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  • 1
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    Online Resource
    Moving in the Anthropocene: Global reductions in terrestrial mammalian movements
    American Association for the Advancement of Science (AAAS) ; 2018
    In:  Science Vol. 359, No. 6374 ( 2018-01-26), p. 466-469
    Details
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 359, No. 6374 ( 2018-01-26), p. 466-469
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    URL: Article
    DOI: 10.1126/science.aam9712
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2018
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  • 2
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    Effects of body size on estimation of mammalian area requirements
    Wiley ; 2020
    In:  Conservation Biology Vol. 34, No. 4 ( 2020-08), p. 1017-1028
    Details
    In: Conservation Biology, Wiley, Vol. 34, No. 4 ( 2020-08), p. 1017-1028
    Abstract: Article impact statement : Due to autocorrelation‐induced bias, conventional methods severely underestimate the area requirements of GPS‐tracked large mammals.
    Type of Medium: Online Resource
    ISSN: 0888-8892 , 1523-1739
    URL: Issue
    URL: Article
    DOI: 10.1111/cobi.v34.4
    DOI: 10.1111/cobi.13495
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2020041-9
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  • 3
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    A comprehensive analysis of autocorrelation and bias in home range estimation
    Wiley ; 2019
    In:  Ecological Monographs Vol. 89, No. 2 ( 2019-05)
    Details
    In: Ecological Monographs, Wiley, Vol. 89, No. 2 ( 2019-05)
    Abstract: 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 () 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 . 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 . While 72% of the 369 empirical data sets had 〉 1,000 total observations, only 4% had an 〉 1,000, where 30% had an 〈 30. In this frequently encountered scenario of small , AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
    Type of Medium: Online Resource
    ISSN: 0012-9615 , 1557-7015
    URL: Issue
    URL: Article
    DOI: 10.1002/ecm.2019.89.issue-2
    DOI: 10.1002/ecm.1344
    Language: English
    Publisher: Wiley
    Publication Date: 2019
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  • 4
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    Evaluating expert‐based habitat suitability information of terrestrial mammals with GPS‐ tracking data
    Wiley ; 2022
    In:  Global Ecology and Biogeography Vol. 31, No. 8 ( 2022-08), p. 1526-1541
    Details
    In: Global Ecology and Biogeography, Wiley, Vol. 31, No. 8 ( 2022-08), p. 1526-1541
    Abstract: Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert‐based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert‐based information with detailed empirical evidence. Here, we compared expert‐based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS‐tracking data of 1,498 individuals from 49 mammal species. Location Worldwide. Time period 1998–2021. Major taxa studied Forty‐nine terrestrial mammal species. Methods Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS‐based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types. Results IUCN habitat suitability data were in accordance with the GPS data ( 〉  95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a 〉  50% probability of agreement based on proportional habitat use and selection ratios, respectively. Main conclusions We show how GPS‐tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS‐tracking data can be used to identify and prioritize species and habitat types for re‐evaluation of IUCN habitat suitability data.
    Type of Medium: Online Resource
    ISSN: 1466-822X , 1466-8238
    URL: Issue
    URL: Article
    DOI: 10.1111/geb.v31.8
    DOI: 10.1111/geb.13523
    Language: English
    Publisher: Wiley
    Publication Date: 2022
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  • 5
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    Behavioral responses of terrestrial mammals to COVID-19 lockdowns
    American Association for the Advancement of Science (AAAS) ; 2023
    In:  Science Vol. 380, No. 6649 ( 2023-06-09), p. 1059-1064
    Details
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6649 ( 2023-06-09), p. 1059-1064
    Abstract: GPS tracking of mammals over five continents shows how animal movements changed during COVID-19 lockdowns.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    URL: Article
    DOI: 10.1126/science.abo6499
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2023
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  • 6
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    Human‐induced reduction in mammalian movements impacts seed dispersal in the tropics
    Wiley ; 2021
    In:  Ecography Vol. 44, No. 6 ( 2021-06), p. 897-906
    Details
    In: Ecography, Wiley, Vol. 44, No. 6 ( 2021-06), p. 897-906
    Abstract: Seed dispersal is a key process affecting the structure, composition and spatial dynamics of plant populations. Numerous plant species in the tropics rely upon animals to disperse their seeds. Humans have altered mammalian movements, which will likely affect seed dispersal distances (SDD). Altered SDD may have a range of consequences for plant communities including reduced seedling recruitment and plant biomass, seed trait homogenization, altered gene flow and a reduced capacity to respond to environmental changes. Therefore, modelling the consequences of altered animal behaviour on ecosystem processes is important for predicting how ecosystems will respond to human impacts. While previous research has focused on the link between animal species extirpation and SDD, it remains unclear how changes in mammalian movement will impact SDD. Here we implemented a mechanistic modelling approach to examine how mammalian movement reductions impact SDD in the tropics. We combined allometric theory with a mechanistic seed dispersal model to estimate SDD via the movement of 37 large frugivorous mammals ( 〉 10 kg) in the tropics under different levels of human footprint, a global proxy of direct and indirect human disturbances. Our results suggest that assemblage‐level SDD reductions are estimated to be up to 80% across the tropics in response to human disturbance. This is particularly the case in areas with high human impact such as agricultural landscapes and suburban areas. The region with the largest reductions in SDD was the Asia‐Pacific with average reductions of 25%, followed by Central–South America (16%) and then Africa (15%). Our study provides insights into how human‐induced changes in movement behaviour of large mammals could translate into altered ecosystem functioning.
