test.json

[
  {"id":"devi10dme","type":"article-journal","title":"Defining and measuring ecological specialization","container-title":"Journal of Applied Ecology","page":"15-25","volume":"47","issue":"1","DOI":"10.1111/j.1365-2664.2009.01744.x","author":[{"family":"Devictor","given":"Vincent"},{"family":"Clavel","given":"Joanne"},{"family":"Julliard","given":"Romain"},{"family":"Lavergne","given":"Sébastien"},{"family":"Mouillot","given":"David"},{"family":"Thuiller","given":"Wilfried"},{"family":"Venail","given":"Patrick"},{"family":"Villéger","given":"Sébastien"},{"family":"Mouquet","given":"Nicolas"}],"issued":{"date-parts":[[2010,2]]}},
  {"id":"cana14een","type":"article-journal","title":"Empirical Evaluation of Neutral Interactions in Host-Parasite Networks","container-title":"The American Naturalist","page":"468-479","volume":"183","issue":"4","DOI":"10.1086/675363","author":[{"family":"Canard","given":"E. F."},{"family":"Mouquet","given":"N."},{"family":"Mouillot","given":"D."},{"family":"Stanko","given":"M."},{"family":"Miklisova","given":"D."},{"family":"Gravel","given":"D."}],"issued":{"date-parts":[[2014,4]]}},
  {"id":"have92ssn","type":"article-journal","title":"Scale and Structure in Natural Food Webs","container-title":"Science","page":"1107-1109","volume":"257","issue":"5073","DOI":"10.1126/science.257.5073.1107","author":[{"family":"Havens","given":"K."}],"issued":{"date-parts":[[1992,8,21]]}},
  {"id":"troj15gvm","type":"article-journal","title":"Geographical variation in mutualistic networks: similarity, turnover and partner fidelity","container-title":"Proceedings of the Royal Society B: Biological Sciences","page":"20142925-20142925","volume":"282","issue":"1802","DOI":"10.1098/rspb.2014.2925","author":[{"family":"Trojelsgaard","given":"K."},{"family":"Jordano","given":"P."},{"family":"Carstensen","given":"D. W."},{"family":"Olesen","given":"J. M."}],"issued":{"date-parts":[[2015,1,28]]}},
  {"id":"grav11tti","type":"article-journal","title":"Trophic theory of island biogeography","container-title":"Ecology Letters","page":"1010-1016","volume":"14","issue":"10","DOI":"10.1111/j.1461-0248.2011.01667.x","author":[{"family":"Gravel","given":"Dominique"},{"family":"Massol","given":"François"},{"family":"Canard","given":"Elsa"},{"family":"Mouillot","given":"David"},{"family":"Mouquet","given":"Nicolas"}],"issued":{"date-parts":[[2011,8,2]]}},
  {"id":"kauf90pmp","type":"chapter","title":"Partitioning Around Medoids (Program PAM)","container-title":"Finding Groups in Data","publisher":"John Wiley & Sons, Inc.","page":"68-125","source":"Wiley Online Library","abstract":"The prelims comprise:\n\n\n*\nShort Description of the Method\n\n\n*\nHow to Use the Program PAM\n\n\n*\nExamples\n\n\n*\nMore on the Algorithm and the Program\n\n\n*\nRelated Methods and References","URL":"http://onlinelibrary.wiley.com/doi/10.1002/9780470316801.ch2/summary","ISBN":"978-0-470-31680-1","language":"en","author":[{"family":"Kaufman","given":"Leonard"},{"family":"Rousseeuw","given":"Peter J."}],"issued":{"date-parts":[[1990]]},"accessed":{"date-parts":[["2016",11,7]]}},
  {"id":"arau13gsb","type":"article-journal","title":"The geographic scaling of biotic interactions","container-title":"Ecography","page":"no-no","DOI":"10.1111/j.1600-0587.2013.00643.x","author":[{"family":"Araújo","given":"Miguel B."},{"family":"Rozenfeld","given":"Alejandro"}],"issued":{"date-parts":[[2013,12]]}},
  {"id":"lali10dfm","type":"article-journal","title":"A distance-based framework for measuring functional diversity from multiple traits","container-title":"Ecology","page":"299-305","volume":"91","issue":"1","DOI":"10.1890/08-2244.1","author":[{"family":"Laliberté","given":"Etienne"},{"family":"Legendre","given":"Pierre"}],"issued":{"date-parts":[[2010,1]]}},
