Predicting the distribution of four species of raptors (Aves: Accipitridae) in southern Spain: statistical models work better than existing maps

Aim To test the effectiveness of statistical models based on explanatory environmental variables vs. existing distribution information (maps and breeding atlas), for predicting the distribution of four species of raptors (family Accipitridae): common buzzard Buteo buteo (Linnaeus, 1758), short‐toed eagle Circaetus gallicus (Gmelin, 1788), booted eagle Hieraaetus pennatus (Gmelin, 1788) and black kite Milvus migrans (Boddaert, 1783). Location Andalusia, southern Spain. Methods Generalized linear models of 10 × 10 km squares surveyed for the presence/absence of the species by road census. Statistical models use as predictors variables derived from topography, vegetation and land‐use, and the geographical coordinates (to take account of possible spatial trends). Predictions from the models are compared with current distribution maps from the national breeding atlas and leading reference works. Results The maps derived from statistical models for all four species were more predictive than the previously published range maps and the recent national breeding atlas. The best models incorporated both topographic and vegetation and land‐use variables. Further, in three of the four species the inclusion of spatial coordinates to account for neighbourhood effects improved these models. Models for the common buzzard and black kite were highly predictive and easy to interpret from an ecological point of view, while models for short‐toed eagle and, particularly, booted eagle were not so easy to interpret, but still predicted better than previous distribution information. Main conclusions It is possible to build accurate predictive models for raptor distribution with a limited field survey using as predictors environmental variables derived from digital maps. These models integrated in a geographical information system produced distribution maps that were more accurate than previously published ones for the study species in the study area. Our study is an example of a methodology that could be used for many taxa and areas to improve unreliable distribution information.     

Quantitative prediction of the distribution and abundance of Vaccinium myrtillus with climatic and edaphic factors

Question: Can the distribution and abundance of Vaccinium myrtillus be reasonably predicted with soil nutritional and climatic factors? Location: Forests of France. Methods: We used Braun‐Blanquet abundance/dominance information for Vaccinium myrtillus on 2905 forest sites extracted from the phyto‐ecological database EcoPlant, to characterize the species ecological response to climatic and edaphic factors and to predict its cover/abundance at the national scale. The link between cover/abundance of the species and climatic (65 monthly and annual predictors concerning temperature, precipitation, radiation, potential evapotranspiration, water balance) and edaphic (two predictors: soil pH and C:N ratio) factors was investigated with proportional odds models. We evaluated the quality of our model with 9830 independent relevés extracted from Sophy, a large phytosociological database for France. Results: In France, Vaccinium myrtillus is at the southern limit of its European geographic range and three environmental factors (mean annual temperature, soil pH and C:N ratio) allow prediction of its distribution and abundance in forests with high success rates. The species reveals a preference for colder sites (especially mountains) and nutritionally poor soils (low pH and high C:N ratio). A predictive map of its geographic range reveals that the main potential habitats are mountains and northwestern France. The potential habitats with maximal expected abundance are the Vosges and the Massif central mountains, which are both acidic mountains. Conclusions: Complete niche models including climate and soil nutritional conditions allow an improvement of the spatial prediction of plant species abundance at a broad scale. The use of soil nutritional variables in distribution models further leads to an improvement in the prediction of plant species habitats within their geographical range.     

黄土残塬沟壑区流域次生植被物种分布的地形响应

研究流域次生植被物种对地形因子的响应规律,识别影响次生植被物种分布的主要地形因子,是流域近自然植被生态恢复和重建的基础。采用ArcGIS空间分析模块和地形分析模块TauDEM,并与统计软件SPLUS2000中的GRASP工具相结合,建立了位于黄土高原残垣沟壑区山西省吉县蔡家川流域次生植被各个物种分布基于地形因子的广义相加模型(GAM)。模型中的地形因子包括:海拔、坡向、坡度、平面曲率、坡位指数(SPI)、地形湿度指数(TWI)、单宽汇水面积(SCA)等。受试者操作特征曲线(ROC)测试中AUC值表明:大部分测试物种(约62%)拟合模型效果较好,且模型较为稳定。总体来看,研究流域次生植被物种分布体现了水分限制的空间分异特征:阴坡各物种分布概率较大,且随海拔升高而减小。影响研究流域次生植被物种空间分布的潜在重要因子为海拔和坡向,而单宽汇水面积(SCA)和地形湿度指数(TWI)虽然是多个物种响应模型的预测因子,但受高一级尺度海拔的影响,SCA与TWI对物种分布的影响作用较小;坡度影响作用最小。据此,在流域植被恢复和防护林建设目标区选择及立地条件划分时应首先以海拔和坡向为依据,单宽汇水面积(SCA)和地形湿度指数(TWI)则可以作为次一级立地分类依据,而坡度则仅能作为最后一级的分类依据。     

