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      ‘Remote’ behavioural ecology: do megaherbivores consume vegetation in proportion to its presence in the landscape?

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          Abstract

          Examination of the feeding habits of mammalian species such as the African elephant ( Loxodonta africana) that range over large seasonally dynamic areas is exceptionally challenging using field-based methods alone. Although much is known of their feeding preferences from field studies, conclusions, especially in relation to differing habits in wet and dry seasons, are often contradictory. Here, two remote approaches, stable carbon isotope analysis and remote sensing, were combined to investigate dietary changes in relation to tree and grass abundances to better understand elephant dietary choice in the Kruger National Park, South Africa. A composited pair of Landsat Enhanced Thematic Mapper satellite images characterising flushed and senescent vegetation states, typical of wet and dry seasons respectively, were used to generate land-cover maps focusing on the forest to grassland gradient. Stable carbon isotope analysis of elephant faecal samples identified the proportion of C 3 (typically browse)/C 4 (typically grass) in elephant diets in the 1–2 days prior to faecal deposition. The proportion of surrounding C 4 land-cover was extracted using concentric buffers centred on faecal sample locations, and related to the faecal %C 4 content. Results indicate that elephants consume C 4 vegetation in proportion to its availability in the surrounding area during the dry season, but during the rainy season there was less of a relationship between C 4 intake and availability, as elephants targeted grasses in these periods. This study illustrates the utility of coupling isotope and cost-free remote sensing data to conduct complementary landscape analysis at highly-detailed, biologically meaningful resolutions, offering an improved ability to monitor animal behavioural patterns at broad geographical scales. This is increasingly important due to potential impacts of climate change and woody encroachment on broad-scale landscape habitat composition, allowing the tracking of shifts in species utilisation of these changing landscapes in a way impractical using field based methods alone.

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          Most cited references39

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          Effect size, confidence interval and statistical significance: a practical guide for biologists.

          Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.
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            Rapid responses of British butterflies to opposing forces of climate and habitat change.

            Habitat degradation and climate change are thought to be altering the distributions and abundances of animals and plants throughout the world, but their combined impacts have not been assessed for any species assemblage. Here we evaluated changes in the distribution sizes and abundances of 46 species of butterflies that approach their northern climatic range margins in Britain-where changes in climate and habitat are opposing forces. These insects might be expected to have responded positively to climate warming over the past 30 years, yet three-quarters of them declined: negative responses to habitat loss have outweighed positive responses to climate warming. Half of the species that were mobile and habitat generalists increased their distribution sites over this period (consistent with a climate explanation), whereas the other generalists and 89% of the habitat specialists declined in distribution size (consistent with habitat limitation). Changes in population abundances closely matched changes in distributions. The dual forces of habitat modification and climate change are likely to cause specialists to decline, leaving biological communities with reduced numbers of species and dominated by mobile and widespread habitat generalists.
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              Remote sensing imagery in vegetation mapping: a review

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                19 February 2020
                2020
                : 8
                : e8622
                Affiliations
                [1 ]Land Use Group, UK Centre for Ecology and Hydrology , Lancaster, UK
                [2 ]School of Life Sciences, University of Lincoln , Lincoln, UK
                [3 ]Department of Classics and Archaeology, University of Nottingham , Nottingham, UK
                [4 ]Department of Anthropology, University of Colorado at Boulder , Boulder, USA
                [5 ]Department of Zoology and Entomology, University of the Free State , Bloemfontein, South Africa
                [6 ]Centre for Environmental Management, University of the Free State , Bloemfontein, South Africa
                Author information
                http://orcid.org/0000-0002-8743-1123
                Article
                8622
                10.7717/peerj.8622
                7035871
                32117638
                30666db1-69e9-419f-a475-14fdc5dce589
                © 2020 Marston et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 20 August 2019
                : 22 January 2020
                Funding
                The authors received no funding for this work.
                Categories
                Animal Behavior
                Biogeography
                Ecology
                Spatial and Geographic Information Science

                behavioural ecology,diet,elephant,isotope,kruger national park,landsat,remote sensing

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