Adding structure to land cover - using fractional cover to study animal habitat selection

Linking animal movements to landscape features is critical to identify factors that shape the spatial behaviour of animals. Habitat selection is led by behavioural decisions and is shaped by the environment, therefore the landscape is crucial for the analysis. Land cover classification based on ground survey and remote sensing data sets are an established approach to define landscapes for habitat selection analysis.We investigate an approach for analysing habitat use using continuous land cover information and spatial metrics. This approach uses a continuous representation of the landscape using percentage cover of a chosen land cover type instead of discrete classes. This approach, fractional cover, captures spatial heterogeneity within classes and is therefore capable to provide a more distinct representation of the landscape. The variation in home range sizes is analysed using fractional cover and spatial metrics in conjunction with mixed effect models on red deer position data in the Bohemian Forest, compared over multiple spatio?temporal scales.ResultsWe analysed forest fractional cover and a texture metric within each home range showing that variance of fractional cover values and texture explain much of variation in home range sizes. The results show a hump?shaped relationship, leading to smaller home ranges when forest fractional cover is very homogeneous or highly heterogeneous, while intermediate stages lead to larger home ranges. ConclusionThe application of continuous land cover information in conjunction with spatial metrics proved to be valuable for the explanation of home-range sizes of red deer

Adding structure to land cover – using fractional cover to study animal habitat use

International audienceBackground: Linking animal movements to landscape features is critical to identify factors that shape the spatial behaviour of animals. Habitat selection is led by behavioural decisions and is shaped by the environment, therefore the landscape is crucial for the analysis. Land cover classification based on ground survey and remote sensing data sets are an established approach to define landscapes for habitat selection analysis. We investigate an approach for analysing habitat use using continuous land cover information and spatial metrics. This approach uses a continuous representation of the landscape using percentage cover of a chosen land cover type instead of discrete classes. This approach, fractional cover, captures spatial heterogeneity within classes and is therefore capable to provide a more distinct representation of the landscape. The variation in home range sizes is analysed using fractional cover and spatial metrics in conjunction with mixed effect models on red deer position data in the Bohemian Forest, compared over multiple spatio-temporal scales. Results: We analysed forest fractional cover and a texture metric within each home range showing that variance of fractional cover values and texture explain much of variation in home range sizes. The results show a hump-shaped relationship, leading to smaller home ranges when forest fractional cover is very homogeneous or highly heterogeneous, while intermediate stages lead to larger home ranges. Conclusion: The application of continuous land cover information in conjunction with spatial metrics proved to be valuable for the explanation of home-range sizes of red deer

Cover-based allometric estimate of aboveground biomass of a non-native, invasive annual grass (Bromus tectorum L.) in the Great Basin, USA

Cheatgrass (Bromus tectorum L.) presence in the Great Basin is associated with an increase in fire frequency andsize, likely due to increased spatial continuity of fine fuel biomass. Measurements of the extent and cover ofcheatgrass are steadily improving, but the strength of the relationship between cover and aboveground biomass(AGB) is unclear. An allometric equation that can reliably convert cover to AGB of cheatgrass would allow forimproved incorporation of regional estimates of cover into models of fire activity, carbon storage, and net pri&shy;mary productivity, all of which rely on biomass. We measured cover and AGB of cheatgrass at 60 locations in thenorth-central Great Basin and used these measurements to model the relationship. We found a strong, linearrelationship between the percent cover and AGB, which was improved after square root transformation of bothcover and AGB, and after incorporating the number of days after peak NDVI that the biomass and cover weremeasured. These results show that AGB of cheatgrass can be reliably estimated from cover. It is likely thatallometric equations based on cover will be effective for other grass species, but care must be taken to account forphenology (e.g., peak NDVI) in the estimation.</p

Remote sensing in ecology and conservation: three years on

Editorial

Remote sensing in ecology and conservation: three years on

In 2014, Wiley and the Zoological Society of London launched Remote Sensing in Ecology and Conservation, an open‐access journal that aims to support communication and collaboration among experts in remote sensing, ecology and conservation science. Remote sensing was from the start understood as the acquisition of information about an object or phenomenon through a device that is not in physical contact with the object, thus including camera traps, field spectrometry, terrestrial and aquatic acoustic sensors, aerial and satellite monitoring as well as ship‐borne automatic identification systems (Pettorelli et al. 2015). The primary goals of this new journal were, and still are, to maximize the understanding and uptake of remote sensing‐based techniques and products by the ecological and conservation communities, prioritizing findings that advance the scientific basis of, and applied outcomes from, ecology and conservation science; and to identify ecological challenges that might direct development of future remote sensors and data products