Modelling the recent and potential future spatial distribution of the Ring Ouzel (Turdus torquatus) and Blackbird (T. merula) in Switzerland

We present here a multiscale modelling approach to predict the current and future spatial distribution of Ring Ouzel (Turdus torquatus) and Blackbird (T. merula) in Switzerland. Species distribution models (SDMs) are applied on three different scales in order to analyse the scale-dependency of predictors that describe the species’ realised niche. While the models on the macro- and mesoscales (grid of 100 and 1 km², respectively) cover the entire country, our small-scale models are based on a small set of territories. Ring Ouzels occur at altitudes above 1000 m a.s.l. only, while Blackbirds occur from the lowlands up to the timberline. Although both species coexist on the macro- and mesoscales, a direct niche overlap on territory scale is rare. Small-scale differences in vegetation cover and structure seem to play a dominant role in habitat selection. On the macroscale, however, we observed a high dependency on bioclimatic variables that mainly represent the altitudinal range and the related forest structure preferred by both species. Applying the models to climate change scenarios, we predict a decline of suitable habitat for the Ring Ouzel with a simultaneous median altitudinal shift of 440 m until 2070. In contrast, the Blackbird is predicted to benefit from higher temperatures and expand its range to higher elevations. Based on the species distribution models we (1) demonstrate the scale-dependency of environmental predictors, (2) quantify the scale-dependent habitat requirements of Blackbird and Ring Ouzel and (3) predict the altitudinal range shift of both species as related to climate change scenarios.     

Nesting preferences of the threatened wood ant <Emphasis Type="Italic">Formica exsecta</Emphasis> (Hymenoptera: Formicidae); implications for conservation in Scotland

Wood ants are a dominant and ecologically important component of northern coniferous forests with interactions at many trophic levels. Each species exhibits specific habitat preferences which need to be understood if conservation measures are to be successful. In Britain, the rare narrow-headed ant Formica exsecta has disappeared from much of its former range and is now largely restricted to the highlands of Scotland where it is found in open canopy woodland and along forest edges. Nest locale of one small and vulnerable population at the edge of its current range, were compared with those of random locations within the same habitat and with actual nests within the stronghold of the Abernethy-Glenmore complex in Strathspey. After data exploration with Redundancy Analysis, stepwise multiple regression was used to create a model which best estimated the variance in nest location using a parsimonious selection of vegetation and environmental variables. The input variables included were light, soil moisture, altitude, tree stature and distribution, vegetation structure and composition, and ground characteristics. F. exsecta clearly exhibited preferences for the position of nest mounds in relation to light, vegetation and tree cover. Forest location was also important in determining which variables nests were affected by. This study highlights the importance of maintaining a dynamic mosaic of different-aged woodland enabling early successional species such as F. exsecta, with suitable areas to move to as conditions change and allowing the co-existence of all wood ant species.     

贺兰山西坡啮齿动物生境选择及种间关系

为明确对贺兰山西坡啮齿动物生境选择起关键作用的主要环境因子,探讨各鼠种之间的相互作用如何影响鼠种的生境选择,选取地理因子（海拔、坡度、坡向）、植被因子（植被盖度、植被高度、灌木/乔木高度）和其他因子（距水源距离、距道路距离、距灌木/乔木距离）等9种生境因子,利用资源选择函数模型和logistic回归模型对啮齿动物生境选择和种间关系进行分析。结果表明,在贺兰山西坡,捕获数量最多的6种啮齿动物对的生境选择存在差异,大林姬鼠（Apodemus peninsulae）偏好高海拔、多灌木（乔木）的生境;子午沙鼠（Meriones meridianus）偏好海拔较低的半荒漠稀疏生境,对道路和人为干扰不回避;灰仓鼠（Cricetulus migratorius）偏好距水源较远、多灌木（乔木）、距道路较近的生境;阿拉善黄鼠（Spermophilus alaschanicus）偏好低海拔、植被丰富的生境;短尾仓鼠（Cricetulus eversmanni）偏好高海拔、距道路较近的生境;社鼠（Niviventer niviventer）偏好海拔较高、坡度较大、距水源较远的生境。鼠种间的相互关系主要呈现回避或随机关系。研究结果有助于了解啮齿动物分布的变化及种群动态规律,可为贺兰山生物资源保护,区域性鼠害的预测、预报和综合治理提供基础资料和科学依据。     

