in

Explicit integration of dispersal-related metrics improves predictions of SDM in predatory arthropods

  • 1.

    Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. Impacts of climate change on the future of biodiversity: biodiversity and climate change. Ecol. Lett. 15, 365–377 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  • 2.

    Garcia, R. A., Cabeza, M., Rahbek, C. & Araújo, M. B. Multiple dimensions of climate change and their implications for biodiversity. Science 344, 1247579 (2014).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  • 3.

    Pereira, H. M. et al. Scenarios for global biodiversity in the 21st century. Science 330, 1496–1501 (2010).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 4.

    Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003).

    ADS  CAS  Article  Google Scholar 

  • 5.

    Parmesan, C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst. 37, 637–669 (2006).

    Article  Google Scholar 

  • 6.

    Walther, G.-R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 7.

    Thomas, C. D. et al. Extinction risk from climate change. Nature 427, 145–148 (2004).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 8.

    Miller, J. Species distribution modeling. Geogr, Compass 4, 490–509 (2010).

    Article  Google Scholar 

  • 9.

    Guisan, A. et al. Predicting species distributions for conservation decisions. Ecol. Lett. 16, 1424–1435 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  • 10.

    Bellard, C. et al. Will climate change promote future invasions?. Glob. Change Biol. 19, 3740–3748 (2013).

    ADS  Article  Google Scholar 

  • 11.

    Hijmans, R. J. & Graham, C. H. The ability of climate envelope models to predict the effect of climate change on species distributions. Glob. Change Biol. 12, 2272–2281 (2006).

    ADS  Article  Google Scholar 

  • 12.

    Hao, T., Elith, J., Guillera-Arroita, G. & Lahoz-Monfort, J. J. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Divers. Distrib. 25, 839–852 (2019).

    Article  Google Scholar 

  • 13.

    Melo-Merino, S. M., Reyes-Bonilla, H. & Lira-Noriega, A. Ecological niche models and species distribution models in marine environments: a literature review and spatial analysis of evidence. Ecol. Model. 415, 108837 (2020).

    Article  Google Scholar 

  • 14.

    Qiao, H., Soberón, J. & Peterson, A. T. No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation. Methods Ecol. Evol. 6, 1126–1136 (2015).

    Article  Google Scholar 

  • 15.

    Araújo, M. B. & New, M. Ensemble forecasting of species distributions. Trends Ecol. Evol. 22, 42–47 (2007).

    PubMed  Article  PubMed Central  Google Scholar 

  • 16.

    Thuiller, W. Patterns and uncertainties of species’ range shifts under climate change. Glob. Change Biol. 10, 2020–2027 (2004).

    ADS  Article  Google Scholar 

  • 17.

    Thuiller, W., Guéguen, M., Renaud, J., Karger, D. N. & Zimmermann, N. E. Uncertainty in ensembles of global biodiversity scenarios. Nat. Commun. 10, 1–9 (2019).

    CAS  Article  Google Scholar 

  • 18.

    Titeux, N. et al. Biodiversity scenarios neglect future land-use changes. Glob. Change Biol. 22, 2505–2515 (2016).

    ADS  Article  Google Scholar 

  • 19.

    Solomon, S. et al.IPCC, 2007: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Vol. 1 (2007).

  • 20.

    Guisan, A. & Thuiller, W. Predicting species distribution: offering more than simple habitat models. Ecol. Lett. 8, 993–1009 (2005).

    Article  Google Scholar 

  • 21.

    Richmond, O. M. W., McEntee, J. P., Hijmans, R. J. & Brashares, J. S. Is the climate right for pleistocene rewilding? Using species distribution models to extrapolate climatic suitability for mammals across continents. PLoS ONE 5, e12899 (2010).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 22.

    Kearney, M. Habitat, environment and niche: what are we modelling?. Oikos 115, 186–191 (2006).

    Article  Google Scholar 

  • 23.

    Soberon, J. & Peterson, A. T. Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodivers. Inform.2, 1–10 (2005).

    Article  Google Scholar 

  • 24.

    Merow, C., LaFleur, N., Silander, J. A. Jr., Wilson, A. M. & Rubega, M. Developing dynamic mechanistic species distribution models: predicting bird-mediated spread of invasive plants across northeastern North America. Am. Nat. 178, 30–43 (2011).

