Dataset Information

Predicting changes in the distribution and abundance of species under environmental change.

ABSTRACT: Environmental changes are expected to alter both the distribution and the abundance of organisms. A disproportionate amount of past work has focused on distribution only, either documenting historical range shifts or predicting future occurrence patterns. However, simultaneous predictions of abundance and distribution across landscapes would be far more useful. To critically assess which approaches represent advances towards the goal of joint predictions of abundance and distribution, we review recent work on changing distributions and on effects of environmental drivers on single populations. Several methods have been used to predict changing distributions. Some of these can be easily modified to also predict abundance, but others cannot. In parallel, demographers have developed a much better understanding of how changing abiotic and biotic drivers will influence growth rate and abundance in single populations. However, this demographic work has rarely taken a landscape perspective and has largely ignored the effects of intraspecific density. We advocate a synthetic approach in which population models accounting for both density dependence and effects of environmental drivers are used to make integrated predictions of equilibrium abundance and distribution across entire landscapes. Such predictions would constitute an important step forward in assessing the ecological consequences of environmental changes.

SUBMITTER: Ehrlen J

PROVIDER: S-EPMC4674973 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:In the context of global warming, the habitats of Ephedra, including Ephedra sinica Stapf, Ephedra intermedia Schrenk ex Mey, and Ephedra equisetina Bunge, have been substantially threatened and deteriorated in recent years. Little is known about the potential geographic dynamics of economically renowned species, including those used in sand fixation and traditional Chinese medicine, under climate change. Therefore, evaluating their potential habitat and determining the crucial environmental variables affecting E. sinica, E. intermedia and E. equisetina under the driving force of global warming are extremely important. In this study, an optimized MaxEnt model in the kuenm package on the basis of occurrence records (a total of 103, 101 and 97 points for E. sinica, E. intermedia and E. equisetina, respectively) and 37 environmental factors were utilized to simulate the distribution of the three species. Two representative concentration pathways (SSP2.6 and SSP8.5) at 2041-2060 and 2061-2080, respectively, were used to establish a future distribution model of the three species. The results indicated that approximately 6.92 × 105 km2, 2.95 × 105 km2, and 11.5 × 105 km2 of suitable regions for E. sinica, E. intermedia and E. equisetina were obtained, which were mostly distributed in central and eastern Inner Mongolia, eastern and southern Gansu, and northern Xinjiang, respectively. Critical environmental variables, such as land cover and annual precipitation, were regarded as critical parameters for the three species. Future assessment revealed that over 60 % of the potential distribution area was affected, and the stability of E. sinica under the SSP8.5 scenario was the greatest. The spatial dynamic changes in suitable areas for E. intermedia were smaller than those for E. equisetina and E. sinica in the future. The comprehensive analysis revealed that the fluctuations in the distributions of the three Ephedra species under climate change are small and provide useful information for future conservation. Therefore, target conservation and management measures should be implemented in combination with the suitability thresholds of different environmental parameters. Our results provide useful recommendations for the current and future protection of Ephedra populations.

Project description:As a transitional vegetation type between evergreen broadleaved forest and deciduous broadleaved forest, evergreen-deciduous broadleaved mixed forest is composed of diverse plant species. This distinctive forest is generally distributed in mountainous areas with complex landforms and heterogeneous microenvironments. However, little is known about the roles of environmental conditions in driving the species diversity patterns of this forest. Here, based on a 15-ha plot in central China, we aimed to understand how and to what extent topographical characteristics and soil nutrients regulate the number and relative abundance of tree species in this forest. We measured environmental factors (terrain convexity, slope, soil total nitrogen, and phosphorus concentrations) and species diversity (species abundance distribution and species richness) in 20 m × 20 m subplots. Species abundance distribution was characterized by skewness, Berger-Parker index, and the proportion of singletons. The generalized additive model was used to examine the variations in diversity patterns caused by environmental factors. The structural equation model was used to assess whether and how topographical characteristics regulate species diversity via soil nutrients. We found that soil nutrients had significant negative effects on species richness and positive effects on all metrics of species abundance distribution. Convexity had significant positive effects on species richness and negative effects on all metrics of species abundance distribution, but these effects were mostly mediated by soil nutrients. Slope had significant negative effects on skewness and the Berger-Parker index, and these effects were almost independent of soil nutrients. Soil nutrients and topographical characteristics together accounted for 9.5-17.1% of variations in diversity patterns and, respectively, accounted for 8.9-13.9% and 3.3-10.7% of the variations. We concluded that soil nutrients were more important than topographical factors in regulating species diversity. Increased soil nutrient concentration led to decreased taxonomic diversity and increased species dominance and rarity. Convexity could be a better proxy for soil nutrients than slope. Moreover, these abiotic factors played limited roles in regulating diversity patterns, and it is possible that the observed patterns are also driven by some biotic and abiotic factors not considered here.

Project description:BackgroundAs global climate change accelerates, ecologists and conservationists are increasingly investigating changes in biodiversity and predicting species distribution based on species observed at sites, but rarely consider those plant species that could potentially inhabit but are absent from these areas (i.e., the dark diversity and its distribution). Here, we estimated the dark diversity of vascular plants in China and picked up threatened dark species from the result, and applied maximum entropy (MaxEnt) model to project current and future distributions of those dark species in their potential regions (those regions that have these dark species).MethodsWe used the Beals probability index to estimate dark diversity in China based on available species distribution information and explored which environmental variables had significant impacts on dark diversity by incorporating bioclimatic data into the random forest (RF) model. We collected occurrence data of threatened dark species (Eucommia ulmoides, Liriodendron chinense, Phoebe bournei, Fagus longipetiolata, Amentotaxus argotaenia, and Cathaya argyrophylla) and related bioclimatic information that can be used to predict their distributions. In addition, we used MaxEnt modeling to project their distributions in suitable areas under future (2050 and 2070) climate change scenarios.ResultsWe found that every study region's dark diversity was lower than its observed species richness. In these areas, their numbers of dark species are ranging from 0 to 215, with a generally increasing trend from western regions to the east. RF results showed that temperature variables had a more significant effect on dark diversity than those associated with precipitation. The results of MaxEnt modeling showed that most threatened dark species were climatically suitable in their potential regions from current to 2070.DiscussionsThe results of this study provide the first ever dark diversity patterns concentrated in China, even though it was estimated at the provincial scale. A combination of dark diversity and MaxEnt modeling is an effective way to shed light on the species that make up the dark diversity, such as projecting the distribution of specific dark species under global climate change. Besides, the combination of dark diversity and species distribution models (SDMs) may also be of value for ex situ conservation, ecological restoration, and species invasion prevention in the future.

Dataset Information

Predicting changes in the distribution and abundance of species under environmental change.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets