A socio‐ecological model for predicting impacts of land‐use and climate change on regional plant diversity in the Austrian Alps

Climate and land‐use change jointly affect the future of biodiversity. Yet, biodiversity scenarios have so far concentrated on climatic effects because forecasts of land use are rarely available at appropriate spatial and thematic scales. Agent‐based models (ABMs) represent a potentially powerful but little explored tool for establishing thematically and spatially fine‐grained land‐use scenarios. Here, we use an ABM parameterized for 1,329 agents, mostly farmers, in a Central European model region, and simulate the changes to land‐use patterns resulting from their response to three scenarios of changing socio‐economic conditions and three scenarios of climate change until the mid of the century. Subsequently, we use species distribution models to, first, analyse relationships between the realized niches of 832 plant species and climatic gradients or land‐use types, respectively, and, second, to project consequent changes in potential regional ranges of these species as triggered by changes in both the altered land‐use patterns and the changing climate. We find that both drivers determine the realized niches of the studied plants, with land use having a stronger effect than any single climatic variable in the model. Nevertheless, the plants' future distributions appear much more responsive to climate than to land‐use changes because alternative future socio‐economic backgrounds have only modest impact on land‐use decisions in the model region. However, relative effects of climate and land‐use changes on biodiversity may differ drastically in other regions, especially where landscapes are still dominated by natural or semi‐natural habitat. We conclude that agent‐based modelling of land use is able to provide scenarios at scales relevant to individual species distribution and suggest that coupling ABMs with models of species' range change should be intensified to provide more realistic biodiversity forecasts.     

Choice of baseline climate data impacts projected species' responses to climate change

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species‐climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040–2069, 2070–2099), using downscaled climate projections, and calculated species turnover and changes in species‐specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species‐specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site‐level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses.     

Back to the future: using historical climate variation to project near‐term shifts in habitat suitable for coast redwood

Studies that model the effect of climate change on terrestrial ecosystems often use climate projections from downscaled global climate models (GCMs). These simulations are generally too coarse to capture patterns of fine‐scale climate variation, such as the sharp coastal energy and moisture gradients associated with wind‐driven upwelling of cold water. Coastal upwelling may limit future increases in coastal temperatures, compromising GCMs’ ability to provide realistic scenarios of future climate in these coastal ecosystems. Taking advantage of naturally occurring variability in the high‐resolution historic climatic record, we developed multiple fine‐scale scenarios of California climate that maintain coherent relationships between regional climate and coastal upwelling. We compared these scenarios against coarse resolution GCM projections at a regional scale to evaluate their temporal equivalency. We used these historically based scenarios to estimate potential suitable habitat for coast redwood (Sequoia sempervirens D. Don) under ‘normal’ combinations of temperature and precipitation, and under anomalous combinations representative of potential future climates. We found that a scenario of warmer temperature with historically normal precipitation is equivalent to climate projected by GCMs for California by 2020–2030 and that under these conditions, climatically suitable habitat for coast redwood significantly contracts at the southern end of its current range. Our results suggest that historical climate data provide a high‐resolution alternative to downscaled GCM outputs for near‐term ecological forecasts. This method may be particularly useful in other regions where local climate is strongly influenced by ocean–atmosphere dynamics that are not represented by coarse‐scale GCMs.     

Dual impacts of climate change: forest migration and turnover through life history

Tree species are predicted to track future climate by shifting their geographic distributions, but climate‐mediated migrations are not apparent in a recent continental‐scale analysis. To better understand the mechanisms of a possible migration lag, we analyzed relative recruitment patterns by comparing juvenile and adult tree abundances in climate space. One would expect relative recruitment to be higher in cold and dry climates as a result of tree migration with juveniles located further poleward than adults. Alternatively, relative recruitment could be higher in warm and wet climates as a result of higher tree population turnover with increased temperature and precipitation. Using the USDA Forest Service's Forest Inventory and Analysis data at regional scales, we jointly modeled juvenile and adult abundance distributions for 65 tree species in climate space of the eastern United States. We directly compared the optimal climate conditions for juveniles and adults, identified the climates where each species has high relative recruitment, and synthesized relative recruitment patterns across species. Results suggest that for 77% and 83% of the tree species, juveniles have higher optimal temperature and optimal precipitation, respectively, than adults. Across species, the relative recruitment pattern is dominated by relatively more abundant juveniles than adults in warm and wet climates. These different abundance‐climate responses through life history are consistent with faster population turnover and inconsistent with the geographic trend of large‐scale tree migration. Taken together, this juvenile–adult analysis suggests that tree species might respond to climate change by having faster turnover as dynamics accelerate with longer growing seasons and higher temperatures, before there is evidence of poleward migration at biogeographic scales.     