Modelling breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus) in relation to topography, disturbance, climate and land use at different spatial scales

Predictive models on breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus; Aves: Accipitridae) have been performed at four different spatial scales in Castellón province, East of Iberian Peninsula. The scales considered were: (1) nest site scale (1×1 km² Universal Transverse Mercator (UTM) square containing the nest); (2) near nest environment (3×3 km² UTM square); (3) home range scale (5×5 km² UTM square); and (4) landscape level scale (9×9 km² UTM square containing the above mentioned ones). Topographic, disturbance, climatic and land use factors were measured on a geographic information system (GIS) at occupied and unoccupied UTM squares. Logistic regression was performed by means of a stepwise addition procedure. We tested whether inclusion of new subset of variables improved the models by increasing the area under the receiver operator characteristic plot. At nest site scale, only topographic factors were considered as the most parsimonious predictors. Probability of species occurrence increases with slope in craggy areas at lower altitudes. At the 3×3 km² scale, climate and disturbance variables were included. At home range and landscape level scales, models included climate, disturbance, topographic and land use factors. Higher temperatures in January, template ones in July, higher rainfall in June, lower altitudes and higher slope in the sample unit increase probability of occurrence of Bonelli’s eagle at broadest scales. The species seems to prefer disperse forests, scrubland and agricultural areas. From our results, we consider that there is a hierarchical framework on habitat selection procedure. We suggest that it is necessary to analyse what key factors are affecting Bonelli’s eagle nest-site selection at every study area to take steps to ensure appropriate conservation measures. The combination of regression modelling and GIS will become a powerful tool for biodiversity and conservation studies, taking into account that application depends on sampling design and the model assumptions of the statistical methods employed. Finally, predictive models obtained could be used for the efficient monitoring of this scarce species, to predict range expansions or identify suitable locations for reintroductions, and also to design protected areas and to help on wildlife management.     

Environmental responses of Pinus ponderosa and associated species in the south-western USA

Abstract Aim We addressed four objectives: (1) Determine the regional responses of species, size classes and a vegetation type to climate and parent material predictors, including their distributions in environmental space and the relative contributions of the predictors to explained variation. (2) Determine whether size classes of a species respond similarly to climate and parent material. (3) Assess the extent to which the predicted regional distribution of a vegetation type can be approximated by the distribution of its diagnostic species and vice versa. The establishment of a consistent relationship between the distribution of a vegetation type and its diagnostic species would facilitate change detection, management and conservation planning by allowing the use of one distribution to generate the other when data availability is limited. (4) Examine landscape‐scale environmental variability in predicted species and vegetation type distributions. Location South‐western USA (Arizona, New Mexico and southern Colorado). Methods Ecological response surface models were developed using a data base of 1409 vegetation plots to analyse biotic–environmental relationships of (1) Pinus ponderosa P. & C. Lawson and Abies concolor (Gord. & Glend.) Lindl. Ex Hildebr. size classes, (2) P. ponderosa, A. concolor and Quercus gambelii Nutt. combined size classes, and (3) a P. ponderosa forest type widely distributed in the south‐western USA. Results and main conclusions Pinus ponderosa and A. concolor models generally were judged to be successful. Quercus gambelii models were judged unsuccessful, which may result from the influence of variables not modelled, such as soil moisture, disturbance, biotic factors and other site limiting factors. Size classes differed in the range of environmental conditions associated with high occurrence probabilities within and between species, reflecting differences in the effects of climate variability and anthropogenic changes, such as fire suppression, on the distribution of each size class. Pinus ponderosa alliance was predicted to be distributed over a narrower range of environmental conditions than P. ponderosa species models, therefore limiting the use of this vegetation type as a surrogate for the distribution of the dominant species, and vice versa. Maps of combinations of environmental variables that produced a high probability of P. ponderosa occurrence showed that some landscapes predicted to contain the species exhibited diverse environmental conditions over short distances. The use of regional environmental relationships to characterize areas with high local environmental variability may facilitate identification of areas of potential rapid biotic change.     

