spatial location.     

Effect of land-use heterogeneity on carabid communities at the landscape scale

Carabid beetle assemblages were studied to assess how diversity and community structure varied along a gradient of land-use. This gradient was composed of six 1 km² quadrats with an increasing proportion of agricultural land reflecting the anthropogenic fragmentation and intensification of landscapes. Carabid species richness and abundance was predicted to peak in the most heterogeneous landscape, in accord with the intermediate disturbance hypothesis (IDH), and then decline as agricultural intensification increased. It was also predicted that the different landscapes would support beetle communities distinct from each other. The IDH was unsupported-in both years of this study carabid species richness and abundance was greatest in the most intensively managed, agricultural sites. Detrended correspondence analysis revealed a clear separation in beetle community structure between forested and open habitats and between different forest types. Canonical correspondence analysis revealed a significant correlation between beetle community structure and the environment, showing distinct beetle assemblages to be significantly associated with specific edaphic and botanical features of the land-use gradient. This study adds to increasing evidence that landscape-scale patterns in land-use significantly affect beetle community structure producing distinct assemblages.     

气候变化对内蒙古中东部沙地-湿地镶嵌景观的影响

利用小波分析和遥感技术相结合的方法,研究了气候变化对1961—2005年内蒙古中东部沙地-湿地镶嵌景观的影响.结果表明：1961—2005年,研究区年均气温呈直线上升趋势,增温率为0.32 ℃·（10 a）^-1,年降水量变化呈现30 a的长周期和15 a的短周期,年均风速呈下降趋势,10 a的风速减小率为0.26 m·s^-1;研究区东南部存在一个气候变化恒定区域,由此恒定区向西北进入浑善达克沙地腹地,向东逐步进入科尔沁沙地腹地;2010年以前,研究区仍将维持气温升高、降水偏少、风速减小的趋势;受气候暖干化的影响,浑善达克沙地及其周围湿地的总面积呈逐年缩小趋势,随着沙地内部植被的退化,流动沙地不断扩大、湿地萎缩、湖泊干涸,而相应的固定和半固定沙地面积则明显减少.     

Determinants of the distribution of nitrogen-cycling microbial communities at the landscape scale

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. However, a landscape perspective is needed to understand the relative importance of local and regional factors and land management for the microbial communities and the ecosystem services they provide. In the most comprehensive analysis of spatial patterns of microbial communities to date, we investigated the distribution of functional microbial communities involved in N-cycling and of the total bacterial and crenarchaeal communities over 107 sites in Burgundy, a 31 500 km² region of France, using a 16 × 16 km² sampling grid. At each sampling site, the abundance of total bacteria, crenarchaea, nitrate reducers, denitrifiers- and ammonia oxidizers were estimated by quantitative PCR and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time, and soil physico-chemical properties to the spatial distribution of the different communities were analyzed by canonical variation partitioning. Our results indicate that 43–85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of microbial communities at the landscape scale. The present study highlights the potential of a spatially explicit approach for microbial ecology to identify the overarching factors driving the spatial heterogeneity of microbial communities even at the landscape scale.