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1.
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.  相似文献   

2.
Previous research focusing on broad‐scale or geographically invariant species‐environment dependencies suggest that temperature‐related variables explain more of the variation in reptile distributions than precipitation. However, species–environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad‐scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile–climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national‐scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r2 = 0.05, < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r2 = 0.65, < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local‐scale analyses.  相似文献   

3.
Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors—a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90‐m digital‐elevation model by using the GRASS‐GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km2. We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land‐use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1–93.2 and 0.61–0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can have consistently high evaluation scores while mapped predictions differ significantly and are highly contingent on the underlying subcatchment size. We encourage building freshwater SDMs across multiple catchment sizes, to assess model variability and uncertainties in model outcomes emerging from the MAUP.  相似文献   

4.
Knowledge of the ecological requirements determining tree species distributions is a precondition for sustainable forest management. At present, the abiotic requirements and the relative importance of the different abiotic factors are still unclear for many temperate tree species. We therefore investigated the relative importance of climatic and edaphic factors for the abundance of 12 temperate tree species along environmental gradients. Our investigations are based on data from 1,075 forest stands across Switzerland including the cold‐induced tree line of all studied species and the drought‐induced range boundaries of several species. Four climatic and four edaphic predictors represented the important growth factors temperature, water supply, nutrient availability, and soil aeration. The climatic predictors were derived from the meteorological network of MeteoSwiss, and the edaphic predictors were available from soil profiles. Species cover abundances were recorded in field surveys. The explanatory power of the predictors was assessed by variation partitioning analyses with generalized linear models. For six of the 12 species, edaphic predictors were more important than climatic predictors in shaping species distribution. Over all species, abundances depended mainly on nutrient availability, followed by temperature, water supply, and soil aeration. The often co‐occurring species responded similar to these growth factors. Drought turned out to be a determinant of the lower range boundary for some species. We conclude that over all 12 studied tree species, soil properties were more important than climate variables in shaping tree species distribution. The inclusion of appropriate soil variables in species distribution models allowed to better explain species' ecological niches. Moreover, our study revealed that the ecological requirements of tree species assessed in local field studies and in experiments are valid at larger scales across Switzerland.  相似文献   

5.
For millennia, locust swarms have recurrently devastated crop productivity across continents. In much of Europe, locust outbreaks have been considerably reduced by human pressure in recent decades, but important foci of outbreaks still exist in Spain. Distribution models are often used to derive spatial hypotheses and risk maps. Because insufficient information is available to include the extreme plasticity of the solitary and gregarious phases of locusts in large‐scale spatial models, we modelled the distribution either of Acrididae species or of outbreaks per se. Confirmed occurrences of Dociostaurus, Calliptamus and Chorthippus species were obtained from a field survey complemented by museum collection data and the published literature. The locations of confirmed or potential outbreaks covering two time periods of 20 years each were obtained from the literature and from Spanish autonomous community reports. Models were built with one topographic and eleven climatic predictors. We evaluated the ability of different models to predict outbreak recurrence and found that models based on Moroccan locust data or outbreak occurrence data performed the best. We generated a predictive map of the climatic favourability for locust outbreaks in Spain and found that the major foci of locust swarms were encompassed by those areas categorized by the models as areas of highest risk. Predictive maps of outbreak favourability can facilitate the more sustainable use of insecticides and more efficient integrated pest management.  相似文献   

