BackgroundPredicting species’ potential geographical range by species distribution models (SDMs) is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs.MethodologyWe collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis) and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials). We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values.ResultsThe mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (p<0.05), while the associated standard deviations and coefficients of variation were larger for BIOCLIM and DOMAIN trials (p<0.05), and the 99% confidence intervals for AUC and Kappa values were narrower for MAHAL, RF, MAXENT, and SVM. Compared to BIOCLIM and DOMAIN, other SDMs (MAHAL, RF, MAXENT, and SVM) had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points).ConclusionsAccording to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important part of the modeling process.

Many studies predict that climate change will cause species movement and turnover, but few have considered the effect of climate change on range fragmentation for current species and/or populations. We used MaxEnt to predict suitable habitat, fragmentation and turnover for 134 amphibian species in China under 40 future climate change scenarios spanning four pathways (RCP2.6, RCP4.5, RCP6 and RCP8.5) and two time periods (the 2050s and 2070s). Our results show that climate change may cause a major shift in spatial patterns of amphibian diversity. Amphibians in China would lose 20% of their original ranges on average; the distribution outside current ranges would increase by 15%. Suitable habitats for over 90% of species will be located in the north of their current range, for over 95% of species in higher altitudes (from currently 137–4,124 m to 286–4,396 m in the 2050s or 314–4,448 m in the 2070s), and for over 75% of species in the west of their current range. Also, our results predict two different general responses to the climate change: some species contract their ranges while moving westwards, southwards and to higher altitudes, while others expand their ranges. Finally, our analyses indicate that range dynamics and fragmentation are related, which means that the effects of climate change on Chinese amphibians might be two-folded.

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The following is a report on software developed to create virtual species for the study of species distribution modelling (SDM). SDMvspecies provides several methods to create virtual species. The package is designed to be simple and intuitive, even for users who are not familiar with the R language. SDMvspecies is available online free of charge from .

Many studies predict that climate change will cause species movement and turnover, but few studies have considered the effect of climate change on range fragmentation for current species and/or populations. We used MaxEnt to predict suitable habitat, fragmentation and turnover for 134 amphibian species in China under 40 future climate change scenarios spanning four pathways (RCP2.6, RCP4.5, RCP6 and RCP8.5) and two time periods (the 2050s and 2070s). Our results show that climate change will cause a major shift in the spatial patterns of amphibian diversity. Suitable habitats for over 90% of species will be located in the north of the current range, for over 95% of species in higher altitudes, and for over 75% of species in the west of the current range. The distributions of species predicted to move westwards, southwards and to higher altitudes will contract, while the ranges of the species not showing these trends will expand. Amphibians will lose 20% of their original ranges on average; the distribution outside current ranges will increase by 15%. Climate change will likely modify the spatial configuration of climatically suitable areas. Changes in area and fragmentation of climatically suitable patches are related, which means that species may be simultaneously affected by different stressors as a consequence of climate change.

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Greenhouse soils and arable (wheat field) soil samples were collected to identify the effects of greenhouse cultivation on the accumulation of six heavy metals (Cd, Cu, Zn, Pb, Cr, and Ni) and to evaluate the likely sources responsible for heavy metal accumulation in the irrigated desert soils of Wuwei District, China. The results indicated that the mean concentrations of Cd, Cu, Zn, Pb, Cr, and Ni were 0.421, 33.85, 85.31, 20.76, 53.12, and 28.59 mg kg(-1), respectively. The concentrations of Cd, Cu, and Zn in greenhouse soils were 60, 23, and 14% higher than those in arable soils and 263, 40, and 25% higher than background concentrations of natural soils in the study area, respectively. These results indicated that Cd, Cu, and Zn accumulation occurred in the greenhouse soils, and Cd was the most problematically accumulated heavy metal, followed by Cu and Zn. There was a significant positive correlation between the concentrations of Cd, Cu, and Zn in greenhouse soils and the number of years under cultivation (P < 0.05). Greenhouse cultivation had little impact on the accumulation of Cr, Ni, or Pb. Correlation analysis and principal component analysis suggested that the accumulation of Cd, Cu, and Zn in greenhouse soils resulted mainly from fertilizer applications. Our results indicated that the excessive and long-term use of fertilizers and livestock manures with high heavy metal levels leads to the accumulation of heavy metals in soils. Therefore, rational fertilization programs and reductions in the concentrations of heavy metals in both fertilizers and manure must be recommended to maintain a safe concentration of heavy metals in greenhouse soils.

Understanding what governs community assembly and the maintenance of biodiversity is a central issue in ecology, but has been a continuing debate. A key question is the relative importance of habitat specialization (niche assembly) and dispersal limitation (dispersal assembly). In the middle of the Loess Plateau, northwestern China, we examined how species turnover in Liaodong oak (Quercus wutaishanica) forests differed between observed and randomized assemblies, and how this difference was affected by habitat specialization and dispersal limitation using variation partitioning. Results showed that expected species turnover based on individual randomization was significantly lower than the observed value (P < 0.01). The turnover deviation significantly depended on the environmental and geographical distances (P < 0.05). Environmental and spatial variables significantly explained approximately 40% of the species composition variation at all the three layers (P < 0.05). However, their contributions varied among forest layers; the herb and shrub layers were dominated by environmental factors, whereas the canopy layer was dominated by spatial factors. Our results underscore the importance of synthetic models that integrate effects of both dispersal and niche assembly for understanding the community assembly. However, habitat specialization (niche assembly) may not always be the dominant process in community assembly, even under harsh environments. Community assembly may be in a trait-dependent manner (e.g., forest layers in this study). Thus, taking more species traits into account would strengthen our confidence in the inferred assembly mechanisms.