    Type of Medium: Online Resource
    ISSN: 0906-7590 , 1600-0587
    URL: Issue
    URL: Article
    DOI: 10.1111/ecog.2021.v44.i6
    DOI: 10.1111/ecog.05210
    Language: English
    Publisher: Wiley
    Publication Date: 2021
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  • 7
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    MadingleyR: An R package for mechanistic ecosystem modelling
    Wiley ; 2021
    In:  Global Ecology and Biogeography Vol. 30, No. 9 ( 2021-09), p. 1922-1933
    Details
    In: Global Ecology and Biogeography, Wiley, Vol. 30, No. 9 ( 2021-09), p. 1922-1933
    Abstract: Mechanistic general ecosystem models are used to explore fundamental ecological dynamics and to assess possible consequences of anthropogenic and natural disturbances on ecosystems. The Madingley model is a mechanistic general ecosystem model (GEM) that simulates a coherent global ecosystem, consisting of photo‐autotrophic and heterotrophic life, based on fundamental ecological processes. The C++ implementation of the Madingley model delivers fast computational performance, but it (a) limits the userbase to researchers that are familiar with the intricacies of C++ programming, (b) has limited possibility to change model settings and provide model outputs required to address specific research questions, and (c) has limited reproducibility of simulation experiments. The aim of this paper is to present an R package of the Madingley model to aid with increasing the accessibility and flexibility of the model. Innovation The MadingleyR R package streamlines the installation procedure and supports all major operating systems. MadingleyR enables users to combine multiple consecutive simulations, making case study specific modifications to MadingleyR objects along the way. Default input files are available from the package and study‐specific inputs can be easily loaded from the R environment. MadingleyR also provides functions to plot and summarize MadingleyR outputs. We provide a comprehensive description of the MadingleyR functions and workflow. We also demonstrate the applicability of the MadingleyR package using three case studies: (a) simulating the cascading effects of the loss of mega‐herbivores on food‐web structure, (b) simulating the impacts of increased land‐use intensity on the total biomass of different feeding guilds by restricting the total vegetation biomass available for feeding and (c) simulating the impacts of an intensive land‐use scenario on a continental scale. Main conclusions The MadingleyR package provides direct accessibility to simulations with the mechanistic ecosystem model Madingley and is flexible in its application without a loss in performance.