Rainfall and temperatures changes have confounding impacts on Phytophthora cinnamomi occurrence risk in the southwestern USA under climate change scenarios

Global change will simultaneously impact many aspects of climate, with the potential to exacerbate the risks posed by plant pathogens to agriculture and the natural environment; yet, most studies that explore climate impacts on plant pathogen ranges consider individual climatic factors separately. In this study, we adopt a stochastic modeling approach to address multiple pathways by which climate can constrain the range of the generalist plant pathogen Phytophthora cinnamomi (Pc): through changing winter soil temperatures affecting pathogen survival; spring soil temperatures and thus pathogen metabolic rates; and changing spring soil moisture conditions and thus pathogen growth rates through host root systems. We apply this model to the southwestern USA for contemporary and plausible future climate scenarios and evaluate the changes in the potential range of Pc. The results indicate that the plausible range of this pathogen in the southwestern USA extends over approximately 200 000 km² under contemporary conditions. While warming temperatures as projected by the IPCC A2 and B1 emissions scenarios greatly expand the range over which the pathogen can survive winter, projected reductions in spring rainfall reduce its feasible habitat, leading to spatially complex patterns of changing risk. The study demonstrates that temperature and rainfall changes associated with possible climate futures in the southwestern USA have confounding impacts on the range of Pc, suggesting that projections of future pathogen dynamics and ranges should account for multiple pathways of climate–pathogen interaction.     

Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change

Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new quasi‐equilibrium suitable habitats (~2100) after accounting for the lag in colonization. However, it is an open question if and when these newly suitable habitats will be colonized under current fragmented landscapes and realistic migration rates. To evaluate this, we used a spatially explicit cell‐based model (SHIFT) that estimates colonization potentials under current fragmented habitats and several estimates of historical migration rates at a 1 km resolution. Computation time, which was previously the biggest constraint, was overcome by a novel application of convolution and Fast Fourier Transforms. SHIFT outputs, when intersected with future suitable habitats predicted by DISTRIB, allow assessment of colonization potential under future climates. In this article, we show how our approach can be used to screen multiple tree species for their colonization potentials under climate change. In particular, we use the DISTRIB and SHIFT models in combination to assess if the future dominant forest types in the north will really be dominated by oaks, as modelled via DISTRIB. Even under optimistic scenarios, we conclude that only a small fraction of the suitable habitats of oaks predicted by DISTRIB is likely to be occupied within 100 years, and this will be concentrated in the first 10–20 km from the current boundary. We also show how DISTRIB and SHIFT can be used to evaluate the potential for assisted migration of vulnerable tree species, and discuss the dynamics of colonization at range limits.     

Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates

Africa is predicted to be highly vulnerable to 21st century climatic changes. Assessing the impacts of these changes on Africa's biodiversity is, however, plagued by uncertainties, and markedly different results can be obtained from alternative bioclimatic envelope models or future climate projections. Using an ensemble forecasting framework, we examine projections of future shifts in climatic suitability, and their methodological uncertainties, for over 2500 species of mammals, birds, amphibians and snakes in sub‐Saharan Africa. To summarize a priori the variability in the ensemble of 17 general circulation models, we introduce a consensus methodology that combines co‐varying models. Thus, we quantify and map the relative contribution to uncertainty of seven bioclimatic envelope models, three multi‐model climate projections and three emissions scenarios, and explore the resulting variability in species turnover estimates. We show that bioclimatic envelope models contribute most to variability, particularly in projected novel climatic conditions over Sahelian and southern Saharan Africa. To summarize agreements among projections from the bioclimatic envelope models we compare five consensus methodologies, which generally increase or retain projection accuracy and provide consistent estimates of species turnover. Variability from emissions scenarios increases towards late‐century and affects southern regions of high species turnover centred in arid Namibia. Twofold differences in median species turnover across the study area emerge among alternative climate projections and emissions scenarios. Our ensemble of projections underscores the potential bias when using a single algorithm or climate projection for Africa, and provides a cautious first approximation of the potential exposure of sub‐Saharan African vertebrates to climatic changes. The future use and further development of bioclimatic envelope modelling will hinge on the interpretation of results in the light of methodological as well as biological uncertainties. Here, we provide a framework to address methodological uncertainties and contextualize results.     