Predicting reptile distributions at the mesoscale: relation to climate and topography

Aim To explore the respective power of climate and topography to predict the distribution of reptiles in Switzerland, hence at a mesoscale level. A more detailed knowledge of these relationships, in combination with maps of the potential distribution derived from the models, is a valuable contribution to the design of conservation strategies. Location All of Switzerland. Methods Generalized linear models are used to derive predictive habitat distribution models from eco‐geographical predictors in a geographical information system, using species data from a field survey conducted between 1980 and 1999. Results The maximum amount of deviance explained by climatic models is 65%, and 50% by topographical models. Low values were obtained with both sets of predictors for three species that are widely distributed in all parts of the country (Anguis fragilis, Coronella austriaca, and Natrix natrix), a result that suggests that including other important predictors, such as resources, should improve the models in further studies. With respect to topographical predictors, low values were also obtained for two species where we anticipated a strong response to aspect and slope, Podarcis muralis and Vipera aspis. Main conclusions Overall, both models and maps derived from climatic predictors more closely match the actual reptile distributions than those based on topography. These results suggest that the distributional limits of reptile species with a restricted range in Switzerland are largely set by climatic, predominantly temperature‐related, factors.     

Establishing species' environmental requirements to understand how the southernmost species of South American pitvipers (Bothrops,Viperidae) are distributed: A niche‐based modelling approach

Three Bothrops species are known to be present along an extensive and generally xeric band of the south‐eastern portion of South America. Yet, the environmental factors responsible for the maintenance of the structure of this community have remained undetermined. To have a better understanding of snakes' geographic range limits in Argentina, we modelled the ecological niche of Bothrops alternatus, B. ammodytoides and B. diporus to identify areas of their occurrence and sympatry. We used snakes presence records and pseudo‐absence data with topographic (altitude and slope), vegetation and 19 bioclimatic variables as predictors. These variables were evaluated for each species, using Multiple Logistic Regression Analysis. The distribution of B. alternatus was correlated with temperature, precipitation and vegetation; that of B. ammodytoides with altitude, slope, precipitation, temperature and vegetation; and that of B. diporus related only to precipitation and temperature variables. Five variables appeared in all three models (i.e. annual precipitation, precipitation seasonality, precipitation of the driest month, mean diurnal temperature range and temperature range), although with different effects in different species. Probable sympatry areas were identified, for B. alternatus – B. ammodytoides in a narrow area, for B. diporus – B. alternatus in a wide area and B. ammodytoides – B. diporus in a small area. While some factors constrain the distribution of the southernmost pitvipers community in South America to spatially non‐overlapping ranges, others facilitate sympatry by allowing spatial coexistence. We found high sympatry between phylogenetically distantly related pitvipers. Niche‐based Geographic Information Systems modelling allowed us to identify the environmental factors correlated with each pitviper range in Argentina and in its contact zones, and to understand species distributional limits.     

Commercially Important Trees as Invasive Aliens – Towards Spatially Explicit Risk Assessment at a National Scale

Alien species that are desirable and commercially important in parts of the landscape, but damaging invaders in other parts, present a special challenge for managers, planners, and policy-makers. Objective methods are needed for identifying areas where control measures should be focussed. We analysed the distribution of forestry plantations and invasive (self-sown) stands of Acacia mearnsii and Pinus spp. in South Africa; these two taxa account for 60% of the area under commercial plantations and 54% of the area invaded by alien trees and shrubs. The distribution of commercial forestry plantations and invasive stands of these taxa were mapped and the data was digitised and stored as Geographic Information System (GIS) (Arc/Info) layers. A series of environmental parameters were derived from GIS layers of climate, topography, geology, land use, and natural vegetation. The current distribution of the two taxa was subdivided into three groups according to the degree of invasion, planting history and the precision of the data collection. We used regression-tree analysis to relate, for each taxon, the distribution of invasive stands with environmental variables, and to derive habitat suitability maps for future invasion. The current distribution of invasive stands in South Africa was largely influenced by climatic factors. At a national scale, the distribution of large commercial plantations was a poor predictor of areas invaded by both taxa. Using environmental factors identified by the regression trees, we found that 6.6% and 9.8% of natural habitats currently not invaded and untransformed by urbanisation or agriculture are suitable for invasion by Pinus spp. and A. mearnsii, respectively. We then derived guidelines for policy on alien plant management based on vegetation type, degree of transformation, extent of invasion, and the risk of future alien spread. These factors were used to identify demarcated areas where these alien species can be grown with little risk of invasions, and areas where special measures are needed to manage spread from plantations.     