  {"id":"hijm05vhr","type":"article-journal","title":"Very high resolution interpolated climate surfaces for global land areas","container-title":"International Journal of Climatology","page":"1965-1978","volume":"25","issue":"15","source":"Wiley Online Library","abstract":"We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledge-based methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright © 2005 Royal Meteorological Society.","URL":"http://onlinelibrary.wiley.com/doi/10.1002/joc.1276/abstract","DOI":"10.1002/joc.1276","ISSN":"1097-0088","language":"en","author":[{"family":"Hijmans","given":"Robert J."},{"family":"Cameron","given":"Susan E."},{"family":"Parra","given":"Juan L."},{"family":"Jones","given":"Peter G."},{"family":"Jarvis","given":"Andy"}],"issued":{"date-parts":[[2005,12,1]]},"accessed":{"date-parts":[["2016",9,2]]},"container-title-short":"Int. J. Climatol."},
  {"id":"pois13fop","type":"article-journal","title":"Facultative and obligate parasite communities exhibit different network properties","container-title":"Parasitology","page":"1340-1345","volume":"140","issue":"11","source":"PubMed","abstract":"Network theory is gaining momentum as a descriptive tool in community ecology. Because organisms with the same lifestyle can still exhibit ecological differences, it is crucial to determine the scale at which networks should be described. Here we show that networks of hosts (mammals) and parasites (ectoparasitic gamasid mites) differ when either facultative or obligatory parasites only are considered. More importantly, the structure of these networks is opposed, with obligatory parasites networks being more modular, and facultative parasites networks being more nested. Our results have consequences for the way we define which species to include in ecological networks, which we discuss in the light of community ecology and epidemiology.","DOI":"10.1017/S0031182013000851","ISSN":"1469-8161","language":"ENG","author":[{"family":"Poisot","given":"Timothée"},{"family":"Stanko","given":"Michal"},{"family":"Miklisová","given":"Dana"},{"family":"Morand","given":"Serge"}],"issued":{"date-parts":[[2013,9]]},"accessed":{"date-parts":[["2014",11,3]]},"container-title-short":"Parasitology"},
  {"id":"bloi14fei","type":"article-journal","title":"A framework for evaluating the influence of climate, dispersal limitation, and biotic interactions using fossil pollen associations across the late Quaternary","container-title":"Ecography","page":"n/a-n/a","DOI":"10.1111/ecog.00779","language":"en","author":[{"family":"Blois","given":"Jessica L."},{"family":"Gotelli","given":"Nicholas J."},{"family":"Behrensmeyer","given":"Anna K."},{"family":"Faith","given":"J. Tyler"},{"family":"Lyons","given":"S. Kathleen"},{"family":"Williams","given":"John W."},{"family":"Amatangelo","given":"Kathryn L."},{"family":"Bercovici","given":"Antoine"},{"family":"Du","given":"Andrew"},{"family":"Eronen","given":"Jussi T."},{"family":"Graves","given":"Gary R."},{"family":"Jud","given":"Nathan"},{"family":"Labandeira","given":"Conrad"},{"family":"Looy","given":"Cindy V."},{"family":"McGill","given":"Brian"},{"family":"Patterson","given":"David"},{"family":"Potts","given":"Richard"},{"family":"Riddle","given":"Brett"},{"family":"Terry","given":"Rebecca"},{"family":"Tóth","given":"Anikó"},{"family":"Villaseñor","given":"Amelia"},{"family":"Wing","given":"Scott"}],"issued":{"date-parts":[[2014,7]]}},
  {"id":"olit15sta","type":"article-journal","title":"Species traits and abundances predict metrics of plantpollinator network structure, but not pairwise interactions","container-title":"Oikos","page":"428-436","volume":"124","DOI":"10.1111/oik.01439","author":[{"family":"Olito","given":"Colin"},{"family":"Fox","given":"Jeremy W."}],"issued":{"date-parts":[[2015]]},"accessed":{"date-parts":[["2015",1,19]]}},