    PubMed  Article  PubMed Central  Google Scholar 

  • 25.

    Bocedi, G. et al. RangeShifter: a platform for modelling spatial eco-evolutionary dynamics and species’ responses to environmental changes. Methods Ecol. Evol. 5, 388–396 (2014).

    Article  Google Scholar 

  • 26.

    Briscoe, N. J. et al. Forecasting species range dynamics with process-explicit models: matching methods to applications. Ecol. Lett. 22, 1940–1956 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  • 27.

    Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M. B. BIOMOD—a platform for ensemble forecasting of species distributions. Ecography 32, 369–373 (2009).

    Article  Google Scholar 

  • 28.

    Mammola, S. & Isaia, M. Rapid poleward distributional shifts in the European cave-dwelling Meta spiders under the influence of competition dynamics. J. Biogeogr. 44, 2789–2797 (2017).

    Article  Google Scholar 

  • 29.

    Lafage, D., Maugenest, S., Bouzillé, J.-B. & Pétillon, J. Disentangling the influence of local and landscape factors on alpha and beta diversities: opposite response of plants and ground-dwelling arthropods in wet meadows. Ecol. Res. 30, 1025–1035 (2015).

    Article  Google Scholar 

  • 30.

    Leroy, B. et al. First assessment of effects of global change on threatened spiders: potential impacts on Dolomedes Plantarius (Clerck) and its conservation plans. Biol. Conserv. 161, 155–163 (2013).

    Article  Google Scholar 

  • 31.

    Leroy, B. et al. Forecasted climate and land use changes, and protected areas: the contrasting case of spiders. Divers. Distrib. 20, 686–697 (2014).

    Article  Google Scholar 

  • 32.

    Keppel, G. & Wardell-Johnson, G. W. Refugia: keys to climate change management. Glob. Change Biol. 18, 2389–2391 (2012).

    ADS  Article  Google Scholar 

  • 33.

    Finlayson, C. M. et al. The second warning to humanity—providing a context for wetland management and policy. Wetlands 39, 1–5 (2019).

    Article  Google Scholar 

  • 34.

    van Helsdingen, P. J. Ecology and distribution of dolomedes in Europe (Araneida: Dolomedidae). Boll. Acc. Gioenia Sci. Nat. 26, 181–187 (1993).

    Google Scholar 

  • 35.

    Duffey, E. Dolomedes plantarius (Clerck, 1757) (Araneae: Pisauridae): a reassessment of its ecology and distribution in Europe, with comments on its history at Redgrave and Lopham Fen, England. Bull. Br. Arachnol. Soc. 15, 285–292 (2012).

    Google Scholar 

  • 36.

    Ivanov, V., Prishepchik, O. & Setrakova, E. Dolomedes plantarius (Araneae, Pisauridae) in Belarus: records, distribution and implications for conservation. Arachnol. Mitteilungen 54, 33–37 (2017).

    Article  Google Scholar 

  • 37.

    Holec, M. Spiders (aranea) of the fishpond eulittoral zone. In Proceedings of the 18th European Colloquium of Arachnology vol. 19, 51–54 (Ekológia, Bratislava, 2000).

  • 38.

    Duffey, E. The distribution, status and habitat of Dolomedes fimbriatus (Clerck) and D. plantarius (Clerck) in Europe. In Proceedings of 15th European Colloquium of Arachnology 54–65 (1995).

  • 39.

    Hill, J. K., Thomas, C. D. & Blakeley, D. S. Evolution of flight morphology in a butterfly that has recently expanded its geographic range. Oecologia 121, 165–170 (1999).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 40.

    GBIF: The Global Biodiversity Information Facility. What is GBIF?https://www.gbif.org/what-is-gbif (2019).

  • 41.

    R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria(2020).

  • 42.

    ESRI. World Imagery. (2009).

  • 43.

    Braunisch, V. et al. Selecting from correlated climate variables: a major source of uncertainty for predicting species distributions under climate change. Ecography 36, 971–983 (2013).

    Article  Google Scholar 

  • 44.

    Dormann, C. F. Promising the future? Global change projections of species distributions. Basic Appl. Ecol. 8, 387–397 (2007).

    Article  Google Scholar 

  • 45.

    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

  • 46.

    van Vuuren, D. P. et al. The representative concentration pathways: an overview. Clim. Change 109, 5 (2011).

    ADS  Article  Google Scholar 

  • 47.

    Hijmans, R. J., Cameron, S. E., Parra, J. L. & Jarvis, A. Very high resolution interpolated climated surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).

    Article  Google Scholar 

  • 48.

    Lafage, D. & Pétillon, J. Relative importance of management and natural flooding on spider, carabid and plant assemblages in extensively used grasslands along the Loire. Basic Appl. Ecol. 17, 535–545 (2016).

    Article  Google Scholar 

  • 49.

    Dickel, L. Characterisation of Habitat Requirements of European Fishing Spiders (Inland Norway University of Applied Sciences, 2019).

  • 50.

    EEA. European Union, Copernicus Land Monitoring Service 2018, European Environment Agency (EEA). (2018).

  • 51.

    Hurtt, G. C. et al. Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Clim. Change 109, 117 (2011).

    ADS  Article  Google Scholar 

  • 52.

    Senay, S. D., Worner, S. P. & Ikeda, T. Novel three-step pseudo-absence selection technique for improved species distribution modelling. PLoS ONE 8, e71218 (2013).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 53.

    Grenouillet, G., Buisson, L., Casajus, N. & Lek, S. Ensemble modelling of species distribution: the effects of geographical and environmental ranges. Ecography 34, 9–17 (2011).

    Article  Google Scholar 

  • 54.

    Buisson, L., Thuiller, W., Casajus, N., Lek, S. & Grenouillet, G. Uncertainty in ensemble forecasting of species distribution. Glob. Change Biol. 16, 1145–1157 (2010).

    ADS  Article  Google Scholar 

  • 55.

    Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many?. Methods Ecol. Evol. 3, 327–338 (2012).

    Article  Google Scholar 

  • 56.

    Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).

    Article  Google Scholar 

  • 57.

    Fawcett, T. An introduction to ROC analysis. Pattern Recognit. Lett. 27, 861–874 (2006).

    Article  Google Scholar 

  • 58.

    Engler, R. & Guisan, A. MigClim: predicting plant distribution and dispersal in a changing climate. Divers. Distrib. 15, 590–601 (2009).

    Article  Google Scholar 

  • 59.

    Bonte, D., Clercq, N. D., Zwertvaegher, I. & Lens, L. Repeatability of dispersal behaviour in a common dwarf spider: evidence for different mechanisms behind short- and long-distance dispersal. Ecol. Entomol. 34, 271–276 (2009).

    Article  Google Scholar 

  • 60.

    Lee, V. M. J., Kuntner, M. & Li, D. Ballooning behavior in the golden orbweb spider Nephila pilipes (Araneae: Nephilidae). Front. Ecol. Evol. 3, 2 (2015).

    Article  Google Scholar 

  • 61.

    Reynolds, A. M., Bohan, D. A. & Bell, J. R. Ballooning dispersal in arthropod taxa: conditions at take-off. Biol. Lett. 3, 237–240 (2007).

    PubMed  PubMed Central  Article  Google Scholar 

  • 62.

    Thomas, C. F. G., Brain, P. & Jepson, P. C. Aerial activity of linyphiid spiders: modelling dispersal distances from meteorology and behaviour. J. Appl. Ecol. 40, 912–927 (2003).

    Article  Google Scholar 

  • 63.

    Shah, V. B. & McRae, B. Circuitscape: a tool for landscape ecology. In Proceedings of the 7th Python in Science Conference Vol. 7 62–66 (2008).

  • 64.

    McRae, B. H., Dickson, B. G., Keitt, T. H. & Shah, V. B. Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology 89, 2712–2724 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  • 65.

    Keeley, A. T. H., Beier, P., Keeley, B. W. & Fagan, M. E. Habitat suitability is a poor proxy for landscape connectivity during dispersal and mating movements. Landsc. Urban Plan. 161, 90–102 (2017).

    Article  Google Scholar 

  • 66.

    Pelletier, D. et al. Applying circuit theory for corridor expansion and management at regional scales: tiling, pinch points, and omnidirectional connectivity. PLoS ONE 9, e84135 (2014).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 67.