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place‐based approach

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species’ niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species’ niches, resulting in predictions that are generally limited to climate‐occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place‐based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence–absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981–2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local‐scale differences in the realized niche of the American pika. This variation resulted in diverse and – in some cases – highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place‐based approach to species distribution modeling that includes fine‐scale factors when assessing current and future climate impacts on species’ distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas.     

Changes in potential habitat of 147 North American breeding bird species in response to redistribution of trees and climate following predicted climate change

Mounting evidence shows that organisms have already begun to respond to global climate change. Advances in our knowledge of how climate shapes species distributional patterns has helped us better understand the response of birds to climate change. However, the distribution of birds across the landscape is also driven by biotic and abiotic components, including habitat characteristics. We therefore developed statistical models of 147 bird species distributions in the eastern United States, using climate, elevation, and the distributions of 39 tree species to predict contemporary bird distributions. We used randomForest, a robust regression‐based decision tree ensemble method to predict contemporary bird distributions. These models were then projected onto three models of climate change under high and low emission scenarios for both climate and the projected change in suitable habitat for the 39 tree species. The resulting bird species models indicated that breeding habitat will decrease by at least 10% for 61–79 species (depending on model and emissions scenario) and increase by at least 10% for 38–52 species in the eastern United States. Alternatively, running the species models using only climate/elevation (omitting tree species), we found that the predictive power of these models was significantly reduced (p<0.001). When these climate/elevation‐only models were projected onto the climate change scenarios, the change in suitable habitat was more extreme in 60% of the species. In the end, the strong associations with vegetation tempers a climate/elevation‐only response to climate change and indicates that refugia of suitable habitat may persist for these bird species in the eastern US, even after the redistribution of tree species. These results suggest the importance of interacting biotic processes and that further fine‐scale research exploring how climate change may disrupt species specific requirements is needed.     

Projected climate and land use change alter western blacklegged tick phenology,seasonal host‐seeking suitability and human encounter risk in California

Global environmental change is having profound effects on the ecology of infectious disease systems, which are widely anticipated to become more pronounced under future climate and land use change. Arthropod vectors of disease are particularly sensitive to changes in abiotic conditions such as temperature and moisture availability. Recent research has focused on shifting environmental suitability for, and geographic distribution of, vector species under projected climate change scenarios. However, shifts in seasonal activity patterns, or phenology, may also have dramatic consequences for human exposure risk, local vector abundance and pathogen transmission dynamics. Moreover, changes in land use are likely to alter human–vector contact rates in ways that models of changing climate suitability are unlikely to capture. Here we used climate and land use projections for California coupled with seasonal species distribution models to explore the response of the western blacklegged tick (Ixodes pacificus), the primary Lyme disease vector in western North America, to projected climate and land use change. Specifically, we investigated how environmental suitability for tick host‐seeking changes seasonally, how the magnitude and direction of changing seasonal suitability differs regionally across California, and how land use change shifts human tick‐encounter risk across the state. We found vector responses to changing climate and land use vary regionally within California under different future scenarios. Under a hotter, drier scenario and more extreme land use change, the duration and extent of seasonal host‐seeking activity increases in northern California, but declines in the south. In contrast, under a hotter, wetter scenario seasonal host‐seeking declines in northern California, but increases in the south. Notably, regardless of future scenario, projected increases in developed land adjacent to current human population centers substantially increase potential human–vector encounter risk across the state. These results highlight regional variability and potential nonlinearity in the response of disease vectors to environmental change.     

