Dataset Information

Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing.

ABSTRACT: Spatial heterogeneity of ecosystems crucially influences plant performance, while in return plant feedbacks on their environment may increase heterogeneous patterns. This is of particular relevance for exotic plant invaders that transform native ecosystems, yet, approaches integrating geospatial information of environmental heterogeneity and plant-plant interaction are lacking. Here, we combined remotely sensed information of site topography and vegetation cover with a functional tracer of the N cycle, ?15N. Based on the case study of the invasion of an N2-fixing acacia in a nutrient-poor dune ecosystem, we present the first model that can successfully predict (R 2?=?0.6) small-scale spatial variation of foliar ?15N in a non-fixing native species from observed geospatial data. Thereby, the generalized additive mixed model revealed modulating effects of heterogeneous environments on invader impacts. Hence, linking remote sensing techniques with tracers of biological processes will advance our understanding of the dynamics and functioning of spatially structured heterogeneous systems from small to large spatial scales.

SUBMITTER: Hellmann C

PROVIDER: S-EPMC5482842 | biostudies-other | 2017 Jun

REPOSITORIES: biostudies-other

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Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing.

Hellmann Christine C Große-Stoltenberg André A Thiele Jan J Oldeland Jens J Werner Christiane C

Scientific reports 20170623 1

Spatial heterogeneity of ecosystems crucially influences plant performance, while in return plant feedbacks on their environment may increase heterogeneous patterns. This is of particular relevance for exotic plant invaders that transform native ecosystems, yet, approaches integrating geospatial information of environmental heterogeneity and plant-plant interaction are lacking. Here, we combined remotely sensed information of site topography and vegetation cover with a functional tracer of the N ...[more]

PMID: 28646189

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Project description:BackgroundSchistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health.MethodologyWe employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d'Ivoire and validated against readily available survey data from school-aged children.Principal findingsEnvironmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d'Ivoire.Conclusions/significanceA predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data.

Dataset Information

Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing.

Publications

Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing.

Similar Datasets

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