    Febbraro, M. D. et al. Integrating climate and land-use change scenarios in modelling the future spread of invasive squirrels in Italy. Divers. Distrib. 25, 644–659 (2019).

    Article  Google Scholar 

  • 68.

    Warren, D. L., Glor, R. E. & Turelli, M. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evol. Int. J. Org. Evol. 62, 2868–2883 (2008).

    Article  Google Scholar 

  • 69.

    Rödder, D. & Engler, J. O. Quantitative metrics of overlaps in Grinnellian niches: advances and possible drawbacks. Glob. Ecol. Biogeogr. 20, 915–927 (2011).

    Article  Google Scholar 

  • 70.

    Bonte, D., Travis, J. M. J., Clercq, N. D., Zwertvaegher, I. & Lens, L. Thermal conditions during juvenile development affect adult dispersal in a spider. Proc. Natl. Acad. Sci. 105, 17000–17005 (2008).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 71.

    Eskildsen, A. et al. Testing species distribution models across space and time: high latitude butterflies and recent warming. Glob. Ecol. Biogeogr. 22, 1293–1303 (2013).

    Article  Google Scholar 

  • 72.

    Svenning, J.-C. & Skov, F. Limited filling of the potential range in European tree species. Ecol. Lett. 7, 565–573 (2004).

    Article  Google Scholar 

  • 73.

    Radchuk, V. et al. Adaptive responses of animals to climate change are most likely insufficient. Nat. Commun. 10, 1–14 (2019).

    CAS  Article  Google Scholar 

  • 74.

    Bell, J. R., Bohan, D. A., Shaw, E. M. & Weyman, G. S. Ballooning dispersal using silk: world fauna, phylogenies, genetics and models. Bull. Entomol. Res. 95, 69–114 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 75.

    Bonte, D., Borre, J. V., Lens, L. & Jean-Pierre, M. Geographical variation in wolf spider dispersal behaviour is related to landscape structure. Anim. Behav. 72, 655–662 (2006).

    Article  Google Scholar 

  • 76.

    Bellvert, A., Casals, A., Fonollosa, A., Dalmau, G. & Tobella, C. First record of Dolomedes plantarius (Clerck, 1758) (Araneae: Pisauridae) from the Iberian Peninsula. Rev. Ibérica Aracnol. 23, 109–111 (2013).

    Google Scholar 

  • 77.

    Carico, J. E. The nearctic species of the genus Dolomedes (Araneae: Pisauridae). Bull. Mus. Comp. Zool. Harv. Coll. 144, 435–488 (1973).

    Google Scholar 

  • 78.

    Weinstein, B. G., Graham, C. H. & Parra, J. L. The role of environment, dispersal and competition in explaining reduced co-occurrence among related species. PLoS ONE 12, e0185493 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 79.

    Montoya, J. M. & Raffaelli, D. Climate change, biotic interactions and ecosystem services. Philos. Trans. R. Soc. B Biol. Sci. 365, 2013–2018 (2010).

    Article  Google Scholar 

  • 80.

    Warren, M. S. et al. Rapid responses of British butterflies to opposing forces of climate and habitat change. Nature 414, 65–69 (2001).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 81.

    Roux, P. C. L. & McGeoch, M. A. Rapid range expansion and community reorganization in response to warming. Glob. Change Biol. 14, 2950–2962 (2008).

    ADS  Article  Google Scholar 

  • 82.

    Losos, J. B. Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species. Ecol. Lett. 11, 995–1003 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  • 83.

    Williams, D. D., Ambrose, L. G. & Browning, L. N. Trophic dynamics of two sympatric species of riparian spider (Araneae: Tetragnathidae). Can. J. Zool. 73, 1545–1553 (1995).

    Article  Google Scholar 

  • 84.

    Balfour, R. A., Buddle, C. M., Rypstra, A. L., Walker, S. E. & Marshall, S. D. Ontogenetic shifts in competitive interactions and intra-guild predation between two wolf spider species. Ecol. Entomol. 28, 25–30 (2003).

    Article  Google Scholar 

  • 85.

    Travis, J. M. J. et al. Dispersal and species’ responses to climate change. Oikos 122, 1532–1540 (2013).

    Article  Google Scholar 

  • 86.