Predator–prey interactions in a ladybeetle–aphid system depend on spatial scale

The outcome of species interactions may manifest differently at different spatial scales; therefore, our interpretation of observed interactions will depend on the scale at which observations are made. For example, in ladybeetle–aphid systems, the results from small‐scale cage experiments usually cannot be extrapolated to landscape‐scale field observations. To understand how ladybeetle–aphid interactions change across spatial scales, we evaluated predator–prey interactions in an experimental system. The experimental habitat consisted of 81 potted plants and was manipulated to facilitate analysis across four spatial scales. We also simulated a spatially explicit metacommunity model parallel to the experiment. In the experiment, we found that the negative effect of ladybeetles on aphids decreased with increasing spatial scales. This pattern can be explained by ladybeetles strongly suppressing aphids at small scales, but not colonizing distant patches fast enough to suppress aphids at larger scales. In the experiment, the positive effects of aphids on ladybeetles were strongest at three‐plant scale. In a model scenario where predators did not have demographic dynamics, we found, consistent with the experiment, that both the effects of ladybeetles on aphids and the effects of aphids on ladybeetles decreased with increasing spatial scales. These patterns suggest that dispersal was the primary cause of ladybeetle population dynamics in our experiment: aphids increased ladybeetle numbers at smaller scales because ladybeetles stayed in a patch longer and performed area‐restricted searches after encountering aphids; these behaviors did not affect ladybeetle numbers at larger spatial scales. The parallel experimental and model results illustrate how predator–prey interactions can change across spatial scales, suggesting that our interpretation of observed predator–prey dynamics would differ if observations were made at different scales. This study demonstrates how studying ecological interactions at a range of scales can help link the results of small‐scale ecological experiments to landscape‐scale ecological problems.     

Modelling the impact of climate and land use change on the geographical distribution of leaf anatomy in a temperate flora

Variation in plant functional traits has been related to variation in environmental conditions. In particular, the relationship between leaf traits and climate has received much attention. This paper presents a functional‐trait‐centred approach to identify potential impacts of climate and land use change on plant species assemblages. Using species atlas data, we modelled the relative frequencies of species with different leaf anatomies (LARF) as a function of observed climate and land use data on a regular spatial grid across Germany. Subsequently, we projected the geographical distribution of LARF with simulated climate and land use data for the late 21st century under two future scenarios. We used a conditional autoregressive regression model to account for spatially structured variation in LARF that remained unexplained by the environmental factors considered. We found a clear relationship between the climatic gradient of water availability and shifts in LARF: increasing water deficit was associated with a decreasing proportion of species with hygromorphic leaves in the composition and increasing proportions of species with scleromorphic and mesomorphic leaves. The variation in LARF due to land use was only small. Under future environmental scenarios the proportion of species with hygromorphic leaves was projected to decrease in all parts of Germany, whereas the proportions of species with sclero‐ and mesomorphic leaves were projected to increase on average. In particular, Germany's south‐western and north‐eastern areas were projected to experience functional change in LARF. Our study highlights the relationship between functional traits and plant species vulnerability to climate change. Our results suggest that the functional‐trait‐centred approach can provide a powerful additional modelling tool to estimate potential impacts of climate change on plant species assemblages.     

Climate warming is associated with smaller body size and shorter lifespans in moose near their southern range limit

Despite the importance of body size for individual fitness, population dynamics and community dynamics, the influence of climate change on growth and body size is inadequately understood, particularly for long‐lived vertebrates. Although temporal trends in body size have been documented, it remains unclear whether these changes represent the adverse impact of climate change (environmental stress constraining phenotypes) or its mitigation (via phenotypic plasticity or evolution). Concerns have also been raised about whether climate change is indeed the causal agent of these phenotypic shifts, given the length of time‐series analysed and that studies often do not evaluate – and thereby sufficiently rule out – other potential causes. Here, we evaluate evidence for climate‐related changes in adult body size (indexed by skull size) over a 4–decade period for a population of moose (Alces alces) near the southern limit of their range whilst also considering changes in density, predation, and human activities. In particular, we document: (i) a trend of increasing winter temperatures and concurrent decline in skull size (decline of 19% for males and 13% for females) and (ii) evidence of a negative relationship between skull size and winter temperatures during the first year of life. These patterns could be plausibly interpreted as an adaptive phenotypic response to climate warming given that latitudinal/temperature clines are often accepted as evidence of adaptation to local climate. However, we also observed: (iii) that moose with smaller skulls had shorter lifespans, (iv) a reduction in lifespan over the 4‐decade study period, and (v) a negative relationship between lifespan and winter temperatures during the first year of life. Those observations indicate that this phenotypic change is not an adaptive response to climate change. However, this decline in lifespan was not accompanied by an obvious change in population dynamics, suggesting that climate change may affect population dynamics and life‐histories differently.     