Lizard species richness patterns in China and its environmental associations

Many ecological hypotheses have been widely used to explain species richness variation across the globe. We investigated lizard species richness patterns in China, and identified areas of high species richness. Furthermore, we tested hypotheses concerning the relationships between lizard richness and environmental variables. A large data including 30,902 records of point locality data for 151 lizard species occurring in China were retrieved from Herpetology museums of CIB/CAS and other museums through HerpNET, and published sources, and then predicted distributions maps were generated using ecological niche modeling. We overlaid all species prediction maps into a composite map to describe species richness patterns. A multiple regression analysis using eigenvector-based spatial filtering (SEVM) was performed to examine the best environmental predictors of species richness. Richness peaked mainly in southern China located in the Oriental realm. Our best multiple regression models explained a total of 80.1% variance of lizard richness (r² = 0.801; F = 203.47; P < 0.001). Among related factors in shaping species richness distribution, the best environmental predictors of species richness were: frost-day frequency, elevation, vegetation, and wet-day frequency. Based on models selection, our results revealed that underlying mechanisms related to different ecological hypotheses might work together and best explain lizard richness in China. We are in an initial step to develop a large data set on species richness, and provide the necessary conservation implications from habitat loss. Additional studies that test species richness at different geographical scale are required to better understand the factors that may influence the species richness distribution in East Asia.     

Reconstructing range dynamics and range fragmentation of European bison for the last 8000 years

Aim Understanding what constituted species’ ranges prior to large‐scale human influence, and how past climate and land use change have affected range dynamics, provides conservation planners with important insights into how species may respond to future environmental change. Our aim here was to reconstruct the Holocene range of European bison (Bison bonasus) by combining a time‐calibrated species distribution models (SDM) with a dynamic vegetation model. Location Europe. Method We used European bison occurrences from the Holocene in a maximum entropy model to assess bison range dynamics during the last 8000 years. As predictors, we used bioclimatic variables and vegetation reconstructions from the generalized dynamic vegetation model LPJ‐GUESS. We compared our range maps with maps of farmland and human population expansion to identify the main species range constraints. Results The Holocene distribution of European bison was mainly determined by vegetation patterns, with bison thriving in both broadleaved and coniferous forests, as well as by mean winter temperature. The heartland of European bison was in Central and Eastern Europe, whereas suitable habitat in Western Europe was scarce. While environmentally suitable regions were overall stable, the expansion of settlements and farming severely diminished available habitat. Main conclusions European bison habitat preferences may be wider than previously assumed, and our results suggest that the species had a more eastern and northern distribution than previously reported. Vegetation and climate transformation during the Holocene did not affect the bison’s range substantially. Conversely, human population growth and the spread of farming resulted in drastic bison habitat loss and fragmentation, likely reaching a tipping point during the last 1000 years. Combining SDM and dynamic vegetation models can improve range reconstructions and projections, and thus help to identify resilient conservation strategies for endangered species.     

Weak climatic associations among British plant distributions

Aim Species distribution models (SDMs) are used to infer niche responses and predict climate change‐induced range shifts. However, their power to distinguish real and chance associations between spatially autocorrelated distribution and environmental data at continental scales has been questioned. Here this is investigated at a regional (10 km) scale by modelling the distributions of 100 plant species native to the UK. Location UK. Methods SDMs fitted using real climate data were compared with those utilizing simulated climate gradients. The simulated gradients preserve the exact values and spatial structure of the real ones, but have no causal relationships with any species and so represent an appropriate null model. SDMs were fitted as generalized linear models (GLMs) or by the Random Forest machine‐learning algorithm and were either non‐spatial or included spatially explicit trend surfaces or autocovariates as predictors. Results Species distributions were significantly but erroneously related to the simulated gradients in 86% of cases (P < 0.05 in likelihood‐ratio tests of GLMs), with the highest error for strongly autocorrelated species and gradients and when species occupied 50% of sites. Even more false effects were found when curvilinear responses were modelled, and this was not adequately mitigated in the spatially explicit models. Non‐spatial SDMs based on simulated climate data suggested that 70–80% of the apparent explanatory power of the real data could be attributable to its spatial structure. Furthermore, the niche component of spatially explicit SDMs did not significantly contribute to model fit in most species. Main conclusions Spatial structure in the climate, rather than functional relationships with species distributions, may account for much of the apparent fit and predictive power of SDMs. Failure to account for this means that the evidence for climatic limitation of species distributions may have been overstated. As such, predicted regional‐ and national‐scale impacts of climate change based on the analysis of static distribution snapshots will require re‐evaluation.     

