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- SourceAvailable from: Tongli Wang[Show abstract] [Hide abstract]
ABSTRACT: Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species' geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species' ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.PLoS ONE 03/2015; 10(3):e0120056. DOI:10.1371/journal.pone.0120056
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ABSTRACT: Invasive species can alter the succession of ecological communities because they are often adapted to the disturbed conditions that initiate succession. The extent to which this occurs may depend on how widely they are distributed across environmental gradients and how long they persist over the course of succession. We focus on plant communities of the USA Pacific Northwest coastal dunes, where disturbance is characterized by changes in sediment supply, and the plant community is dominated by two introduced grasses - the long-established Ammophila arenaria and the currently invading A. breviligulata. Previous studies showed that A. breviligulata has replaced A. arenaria and reduced community diversity. We hypothesize that this is largely due to A. breviligulata occupying a wider distribution across spatial environmental gradients and persisting in later-successional habitat than A. arenaria. We used multi-decadal chronosequences and a resurvey study spanning 2 decades to characterize distributions of both species across space and time, and investigated how these distributions were associated with changes in the plant community. The invading A. breviligulata persisted longer and occupied a wider spatial distribution across the dune, and this corresponded with a reduction in plant species richness and native cover. Furthermore, backdunes previously dominated by A. arenaria switched to being dominated by A. breviligulata, forest, or developed land over a 23-yr period. Ammophila breviligulata likely invades by displacing A. arenaria, and reduces plant diversity by maintaining its dominance into later successional backdunes. Our results suggest distinct roles in succession, with A. arenaria playing a more classically facilitative role and A. breviligulata a more inhibitory role. Differential abilities of closely-related invasive species to persist through time and occupy heterogeneous environments allows for distinct impacts on communities during succession.PLoS ONE 02/2015; 10(2):e0117283. DOI:10.1371/journal.pone.0117283
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ABSTRACT: Scaly-sided Merganser is a globally endangered species restricted to eastern Asia. Estimating its population is difficult and considerable gap exists between populations at its breeding grounds and wintering sites. In this study, we built a species distribution model (SDM) using Maxent with presence-only data to predict the potential wintering habitat for Scaly-sided Merganser in China. Area under the receiver operating characteristic curve (AUC) method suggests high predictive power of the model (training and testing AUC were 0.97 and 0.96 respectively). The most significant environmental variables included annual mean temperature, mean temperature of coldest quarter, minimum temperature of coldest month and precipitation of driest quarter. Suitable conditions for Scaly-sided Merganser are predicted in the middle and lower reaches of the Yangtze River, especially in Jiangxi, Hunan and Hubei Provinces. The predicted suitable habitat embraces 6,984 km of river. Based on survey results from three consecutive winters (2010-2012) and previous studies, we estimated that the entire wintering population of Scaly-sided Merganser in China to be 3,561 ± 478 individuals, which is consistent with estimate in its breeding ground.PLoS ONE 02/2015; 10(2):e0117307. DOI:10.1371/journal.pone.0117307
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