  {"id":"bart16cfi","type":"article-journal","title":"A common framework for identifying linkage rules across different types of interactions","container-title":"Functional Ecology","page":"1894-1903","volume":"30","issue":"12","source":"Wiley Online Library","abstract":"* Species interactions, ranging from antagonisms to mutualisms, form the architecture of biodiversity and determine ecosystem functioning. Understanding the rules responsible for who interacts with whom, as well as the functional consequences of these interspecific interactions, is central to predict community dynamics and stability.\n\n\n* Species traits sensu lato may affect different ecological processes by determining species interactions through a two-step process. First, ecological and life-history traits govern species distributions and abundance, and hence determine species co-occurrence and the potential for species to interact. Secondly, morphological or physiological traits between co-occurring potential interaction partners should match for the realization of an interaction. Here, we review recent advances on predicting interactions from species co-occurrence and develop a probabilistic model for inferring trait matching.\n\n\n* The models proposed here integrate both neutral and trait-matching constraints, while using only information about known interactions, thereby overcoming problems originating from undersampling of rare interactions (i.e. missing links). They can easily accommodate qualitative or quantitative data and can incorporate trait variation within species, such as values that vary along developmental stages or environmental gradients.\n\n\n* We use three case studies to show that the proposed models can detect strong trait matching (e.g. predator–prey system), relaxed trait matching (e.g. herbivore–plant system) and barrier trait matching (e.g. plant–pollinator systems).\n\n\n* Only by elucidating which species traits are important in each process (i.e. in determining interaction establishment and frequency), we can advance in explaining how species interact and the consequences of these interactions for ecosystem functioning.","URL":"http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.12666/abstract","DOI":"10.1111/1365-2435.12666","ISSN":"1365-2435","language":"en","author":[{"family":"Bartomeus","given":"Ignasi"},{"family":"Gravel","given":"Dominique"},{"family":"Tylianakis","given":"Jason M."},{"family":"Aizen","given":"Marcelo A."},{"family":"Dickie","given":"Ian A."},{"family":"Bernard-Verdier","given":"Maud"}],"issued":{"date-parts":[[2016,5,1]]},"accessed":{"date-parts":[["2016",9,2]]},"container-title-short":"Funct Ecol"},
  {"id":"mcgi06rce","type":"article-journal","title":"Rebuilding community ecology from functional traits.","container-title":"Trends Ecol. Evol.","page":"178-185","volume":"21","issue":"4","DOI":"10.1016/j.tree.2006.02.002","author":[{"family":"McGill","given":"Brian J"},{"family":"Enquist","given":"Brian J"},{"family":"Weiher","given":"Evan"},{"family":"Westoby","given":"Mark"}],"issued":{"date-parts":[[2006,4]]}},
  {"id":"lege12ne","type":"book","title":"Numerical ecology","collection-title":"Developments in environmental modelling","collection-number":"Developments in environmental modelling","publisher":"Elsevier","publisher-place":"Oxford, UK","volume":"20","number-of-pages":"990","edition":"Third English edition","event-place":"Oxford, UK","language":"eng","author":[{"family":"Legendre","given":"Pierre"},{"family":"Legendre","given":"Louis"}],"issued":{"date-parts":[[2012]]},"archive-place":"Oxford, UK"},
  {"id":"cars14bdp","type":"article-journal","title":"Beta Diversity of Plant-Pollinator Networks and the Spatial Turnover of Pairwise Interactions","container-title":"PLoS ONE","page":"e112903","volume":"9","issue":"11","DOI":"10.1371/journal.pone.0112903","author":[{"family":"Carstensen","given":"Daniel W."},{"family":"Sabatino","given":"Malena"},{"family":"Trøjelsgaard","given":"Kristian"},{"family":"Morellato","given":"Leonor Patricia C."}],"issued":{"date-parts":[[2014,11,10]]}},