落叶松和水曲柳人工林细根生长、死亡和周转

 细根周转是陆地生态系统碳分配格局与过程的核心环节,而细根周转估计的关键是了解细根的生长和死亡动态。该研究以18年生落叶松(Larix gmelinii)和水曲柳(Fraxi nus mandshurica)人工林为对象,采用微根管（Minirhizotron）技术对两树种0～40 cm深度的细根生长和死亡动态进行了为期1年的观测,研究了两树种细根在不同土层深度的生长与死亡动态、细根周转以及与土壤有效氮含量、土壤温度、大气温度和降水的关系。结果表明：1） 落叶松平均细根生长（Root length density production, RLDP）0.0045 mm•cm^－2•d^－1）明显低于水曲柳RLDP（0.0077 mm•cm^－2•d^－1）。两个树种细根平均RLDP在表层（0～10 cm）最大,而底层（30～40 cm）最小 ,两树种平均细根死亡（Root length density mortality, RLDM）也表现同样规律 。水曲柳春季生长的细根占41.7%,夏季占39.7%,而落叶松细根生长分别是24.0%和51.2%,水曲柳细根死亡主要发生在春季（34.3%） 和夏季（34.0%）,而落叶松细根死亡主要发生在夏季和秋季（分别占28.5%和32.3%）,两 树种细根生长与死亡在冬季均较小;2）落叶松细根年生长量（0.94 mm•cm^－2•a^－1）和年死亡量（0.72 mm•cm^－2•a^－1）明显低于水曲柳（1.52和1.21 mm•cm^－2•a^－1）,两树种细根表层年生长量和年死亡量均最高,底层最低。落叶松细根年周转为3.1次•a^－1（按年生长量计算）和2.4次•a^－1（按年死亡量计算）,相比较,水曲柳细根年周转分别为2.7次•a^－1和2.2次•a^－1;3）土壤有效氮含量、土壤温度、大气温度和降水综合作用影响细根生长和死亡动态,可以解释细根生长80%的变异和细根死亡95%以上的变异。     

Climate change at the landscape scale: predicting fine-grained spatial heterogeneity in warming and potential refugia for vegetation

Current predictions of how species will respond to climate change are based on coarse‐grained climate surfaces or idealized scenarios of uniform warming. These predictions may erroneously estimate the risk of extinction because they neglect to consider spatially heterogenous warming at the landscape scale or identify refugia where species can persist despite unfavourable regional climate. To address this issue, we investigated the heterogeneity in warming that has occurred in a 10 km × 10 km area from 1972 to 2007. We developed estimates by combining long‐term daily observations from a limited number of weather stations with a more spatially comprehensive dataset (40 sites) obtained during 2005–2006. We found that the spatial distribution of warming was greater inland, at lower elevations, away from streams, and at sites exposed to the northwest (NW). These differences corresponded with changes in weather patterns, such as an increasing frequency of hot, dry NW winds. As plant species were biased in the topographic and geographic locations they occupied, these differences meant that some species experienced more warming than others, and are at greater risk from climate change. This species bias could not be detected at coarser scales. The uneven seasonal nature of warming (e.g. more warming in winter, minimums increased more than maximums) means that climate change predictions will vary according to which predictors are selected in species distribution models. Models based on a limited set of predictors will produce erroneous predictions when the correct limiting factor is not selected, and this is difficult to avoid when temperature predictors are correlated because they are produced using elevation‐sensitive interpolations. The results reinforce the importance of downscaling coarse‐grained (∼50 km) temperature surfaces, and suggest that the accuracy of this process could be improved by considering regional weather patterns (wind speed, direction, humidity) and topographic exposure to key wind directions.     