Polymorphic microsatellite DNA markers in the ant Formica exsecta

Highly polymorphic genetic markers provide a useful tool for estimating important genetic parameters in studies of the evolution of sociality in insects. Here we report 14 polymorphic microsatellite markers developed in the ant Formica exsecta. The number of alleles found ranged between 3 and 18 per locus. These markers were developed for studying genetic population structure and mating structure in F. exsecta populations with varying social organizations (monogyne and polygyne types of societies). Cross‐species amplification indicated that some of the markers might be usable even in species belonging to different subfamilies.     

Impact of Formica exsecta Nyl. on seed bank and vegetation patterns in a subalpine grassland ecosystem

The mound building ant Formica exsecta Nyl. is widely distributed in grassland ecosystems of the Central European Alps. We studied the impact of these ants on seed bank and vegetation patterns in a 11 ha subalpine grassland, where we counted over 700 active ant mounds. The mounds showed a distinct spatial distribution with most of them being located in tall‐grass, which was rarely visited by ungulates (red deer; Cervus elaphus L.). Heavily grazed short‐grass, in contrast, seemed to be completely avoided by ants as only few mounds were found in this vegetation type. The species composition of the ant mound and grassland seed banks was quite similar, i.e. from 15 common plant species 12 were found in both seed bank types. We found the same proportions of myrmecochorous seeds in ant mound and grassland soil samples. In contrast, the number of seeds was 15 times higher in mound compared with the grassland soil samples. Also, the vegetation growing on ant mounds significantly differed from the vegetation outside the mounds: graminoids dominated on ant mounds, herbaceous and myrmecochorous species in the grassland vegetation. We found significant continuous changes in vegetation composition on gradients from the ant mound centre to 1 m away from the mound edge. Overall, F. exsecta was found to have a considerable impact on seed bank and vegetation patterns in the grassland ecosystem studied. These insects not only altered grassland characteristics in the close surrounding of their mounds, but also seem to affect the entire ecosystem including, for example, the spatial use of the grassland by red deer.     

The influence of non‐climate predictors at local and landscape resolutions depends on the autecology of the species

Species distribution models have come under criticism for being too simplistic for making robust future forecasts, partly because they assume that climate is the main determinant of geographical range at large spatial extents and coarse resolutions, with non‐climate predictors being important only at finer scales. We suggest that this paradigm might be obscured by species movement patterns. To explore this we used contrasting kangaroo (family Macropodidae) case studies: two species with relatively small, stable home ranges (Macropus giganteus and M. robustus) and three species with more extensive, adaptive ranging behaviour (M. antilopinus, M. fuliginosus and M. rufus). We predicted that non‐climate predictors will be most influential to model fit and predictive performance at local spatial resolution for the former species and at landscape resolution for the latter species. We compared residuals autocovariate – boosted regression tree (RAC‐BRT) model statistics with and without species‐specific non‐climate predictors (habitat, soil, fire, water and topography), at local‐ and landscape‐level spatial resolutions (5 and 50 km). As predicted, the influence of non‐climate predictors on model fit and predictive performance (compared with climate‐only models) was greater at 50 compared with 5 km resolution for M. rufus and M. fuliginosus and the opposite trend was observed for M. giganteus. The results for M. robustus and M. antilopinus were inconclusive. Also notable was the difference in inter‐scale importance of climate predictors in the presence of non‐climate predictors. In conclusion, differences in autecology, particularly relating to space use, may contribute to the importance of non‐climate predictors at a given scale, not model scale per se. Further exploration of this concept across a range of species is encouraged and findings may contribute to more effective conservation and management of species at ecologically meaningful scales.     