  {"id":"hadf14ttp","type":"article-journal","title":"A Tale of Two Phylogenies: Comparative Analyses of Ecological Interactions","container-title":"The American Naturalist","page":"174-187","volume":"183","issue":"2","DOI":"10.1086/674445","author":[{"family":"Hadfield","given":"Jarrod D."},{"family":"Krasnov","given":"Boris R."},{"family":"Poulin","given":"Robert"},{"family":"Nakagawa","given":"Shinichi"}],"issued":{"date-parts":[[2014,1]]},"accessed":{"date-parts":[["2014",1,23]]}},
  {"id":"oles11mfl","type":"article-journal","title":"Missing and forbidden links in mutualistic networks","container-title":"Proc. R. Soc. B","page":"725-732","volume":"278","issue":"1706","DOI":"10.1098/rspb.2010.1371","author":[{"family":"Olesen","given":"Jens M."},{"family":"Bascompte","given":"Jordi"},{"family":"Dupont","given":"Yoko L."},{"family":"Elberling","given":"Heidi"},{"family":"Rasmussen","given":"Claus"},{"family":"Jordano","given":"Pedro"}],"issued":{"date-parts":[[2011,3]]},"accessed":{"date-parts":[["2014",10,7]]}},
  {"id":"troj16enm","type":"article-journal","title":"Ecological networks in motion: micro- and macroscopic variability across scales","container-title":"Functional Ecology","page":"1926-1935","volume":"30","issue":"12","source":"Wiley Online Library","abstract":"* There has been an intense focus on the response of species to environmental changes, and more recently, the interactions of species have been examined in a similar way in order to understand the stability of entire communities and networks of interacting species. As a consequence, ecological networks have been placed in spatial and temporal contexts in order to reveal what may drive network variability. Understanding the spatial and temporal variability of ecological networks, and in particular the underlying forces facilitating changes, seems pertinent in our attempts to understand and anticipate how ecological networks may vary and respond to future environmental scenarios.\n\n\n* Network variability has been studied at widely differing temporal and spatial scales. For example, studies exploring temporal variability ranges from within-season comparisons to comparisons over vast geological time spans, and the spatial extent ranges from the scale of a single pond to global analyses. Here, we highlight the outcomes from such studies and emphasize the identified mechanisms driving spatio-temporal variability in ecological networks. Specifically, we describe how ecological networks vary over different temporal (years, centuries and millennia) and spatial (local, regional and global) scales, discuss how this variability is monitored and identify potential future directions.\n\n\n* Present knowledge allows some tentative generalizations. First, ecological networks tend to exhibit considerable spatial and temporal stability in several macroscopic features (e.g. connectance, nestedness), but studies also show that macroscopic features may change, for example, in relation to mass extinction or steep environmental gradients. Secondly, microscopic features (e.g. individual specialization levels, species roles and partner affiliations), albeit less studied, seem to show strong variability, and in several cases, microscopic instability co-occurs with macroscopic stability. We therefore recommend a stronger focus on this macro–micro interplay and list ideas (e.g. temporal species centrality measures and interaction phenologies), towards expanding the microscopic toolbox of network ecologists.","URL":"http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.12710/abstract","DOI":"10.1111/1365-2435.12710","ISSN":"1365-2435","language":"en","author":[{"family":"Trøjelsgaard","given":"Kristian"},{"family":"Olesen","given":"Jens M."}],"issued":{"date-parts":[[2016,7,1]]},"accessed":{"date-parts":[["2016",9,1]]},"title-short":"Ecological networks in motion","container-title-short":"Funct Ecol"},