    Type of Medium: Online Resource
    ISSN: 1466-822X , 1466-8238
    URL: Issue
    URL: Article
    DOI: 10.1111/geb.v30.9
    DOI: 10.1111/geb.13354
    Language: English
    Publisher: Wiley
    Publication Date: 2021
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  • 8
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    HomeRange : A global database of mammalian home ranges
    Wiley ; 2023
    In:  Global Ecology and Biogeography Vol. 32, No. 2 ( 2023-02), p. 198-205
    Details
    In: Global Ecology and Biogeography, Wiley, Vol. 32, No. 2 ( 2023-02), p. 198-205
    Abstract: Home range is a common measure of use of space by animals because it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of use of space by animals. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has historically been biased towards terrestrial mammals. The use of aggregated numbers and the terrestrial focus limit our ability to examine home‐range patterns across different environments, their variation in time and variation between different levels of organization. Here, we introduce HomeRange , a global database with 75,611 home‐range values across 960 different species of mammals, including terrestrial, aquatic and aerial species. Main types of variables contained The dataset contains estimates of home ranges of mammals, species names, methodological information on data collection, method of home‐range estimation, period of data collection, study coordinates and name of location, in addition to species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit. Spatial location and grain The collected data are distributed globally. Across studies, the spatial accuracy varies, with the coarsest resolution being 1°. Time period and grain The data represent information published between 1939 and 2022. Across studies, the temporal accuracy varies; some studies report start and end dates specific to the day, whereas for other studies only the month or year is reported. Major taxa and level of measurement Mammalian species from 24 of the 27 different taxonomic orders. Home‐range estimates range from individual‐level values to population‐level averages. Software format Data are supplied as a comma‐delimited text file (.csv) and can be loaded directly into R using the “HomeRange” R package ( https://github.com/SHoeks/HomeRange ).
    Type of Medium: Online Resource
    ISSN: 1466-822X , 1466-8238
    URL: Issue
    URL: Article
    DOI: 10.1111/geb.v32.2
    DOI: 10.1111/geb.13625
    Language: English
    Publisher: Wiley
    Publication Date: 2023
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  • 9
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    A vision for incorporating human mobility in the study of human–wildlife interactions
    Springer Science and Business Media LLC ; 2023
    In:  Nature Ecology & Evolution Vol. 7, No. 9 ( 2023-08-07), p. 1362-1372
    Details
    In: Nature Ecology & Evolution, Springer Science and Business Media LLC, Vol. 7, No. 9 ( 2023-08-07), p. 1362-1372
    Type of Medium: Online Resource
    ISSN: 2397-334X
    URL: Article
    DOI: 10.1038/s41559-023-02125-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2879715-2
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  • 10
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    Environmental drivers of global variation in home range size of terrestrial and marine mammals
    Wiley ; 2024
    In:  Journal of Animal Ecology Vol. 93, No. 4 ( 2024-04), p. 488-500
    Details
    In: Journal of Animal Ecology, Wiley, Vol. 93, No. 4 ( 2024-04), p. 488-500
    Abstract: As animal home range size (HRS) provides valuable information for species conservation, it is important to understand the driving factors of HRS variation. It is widely known that differences in species traits (e.g. body mass) are major contributors to variation in mammal HRS. However, most studies examining how environmental variation explains mammal HRS variation have been limited to a few species, or only included a single (mean) HRS estimate for the majority of species, neglecting intraspecific HRS variation. Additionally, most studies examining environmental drivers of HRS variation included only terrestrial species, neglecting marine species. Using a novel dataset of 2800 HRS estimates from 586 terrestrial and 27 marine mammal species, we quantified the relationships between HRS and environmental variables, accounting for species traits. Our results indicate that terrestrial mammal HRS was on average 5.3 times larger in areas with low human disturbance (human footprint index [HFI] = 0), compared to areas with maximum human disturbance (HFI = 50). Similarly, HRS was on average 5.4 times larger in areas with low annual mean productivity (NDVI = 0), compared to areas with high productivity (NDVI = 1). In addition, HRS increased by a factor of 1.9 on average from low to high seasonality in productivity (standard deviation (SD) of monthly NDVI from 0 to 0.36). Of these environmental variables, human disturbance and annual mean productivity explained a larger proportion of HRS variance than seasonality in productivity. Marine mammal HRS decreased, on average, by a factor of 3.7 per 10°C decline in annual mean sea surface temperature (SST), and increased by a factor of 1.5 per 1°C increase in SST seasonality (SD of monthly values). Annual mean SST explained more variance in HRS than SST seasonality. Due to the small sample size, caution should be taken when interpreting the marine mammal results. Our results indicate that environmental variation is relevant for HRS and that future environmental changes might alter the HRS of individuals, with potential consequences for ecosystem functioning and the effectiveness of conservation actions.
    Type of Medium: Online Resource
    ISSN: 0021-8790 , 1365-2656
    URL: Issue
    URL: Article
    DOI: 10.1111/jane.v93.4
    DOI: 10.1111/1365-2656.14073
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2024
    detail.hit.zdb_id: 2006616-8
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