关于氮有效性影响细根生产量和周转率的四个假说

在全球变化如氮沉降及温度升高等可能导致土壤氮有效性增加的背景下,细根动态如何变化一直是陆地生态学研究中的一个重要内容.本文综述了前人提出的细根动态响应土壤N有效性提高的4个代表性假说:1)细根生产量和周转率都提高;2)细根生产量和周转率都下降;3)细根生产量下降,周转率提高;4)细根生产量提高,周转率下降.根据2000年以来以微根管方法为主测得的根系动态数据,笔者认为假说1)和假说2)得到的支持最为充分.此外,还探讨了树种、细根异质性、菌根真菌、细根采样方法和施肥方法等对上述各假说检验的影响.     

四种不同生活型树种细根寿命及影响因素

以4种不同生活型树种(常绿阔叶和针叶树种、落叶阔叶和针叶树种)为研究对象,通过微根管法现地观测细根的生长动态,比较不同生活型树种细根寿命在种内和种间的差异,探讨影响细根寿命的主要因子,研究结果对理解和预测森林生态系统碳及养分循环过程具有重要的理论意义。结果表明:(1)细根形态特征(分枝结构和直径)显著影响种内细根寿命,分枝等级越低、直径越小,细根的寿命越短;(2)4个树种的细根寿命表现出明显的土层效应和季节效应,即随土壤深度增加,细根的累积存活率逐渐增加,寿命延长;而不同季节出生的细根其寿命长短模式在树种间不一致,春季或夏季出生的细根寿命要长于秋冬季;(3)常绿树种(柳杉、石栎)的细根寿命要长于落叶树种(池杉、麻栎),同时,针叶树种(池杉、柳杉)的细根寿命要长于阔叶树种(麻栎、石栎)。在同一树种内,细根寿命受细根直径、根系分枝结构、土壤环境因子(土层)等因素显著影响,但在不同树种间,细根寿命可能更依赖于树木生长速率、碳分配模式等树木整体的功能性状差异。     

Protecting rare and endangered species under climate change on the Qinghai Plateau,China

Climate change‐induced species range shift may pose severe challenges to species conservation. The Qinghai‐Tibet Plateau is the highest and biggest plateau, and also one of the most sensitive areas to global warming in the world, which provides important shelters for a unique assemblage of species. Here, ecological niche‐based model was employed to project the potential distributions of 59 key rare and endangered species under three climate change scenarios (RCP2.6, RCP4.5 and RCP8.5) in Qinghai Province. I assessed the potential impacts of climate change on these key species (habitats, species richness and turnover) and effectiveness of nature reserves (NRs) in protecting these species. The results revealed that that climate change would shrink the geographic ranges of about a third studied species and expand the habitats for two thirds of these species, which would thus alter the conservation value of some local areas and conservation effectiveness of some NRs in Qinghai Province. Some regions require special attention as they are expected to experience significant changes in species turnover, species richness or newly colonized species in the future, including Haidong, Haibei and Haixi junctions, the southwestern Yushu, Qinghai Nuomuhong Provincial NR, Qinghai Qaidam and Haloxylon Forest NR. The Haidong and the eastern part of Haibei, are projected to have high species richness and conservation value in both current and future, but they are currently not protected, and thus require extra protection in the future. The results could provide the first basis on the high latitude region to formulate biodiversity conservation strategies on climate change adaptation.     

Predicting fine root lifespan from plant functional traits in temperate trees

? Although linkages of leaf and whole-plant traits to leaf lifespan have been rigorously investigated, there is a limited understanding of similar linkages of whole-plant and fine root traits to root lifespan. In comparisons across species, do suites of traits found in leaves also exist for roots, and can these traits be used to predict root lifespan? ? We observed the fine root lifespan of 12 temperate tree species using minirhizotrons in a common garden and compared their median lifespans with fine-root and whole-plant traits. We then determined which set of combined traits would be most useful in predicting patterns of root lifespan. ? Median root lifespan ranged widely among species (95-336?d). Root diameter, calcium content, and tree wood density were positively related to root lifespan, whereas specific root length, nitrogen (N)?:?carbon (C) ratio, and plant growth rate were negatively related to root lifespan. Root diameter and plant growth rate, together (R(2) =?0.62) or in combination with root N?:?C ratio (R(2) =?0.76), were useful predictors of root lifespan across the 12 species. ? Our results highlight linkages between fine root lifespan in temperate trees and plant functional traits that may reduce uncertainty in predictions of root lifespan or turnover across species at broader spatial scales.