  {"id":"pois16spn","type":"article-journal","title":"The structure of probabilistic networks","container-title":"Methods in Ecology and Evolution","page":"303-312","volume":"7","issue":"3","source":"CrossRef","URL":"http://doi.wiley.com/10.1111/2041-210X.12468","DOI":"10.1111/2041-210X.12468","ISSN":"2041210X","language":"en","author":[{"family":"Poisot","given":"Timothée"},{"family":"Cirtwill","given":"Alyssa R."},{"family":"Cazelles","given":"Kévin"},{"family":"Gravel","given":"Dominique"},{"family":"Fortin","given":"Marie-Josée"},{"family":"Stouffer","given":"Daniel B."}],"editor":[{"family":"Vamosi","given":"Jana"}],"issued":{"date-parts":[[2016,3]]},"accessed":{"date-parts":[["2016",10,12]]}},
  {"id":"pois15swe","type":"article-journal","title":"Beyond species: why ecological interaction networks vary through space and time","container-title":"Oikos","page":"243–251","volume":"124","issue":"3","source":"Google Scholar","URL":"http://onlinelibrary.wiley.com/doi/10.1111/oik.01719/full","DOI":"10.1111/oik.01719","author":[{"family":"Poisot","given":"Timothée"},{"family":"Stouffer","given":"Daniel B."},{"family":"Gravel","given":"Dominique"}],"issued":{"date-parts":[[2015]]},"accessed":{"date-parts":[["2016",9,2]]},"title-short":"Beyond species"},
  {"id":"pois12dsi","type":"article-journal","title":"The dissimilarity of species interaction networks","container-title":"Ecology Letters","page":"1353–1361","volume":"15","issue":"12","source":"Google Scholar","abstract":"In a context of global changes, and amidst the perpetual modification of community structure undergone by most natural ecosystems, it is more important than ever to understand how species interactions vary through space and time. The integration of biogeography and network theory will yield important results and further our understanding of species interactions. It has, however, been hampered so far by the difficulty to quantify variation among interaction networks. Here, we propose a general framework to study the dissimilarity of species interaction networks over time, space or environments, allowing both the use of quantitative and qualitative data. We decompose network dissimilarity into interactions and species turnover components, so that it is immediately comparable to common measures of β-diversity. We emphasise that scaling up β-diversity of community composition to the β-diversity of interactions requires only a small methodological step, which we foresee will help empiricists adopt this method. We illustrate the framework with a large dataset of hosts and parasites interactions and highlight other possible usages. We discuss a research agenda towards a biogeographical theory of species interactions.","URL":"http://onlinelibrary.wiley.com/doi/10.1111/ele.12002/full","DOI":"10.1111/ele.12002","ISSN":"1461023X","language":"ENG","author":[{"family":"Poisot","given":"Timothée"},{"family":"Canard","given":"Elsa"},{"family":"Mouillot","given":"David"},{"family":"Mouquet","given":"Nicolas"},{"family":"Gravel","given":"Dominique"}],"issued":{"date-parts":[[2012]]},"accessed":{"date-parts":[["2016",9,2]]},"container-title-short":"Ecol. Lett."},
  {"id":"coux16lsf","type":"article-journal","title":"Linking species functional roles to their network roles","container-title":"Ecology Letters","page":"762-770","volume":"19","issue":"7","DOI":"10.1111/ele.12612","language":"en","author":[{"family":"Coux","given":"Camille"},{"family":"Rader","given":"Romina"},{"family":"Bartomeus","given":"Ignasi"},{"family":"Tylianakis","given":"Jason M."}],"issued":{"date-parts":[[2016,5]]}},
  {"id":"rose69ped","type":"article-journal","title":"Population Ecology of Desert Rodent Communities: Habitats and Environmental Complexity","container-title":"Ecology","page":"558-572","volume":"50","issue":"4","source":"onlinelibrary.wiley.com","URL":"http://onlinelibrary.wiley.com/doi/10.2307/1936246/abstract","DOI":"10.2307/1936246","ISSN":"1939-9170","language":"en","author":[{"family":"Rosenzweig","given":"Michael L."},{"family":"Winakur","given":"Jerald"}],"issued":{"date-parts":[[1969,7,1]]},"accessed":{"date-parts":[["2017",1,20]]},"title-short":"Population Ecology of Desert Rodent Communities"},
