Journal
DIVERSITY AND DISTRIBUTIONS
Volume 28, Issue 4, Pages 685-699Publisher
WILEY
DOI: 10.1111/ddi.13468
Keywords
Acrocephalus; habitat heterogeneity; LiDAR; Locustella; reedbed structure; SAR; Sentinel; temporal vegetation dynamics
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Funding
- Netherlands eScience Center [ASDI.2016.014]
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This study aims to assess the predictive ability of metrics derived from different types of high-resolution remote sensing (RS) products for the habitat suitability of wetland birds. The results show that ALS and Sentinel metrics improve the accuracy of species distribution models (SDMs) for wetland bird species by 11% and 10% of the area under curve (AUC) respectively. The importance of different RS products varies among species.
Aim The increasing availability of remote sensing (RS) products from airborne laser scanning (ALS) surveys, synthetic aperture radar acquisitions and multispectral satellite imagery provides unprecedented opportunities for describing the physical structure and seasonal changes of vegetation. However, the added value of these RS products for predicting species distributions and animal habitats beyond land cover maps remains little explored. Here, we aim to assess how metrics derived from different types of high-resolution (10 m) RS products predict the habitat suitability of wetland birds. Location North-eastern part of the Netherlands. Methods We built species distribution models (SDMs) with occurrence observations from territory mapping of two selected wetland bird species (great reed warbler and Savi's warbler) and metrics from a Dutch land cover map, country-wide ALS and Sentinel-1 and Sentinel-2 RS products. We then compared model performance, relative variable importance and response curves of the SDMs to assess the contribution and ecological relevance of each RS product and metric. Results Our results showed that ALS and Sentinel metrics improve SDMs with only land cover metrics by 11% and 10% of the Area Under Curve (AUC) for the great reed warbler and the Savi's warbler respectively. Assessments of feature importance revealed that all types of RS products contributed substantially to predicting the habitat suitability of these wetland birds, but that the most important variables vary among species. Main conclusions Our study demonstrates that metrics from different high-resolution RS products capture complementary ecological information on animal habitats, including aspects such as the proportional cover of habitat types, vegetation density and the horizontal variability of vegetation height. Land cover maps with detailed spatial and thematic information can already achieve high model accuracies, but adding metrics derived from ALS point clouds and Sentinel imagery further improve model accuracy and enhance the understanding of animal-habitat relationships.
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