6.
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we propose to derive environmental data layers by mapping ecological indicator values in space. We combined ~6 million plant occurrences with expert-based plant ecological indicator values (EIVs) of 3600 species in Switzerland. EIVs representing local soil properties (pH, moisture, moisture variability, aeration, humus and nutrients) and climatic conditions (continentality, light) were modelled at 93 m spatial resolution with the Random Forest algorithm and 16 predictors representing meso-climate, land use, topography and geology. Models were evaluated and predictions of EIVs were compared with soil inventory data. We mapped each EIV separately and evaluated EIV importance in explaining the distribution of 500 plant species using SDMs with a set of 30 environmental predictors. Finally, we tested how they improve an ensemble of SDMs compared to a standard set of predictors for ca 60 plant species. All EIV models showed excellent performance (|r| > 0.9) and predictions were correlated reasonably (|r| > 0.4) to soil properties measured in the field. Resulting EIV maps were among the most important predictors in SDMs. Also, in ensemble SDMs overall predictive performance increased, mainly through improved model specificity reducing species range overestimation. Combining large citizen science databases to expert-based EIVs is a powerful and cost–effective approach for generalizing local edaphic and climatic conditions over large areas. Producing ecologically meaningful predictors is a first step for generating better predictions of species distribution which is of main importance for decision makers in conservation and environmental management projects.  相似文献   

7.
Aim Soil nutrient content plays a key role in plant growth through mineral nutrition and toxicity. Its impact on plant species and community distribution is studied on a large geographical scale through surrogates like topography or geology. We investigated the importance of soil pH and C:N ratio, as direct nutritional gradients, to determine, with climatic factors, the spatial distribution of plant communities over large territories. Location We studied the distribution of six beech habitats of the NATURA 2000 network throughout France (550,000 km2). Methods Models were calibrated with 2108 floristic plots classified in the NATURA 2000 system and including climatic and topographic variables and soil nutritional measurements carried out in a laboratory. Logistic regression was used to model habitat distribution according to environmental variables. Climatic layers, a digital elevation model and maps of soil pH and nitrogen content, created using plant indicator values and large floristic databases, were used to map the sites suitable for beech communities. Distribution models were evaluated with an independent set of 2091 phytosociological plots. Results pH and nitrogen supply were the key distribution drivers for four of the six beech communities on a national scale. Their use in the distribution models distinguished within homogeneous climatic territories a gradient of nutritional conditions from acidic areas, suitable for nutrient‐poor beech communities, to calcareous areas suitable for nutrient‐rich ones. Predicted maps of beech habitats fit the spatial distribution of validation plots. Main conclusions Soil pH and nitrogen supply strongly improve predictions of forest community distribution carried out with climatic variables on a broad geographical scale. They allow delineation of areas with nutritional conditions suitable for each community, as well as the realization of predictive high‐resolution maps over large areas useful for sustainable and conservation management. Nomenclature Tutin & Heywood (2001 ) Flora Europaea. Cambridge University Press, Cambridge.  相似文献   

8.
Aim The transferability of species distribution models requires that species show climatic equilibrium throughout their entire distribution area. We test this assumption for the case of the spotted hyena, Crocuta crocuta, a large carnivore that has shifted its distribution over the last 100,000 years from a widespread Eurasian and African range to its current geographical distribution, restricted to the Sub‐Saharan areas of the African continent. Location Western Eurasia and Africa. Methods The current realized distribution of C. crocuta was estimated using presences and reliable absences as well as climatic, land‐cover and anthropic variables as predictors. The potential distribution was estimated using presences and a set of pseudo‐absences selected from localities outside climatically suitable localities, with only climatic variables serving as predictors. The current potential distribution was transferred to the Last Interglacial period (126,000 yr bp ) using the palaeoclimatic data yielded by the GENESIS 2 general circulation model, and validated with European fossil data. Generalized linear models were used on all occasions. Results Climatic variables are able to predict the current distribution of the species with high accuracy. The geographical projection of this model indicates that the species is distributed over almost all of its potential suitable area, which allows us to suppose that the current distribution of this species is in climatic equilibrium. However, the time transference of model predictions for the western Eurasian region reveals almost no suitable conditions for hyenas, despite the widespread presence of C. crocuta fossil remains on this continent during the Last Interglacial period. Main conclusions Our results indicate that, even when model results suggest a climatic equilibrium for a species distribution, the time transferability of such models does not necessarily provide realistic results. This occurs because the current geographical range does not allow estimations of all of the environmental requirements of a species. Therefore, any model trained with current data risks underestimating the potential suitable environmental and geographical range for species in a new area or time period.  相似文献   