  {"id":"bord15hfa","type":"article-journal","title":"Habitat fragmentation alters the properties of a host–parasite network: rodents and their helminths in South-East Asia","container-title":"Journal of Animal Ecology","page":"1253-1263","volume":"84","issue":"5","source":"Wiley Online Library","abstract":"* While the effects of deforestation and habitat fragmentation on parasite prevalence or richness are well investigated, host–parasite networks are still understudied despite their importance in understanding the mechanisms of these major disturbances. Because fragmentation may negatively impact species occupancy, abundance and co-occurrence, we predict a link between spatiotemporal changes in habitat and the architecture of host–parasite networks.\n\n\n* For this, we used an extensive data set on 16 rodent species and 29 helminth species from seven localities of South-East Asia. We analysed the effects of rapid deforestation on connectance and modularity of helminth–parasite networks. We estimated both the degree of fragmentation and the rate of deforestation through the development of land uses and their changes through the last 20 to 30 years in order to take into account the dynamics of habitat fragmentation in our statistical analyses.\n\n\n* We found that rapid fragmentation does not affect helminth species richness per se but impacts host–parasite interactions as the rodent–helminth network becomes less connected and more modular.\n\n\n* Our results suggest that parasite sharing among host species may become more difficult to maintain with the increase of habitat disturbance.","URL":"http://onlinelibrary.wiley.com/doi/10.1111/1365-2656.12368/abstract","DOI":"10.1111/1365-2656.12368","ISSN":"1365-2656","language":"en","author":[{"family":"Bordes","given":"Frédéric"},{"family":"Morand","given":"Serge"},{"family":"Pilosof","given":"Shai"},{"family":"Claude","given":"Julien"},{"family":"Krasnov","given":"Boris R."},{"family":"Cosson","given":"Jean-François"},{"family":"Chaval","given":"Yannick"},{"family":"Ribas","given":"Alexis"},{"family":"Chaisiri","given":"Kittipong"},{"family":"Blasdell","given":"Kim"},{"family":"Herbreteau","given":"Vincent"},{"family":"Dupuy","given":"Stéphane"},{"family":"Tran","given":"Annelise"}],"issued":{"date-parts":[[2015,9,1]]},"accessed":{"date-parts":[["2017",1,20]]},"title-short":"Habitat fragmentation alters the properties of a host–parasite network","container-title-short":"J Anim Ecol"},
  {"id":"kotl84rps","type":"article-journal","title":"Risk of Predation and the Structure of Desert Rodent Communities","container-title":"Ecology","page":"689-701","volume":"65","issue":"3","source":"CrossRef","URL":"http://doi.wiley.com/10.2307/1938041","DOI":"10.2307/1938041","ISSN":"00129658","language":"en","author":[{"family":"Kotler","given":"Burt P."}],"issued":{"date-parts":[[1984,6]]},"accessed":{"date-parts":[["2017",1,20]]}},
  {"id":"kotl88ehc","type":"article-journal","title":"Environmental Heterogeneity and the Coexistence of Desert Rodents","container-title":"Annual Review of Ecology and Systematics","page":"281-307","volume":"19","issue":"1","source":"CrossRef","URL":"http://www.annualreviews.org/doi/10.1146/annurev.es.19.110188.001433","DOI":"10.1146/annurev.es.19.110188.001433","ISSN":"0066-4162","language":"en","author":[{"family":"Kotler","given":"B P"},{"family":"Brown","given":"J S"}],"issued":{"date-parts":[[1988,11]]},"accessed":{"date-parts":[["2017",1,20]]}},