    Travis, J. M. J. et al. Modelling dispersal: an eco-evolutionary framework incorporating emigration, movement, settlement behaviour and the multiple costs involved. Methods Ecol. Evol. 3, 628–641 (2012).

    Article  Google Scholar 

  • 87.

    Bonte, D., Lukáč, M. & Lens, L. Starvation affects pre-dispersal behaviour of Erigone spiders. Basic Appl. Ecol. 9, 308–315 (2008).

    Article  Google Scholar 

  • 88.

    Goodacre, S. L. et al. Microbial modification of host long-distance dispersal capacity. BMC Biol. 7, 32 (2009).

    PubMed  PubMed Central  Article  Google Scholar 

  • 89.

    De Meester, N. & Bonte, D. Information use and density-dependent emigration in an agrobiont spider. Behav. Ecol. 21, 992–998 (2010).

    Article  Google Scholar 

  • 90.

    Bonte, D. & Lens, L. Heritability of spider ballooning motivation under different wind velocities. Evol. Ecol. Res. 9, 817–827 (2007).

    Google Scholar 

  • 91.

    Clobert, J., Galliard, J.-F.L., Cote, J., Meylan, S. & Massot, M. Informed dispersal, heterogeneity in animal dispersal syndromes and the dynamics of spatially structured populations. Ecol. Lett. 12, 197–209 (2009).

    PubMed  Article  PubMed Central  Google Scholar 

  • 92.

    Titeux, N. et al. Ecological traps and species distribution models: a challenge for prioritizing areas of conservation importance. Ecography 43, 365–375 (2020).

    Article  Google Scholar 

  • 93.

    Ceia-Hasse, A., Sinervo, B., Vicente, L. & Pereira, H. M. Integrating ecophysiological models into species distribution projections of European reptile range shifts in response to climate change. Ecography 37, 679–688 (2014).

    Article  Google Scholar 

  • 94.

    Sinervo, B. et al. Erosion of lizard diversity by climate change and altered thermal niches. Science 328, 894–899 (2010).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 95.

    Slatyer, R. A., Nash, M. A. & Hoffmann, A. A. Measuring the effects of reduced snow cover on Australia’s alpine arthropods. Austral Ecol. 42, 844–857 (2017).

    Article  Google Scholar 

  • 96.

    Cardoso, P. et al. Scientists’ warning to humanity on insect extinctions. Biol. Conserv. 242, 108426 (2020).

    Article  Google Scholar 

  • 97.

    Samways, M. J. et al. Solutions for humanity on how to conserve insects. Biol. Conserv. 242, 108427 (2020).

    Article  Google Scholar 

  • 98.

    Prieto-Benítez, S. & Méndez, M. Effects of land management on the abundance and richness of spiders (Araneae): a meta-analysis. Biol. Conserv. 144, 683–691 (2011).

    Article  Google Scholar 

  • 99.

    Marc, P., Canard, A. & Ysnel, F. Spiders (Araneae) useful for pest limitation and bioindication. Agric. Ecosyst. Environ. 74, 229–273 (1999).

    Article  Google Scholar 

  • 100.

    Noss, R. F. & Daly, K. M. Incorporating connectivity into broad-scale conservation planning. In Connectivity Conservation (eds Crooks, K. R. et al.) 587–619 (Cambridge University Press, Cambridge, 2006). https://doi.org/10.1017/CBO9780511754821.026.

    Google Scholar 

  • 101.

    World Conservation Monitoring Centre. The IUCN Red List of Threatened Species 1996 (1996).

  • 102.

    Dunnington, D. ggspatial: Spatial Data Framework for ggplot2. https://CRAN.R-project.org/package=ggspatial (2020).

  • 103.

    Wickham, H. ggplot2: elegant graphics for data analysis (Springer, New York, 2016).

    Google Scholar 

  • 104.

    South, A. rnaturalearth: World Map Data from Natural Earth. https://CRAN.R-project.org/package=rnaturalearth (2017).

  • 105.

    Kassambara, A. ggpubr: ‘ggplot2’ Based Publication Ready Plots. https://CRAN.R-project.org/package=ggpubr (2020).


  • Source: Ecology - nature.com

    Acidobacteria are active and abundant members of diverse atmospheric H2-oxidizing communities detected in temperate soils

    Undergraduates ramp up research during pandemic diaspora