9.
Understanding species–environment relationships is key to defining the spatial structure of species distributions and develop effective conservation plans. However, for many species, this baseline information does not exist. With reliable presence data, spatial models that predict geographic ranges and identify environmental processes regulating distribution are a cost‐effective and rapid method to achieve this. Yet these spatial models are lacking for many rare and threatened species, particularly in tropical regions. The harpy eagle (Harpia harpyja) is a Neotropical forest raptor of conservation concern with a continental distribution across lowland tropical forests in Central and South America. Currently, the harpy eagle faces threats from habitat loss and persecution and is categorized as Near‐Threatened by the International Union for the Conservation of Nature (IUCN). Within a point process modeling (PPM) framework, we use presence‐only occurrences with climatic and topographical predictors to estimate current and past distributions and define environmental requirements using Ecological Niche Factor Analysis. The current PPM prediction had high calibration accuracy (Continuous Boyce Index = 0.838) and was robust to null expectations (pROC ratio = 1.407). Three predictors contributed 96% to the PPM prediction, with Climatic Moisture Index the most important (72.1%), followed by minimum temperature of the warmest month (15.6%) and Terrain Roughness Index (8.3%). Assessing distribution in environmental space confirmed the same predictors explaining distribution, along with precipitation in the wettest month. Our reclassified binary model estimated a current range size 11% smaller than the current IUCN range polygon. Paleoclimatic projections combined with the current model predicted stable climatic refugia in the central Amazon, Guyana, eastern Colombia, and Panama. We propose a data‐driven geographic range to complement the current IUCN range estimate and that despite its continental distribution, this tropical forest raptor is highly specialized to specific environmental requirements.  相似文献   

10.
Aim Because intertidal organisms often live close to their physiological tolerance limits, they are potentially sensitive indicators of climate‐driven changes in the environment. The goals of this study were to assess the effect of climatic and non‐climatic factors on the geographical distribution of intertidal macroalgae, and to predict future distributions under different climate‐warming scenarios. Location North‐western Iberian Peninsula, southern Europe. Methods We developed distribution models for six ecologically important intertidal seaweed species. Occurrence and microhabitat data were sampled at 1‐km2 resolution and analysed with climate variables measured at larger spatial scales. We used generalized linear models and applied the deviance and Bayesian information criterion to model the relationship between environmental variables and the distribution of each target species. We also used hierarchical partitioning (HP) to identify predictor variables with higher independent explanatory power. Results The distributions of Himanthalia elongata and Bifurcaria bifurcata were correlated with measures of terrestrial and marine climate, although in opposite directions. Model projections under two warming scenarios indicated the extinction of the former at a faster rate in the Cantabrian Sea (northern Spain) than in the Atlantic (west). In contrast, these models predicted an increase in the occurrence of B. bifurcata in both areas. The occurrences of Ascophyllum nodosum and Pelvetia canaliculata, species showing rather static historical distributions, were related to specific non‐climatic environmental conditions and locations, such as the location of sheltered sites. At the southernmost distributional limit, these habitats may present favourable microclimatic conditions or provide refuges from competitors or natural enemies. Model performances for Fucus vesiculosus and F. serratus were similar and poor, but several climatic variables influenced the occurrence of the latter in the HP analyses. Main conclusions The correlation between species distributions and climate was evident for two species, whereas the distributions of the others were associated with non‐climatic predictors. We hypothesize that the distribution of F. serratus responds to diverse combinations of factors in different sections of the north‐west Iberian Peninsula. Our study shows how the response of species distributions to climatic and non‐climatic variables may be complex and vary geographically. Our analyses also highlight the difficulty of making predictions based solely on variation in climatic factors measured at coarse spatial scales.  相似文献   

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