  {"id":"aars02icd","type":"article-journal","title":"Intrinsic and climatic determinants of population demography: the winter dynamics of tundra voles","container-title":"Ecology","page":"3449–3456","volume":"83","issue":"12","source":"Google Scholar","URL":"http://onlinelibrary.wiley.com/doi/10.1890/0012-9658(2002)083%5B3449:IACDOP%5D2.0.CO;2/full","author":[{"family":"Aars","given":"Jon"},{"family":"Ims","given":"Rolf A"}],"issued":{"date-parts":[[2002]]},"accessed":{"date-parts":[["2017",1,20]]},"title-short":"Intrinsic and climatic determinants of population demography"},
  {"id":"bozi89mmr","type":"article-journal","title":"Maximum metabolic rate of rodents: physiological and ecological consequences on distributional limits","container-title":"Functional Ecology","page":"173–181","source":"Google Scholar","URL":"http://www.jstor.org/stable/2389298","author":[{"family":"Bozinovic","given":"F."},{"family":"Rosenmann","given":"M."}],"issued":{"date-parts":[[1989]]},"accessed":{"date-parts":[["2017",1,20]]},"title-short":"Maximum metabolic rate of rodents"},
  {"id":"lege14smt","type":"article-journal","title":"Statistical methods for temporal and space-time analysis of community composition data","container-title":"Proceedings of the Royal Society B: Biological Sciences","page":"20132728-20132728","volume":"281","issue":"1778","source":"CrossRef","URL":"http://rspb.royalsocietypublishing.org/cgi/doi/10.1098/rspb.2013.2728","DOI":"10.1098/rspb.2013.2728","ISSN":"0962-8452, 1471-2954","language":"en","author":[{"family":"Legendre","given":"Pierre"},{"family":"Gauthier","given":"O."}],"issued":{"date-parts":[[2014,1,15]]},"accessed":{"date-parts":[["2017",1,20]]}},
  {"id":"dec13dms","type":"article-journal","title":"Dissimilarity measurements and the size structure of ecological communities","container-title":"Methods in Ecology and Evolution","page":"1167-1177","volume":"4","issue":"12","source":"CrossRef","URL":"http://doi.wiley.com/10.1111/2041-210X.12116","DOI":"10.1111/2041-210X.12116","ISSN":"2041210X","language":"en","author":[{"family":"De Cáceres","given":"Miquel"},{"family":"Legendre","given":"Pierre"},{"family":"He","given":"Fangliang"}],"editor":[{"family":"Faith","given":"Daniel"}],"issued":{"date-parts":[[2013,12]]},"accessed":{"date-parts":[["2017",1,20]]}},
  {"id":"pois16mme","type":"article-journal","title":"mangal - making ecological network analysis simple","container-title":"Ecography","page":"384-390","volume":"39","issue":"4","source":"CrossRef","URL":"http://doi.wiley.com/10.1111/ecog.00976","DOI":"10.1111/ecog.00976","ISSN":"09067590","language":"en","author":[{"family":"Poisot","given":"Timothée"},{"family":"Baiser","given":"Benjamin"},{"family":"Dunne","given":"Jennifer A."},{"family":"Kéfi","given":"Sonia"},{"family":"Massol","given":"François"},{"family":"Mouquet","given":"Nicolas"},{"family":"Romanuk","given":"Tamara N."},{"family":"Stouffer","given":"Daniel B."},{"family":"Wood","given":"Spencer A."},{"family":"Gravel","given":"Dominique"}],"issued":{"date-parts":[[2016,4]]},"accessed":{"date-parts":[["2017",1,20]]}},
  {"id":"kras04gvh","type":"article-journal","title":"Geographical variation in host specificity of fleas (Siphonaptera) parasitic on small mammals: the influence of phylogeny and local environmental conditions","container-title":"Ecography","page":"787-797","volume":"27","issue":"6","source":"Wiley Online Library","abstract":"The evolution of host specificity remains a central issue in the study of host-parasite relationships. Here we tackle three basic questions about host specificity using data on host use by fleas (Siphonaptera) from 21 geographical regions. First, are the host species exploited by a flea species no more than a random draw from the locally available host species, or do they form a taxonomically distinct subset? Using randomization tests, we showed that in the majority of cases, the taxonomic distinctness (measured as the average taxonomic distances among host species) of the hosts exploited by a flea is no different from that of random subsets of hosts taken from the regional pool. In the several cases where a difference was found, the