山西太岳山小流域土壤水分空间异质性及其影响因子

以山西太岳山华北落叶松林地为主的小流域作为研究对象,采用地统计学方法结合地理信息系统(GIS)技术手段,研究了接石沟小流域土壤水分(0—60cm)的空间变异特征,以及植被分布和地形因子对其影响规律。结果表明:在时间稳定性的前提下,土壤水分含量和变异系数随土层加深逐渐降低。三层土壤水分半方差函数的最优拟合模型为球状模型,变程范围在1.1—1.4 km,均具有强烈的空间自相关性,其中0—20 cm和20—40 cm层土壤水分的空间异质性程度高于40—60 cm土层,以中间层的结构因素占总变异比例最大。自然结构因素(地形、母质、植被和土壤等)对不同土层土壤水分的总空间变异性起主导作用(81.4%—91.3%),而随机因素(取样误差、人为干扰等)的影响相对较小(8.7%—18.6%)。沿着集水线由西-东方向,从边缘的土壤水分高值斑块区逐渐过渡到明显的低值斑块区,梯度变化明显。研究发现,在植被覆盖异质性小的山地,土壤水分的空间异质性主要由地形因素引起,具体表现为其与坡向指数(TRASP)、坡度、海拔和土壤有机碳、全氮呈极显著相关关系(P0.01),而与植被指数(NDVI)呈弱的负相关关系。叠加分析显示,在阴坡、坡度较缓(15°)及高海拔叠合的区域土壤水分含量较高。研究结果可为山地人工林构建和植被恢复中土壤水资源的利用以及水分管理策略的制定提供理论依据。     

Vegetation structure and ground cover attributes describe the occurrence of a newly discovered carnivorous marsupial on the Tweed Shield Volcano caldera,the endangered black‐tailed dusky antechinus (Antechinus arktos)

The black‐tailed dusky antechinus (Antechinus arktos) is a recently discovered, endangered, carnivorous marsupial mammal endemic to the Tweed Shield Volcano caldera, straddling the border between Queensland and New South Wales in eastern Australia. The species' preference for cool, high‐altitude habitats makes it particularly vulnerable to a shifting climate as these habitats recede. Aside from basic breeding and dietary patterns, the species' ecology is largely unknown. Understanding fine‐scale habitat attributes preferred by this endangered mammal is critical to employ successful conservation management. Here, we assess vegetation attributes of known habitats over three sites at Springbrook and Border Ranges National Parks, including detailed structure data and broad floristic assessment. Floristic compositional assessment of the high‐altitude cloud rainforest indicated broad similarities. However, only 22% of plant species were shared between all sites indicating a high level of local endemism. This suggests a diverse assemblage of vegetation across A. arktos habitats. Habitat characteristics were related to capture records of A. arktos to determine potential fine‐scale structural habitat requirements. Percentage of rock cover and leaf litter were the strongest predictors of A. arktos captures across survey sites, suggesting a need for foraging substrate and cover. Habitat characteristics described here will inform predictive species distribution models of this federally endangered species and are applicable to other mammal conservation programs.     

Predictive Mapping of Species Richness and Plant Species' Distributions of a Peruvian Fog Oasis Along an Altitudinal Gradient

Tropical arid to semi‐arid ecosystems are nearly as diverse as more humid forests and occupy large parts of the tropics. In comparison, however, they are vastly understudied. For instance, fog precipitation alone supports a unique vegetation formation, locally termed lomas, on coastal mountains in the Peruvian desert. To effectively protect these highly endemic and threatened ecosystems, we must increase our understanding of their diversity patterns in relation to environmental factors. Consequently, we recorded all vascular species from 100 random 4 × 4 m plots on the fog‐exposed southern slope of the mountain Mongón. We used topographic and remotely sensed covariates in statistical models to generate spatial predictions of alpha diversity and plant species' distribution probabilities. Altitude was the most important predictor in all models and may represent fog moisture levels. Other significant covariates in the models most likely refer also to water availability but on a finer spatial scale. Additionally, model‐based clustering revealed five altitudinal vegetation zones. This study contributes to a better spatial understanding of the biodiversity and spatial arrangement of vegetation belts of the largely unknown but highly unique lomas formations. Furthermore, mapping species richness and plant species' distributions could support a long‐needed lomas strategic conservation scheme.