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We investigated whether a given landscape structure affects the level of home range size adaptation in response to resource variability. We tested whether increasing resource variability forces herbivorous mammals to increase their home ranges. In 2014 and 2015 we collared 40 European brown hares (Lepus europaeus) with GPS-tags to record hare movements in two regions in Germany with differing landscape structures. We examined hare home range sizes in relation to resource availability and variability by using the normalized difference vegetation index as a proxy. Hares in simple landscapes showed increasing home range sizes with increasing resource variability, whereas hares in complex landscapes did not enlarge their home range. Animals in complex landscapes have the possibility to include various landscape elements within their home ranges and are more resilient against resource variability. But animals in simple landscapes with few elements experience shortcomings when resource variability becomes high. The increase in home range size, the movement related increase in energy expenditure, and a decrease in hare abundances can have severe implications for conservation of mammals in anthropogenic landscapes. Hence, conservation management could benefit from a better knowledge about fine-scaled effects of resource variability on movement behaviour.
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
Understanding vegetation-modern pollen relationships is essential to provide confidence in fossil pollen reconstructions of long-term vegetation changes in savanna ecosystems. In this paper we compare the taxonomical composition and the diversity (Hill NO, N1, N2) of vegetation and modern pollen along precipitation and local grazing-intensity gradients in Namibian savannas. Modern pollen was extracted from surface soil samples collected from 5 x 5 m plots distributed along four 500 m gradients. Vegetation was surveyed in each plot. The results show a high correspondence between vegetation and pollen data in terms of composition. Precipitation and grazing explain a significant although low proportion of compositional change in the vegetation and pollen spectra. We identified pollen taxa as indicators of grazing pressure such as Limeum, Alternanthera, and particularly Tribulus. Correspondence between vegetation and pollen data in terms of taxa richness (NO) is limited, probably because of the influence of landscape heterogeneity and openness, as well as low pollen concentrations. In contrast, the effective numbers of common and dominant taxa (N1, N2) are consistent among the different datasets. We conclude that in spite of limitations, modern pollen assemblages can reflect changes in vegetation composition, richness and diversity patterns along precipitation and grazing gradients in savanna environments. (C) 2018 Elsevier B.V. All rights reserved.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
Agricultural land-use practices have intensified over the last decades, leading to population declines of various farmland species, including the European hare (Lepus europaeus). In many European countries, arable fields dominate agricultural landscapes. Compared to pastures, arable land is highly variable, resulting in a large spatial variation of food and cover for wildlife over the course of the year, which potentially affects habitat selection by hares. Here, we investigated within-home-range habitat selection by hares in arable areas in Denmark and Germany to identify habitat requirements for their conservation. We hypothesized that hare habitat selection would depend on local habitat structure, that is, vegetation height, but also on agricultural field size, vegetation type, and proximity to field edges. Active hares generally selected for short vegetation (1-25 cm) and avoided higher vegetation and bare ground, especially when fields were comparatively larger. Vegetation >50 cm potentially restricts hares from entering parts of their home range and does not provide good forage, the latter also being the case on bare ground. The vegetation type was important for habitat selection by inactive hares, with fabaceae, fallow, and maize being selected for, potentially providing both cover and forage. Our results indicate that patches of shorter vegetation could improve the forage quality and habitat accessibility for hares, especially in areas with large monocultures. Thus, policymakers should aim to increase areas with short vegetation throughout the year. Further, permanent set-asides, like fallow and wildflower areas, would provide year-round cover for inactive hares. Finally, the reduction in field sizes would increase the density of field margins, and farming different crop types within small areas could improve the habitat for hares and other farmland species.