taxonomic distinctness of the hosts used by a flea was almost always lower than that of the random subsets, suggesting that the parasites use hosts within a narrower taxonomic spectrum than what is available to them. Second, given the variation in host specificity among populations of the same flea species, is host specificity truly a species character? We found that host specificity measures are repeatable among different populations of the same flea species: host specificity varies significantly more among flea species than within flea species. This was true for both measures of host specificity used in the analyses: the number of host species exploited, and the index measuring the average taxonomic distinctness of the host species and its variance. Third, what causes geographical variation in host specificity among populations of the same flea species? In the vast majority of flea species, neither of our two measures of host specificity correlated with either the regional number of potential host species or their taxonomic distinctness, or the distance between the sampled region and the center of the flea's geographical range. However, in most flea species host specificity correlated with measures of the deviation in climatic conditions (precipitation and temperature) between the sampled region and the average conditions computed across the flea's entire range. Overall, these results suggest that host specificity in fleas is to a large extent phylogenetically constrained, while still strongly influenced by local environmental conditions.","URL":"http://onlinelibrary.wiley.com/doi/10.1111/j.0906-7590.2004.04015.x/abstract","DOI":"10.1111/j.0906-7590.2004.04015.x","ISSN":"1600-0587","language":"en","author":[{"family":"Krasnov","given":"Boris R."},{"family":"Mouillot","given":"David"},{"family":"Shenbrot","given":"Georgy I."},{"family":"Khokhlova","given":"Irina S."},{"family":"Poulin","given":"Robert"}],"issued":{"date-parts":[[2004,12,1]]},"accessed":{"date-parts":[["2017",1,20]]},"title-short":"Geographical variation in host specificity of fleas (Siphonaptera) parasitic on small mammals","container-title-short":"Ecography"},
  {"id":"lege13bdv","type":"article-journal","title":"Beta diversity as the variance of community data: dissimilarity coefficients and partitioning","container-title":"Ecology Letters","page":"951-963","volume":"16","issue":"8","source":"CrossRef","URL":"http://doi.wiley.com/10.1111/ele.12141","DOI":"10.1111/ele.12141","ISSN":"1461023X","language":"en","author":[{"family":"Legendre","given":"Pierre"},{"family":"De Cáceres","given":"Miquel"}],"editor":[{"family":"Morlon","given":"Hélène"}],"issued":{"date-parts":[[2013,8]]},"accessed":{"date-parts":[["2017",1,25]]},"title-short":"Beta diversity as the variance of community data"},
  {"id":"boul12adb","type":"article-journal","title":"Accounting for dispersal and biotic interactions to disentangle the drivers of species distributions and their abundances","container-title":"Ecology Letters","page":"584-593","volume":"15","issue":"6","source":"PubMed","abstract":"Although abiotic factors, together with dispersal and biotic interactions, are often suggested to explain the distribution of species and their abundances, species distribution models usually focus on abiotic factors only. We propose an integrative framework linking ecological theory, empirical data and statistical models to understand the distribution of species and their abundances together with the underlying community assembly dynamics. We illustrate our approach with 21 plant species in the French Alps. We show that a spatially nested modelling framework significantly improves the model's performance and that the spatial variations of species presence-absence and abundances are predominantly explained by different factors. We also show that incorporating abiotic, dispersal and biotic factors into the same model bring new insights to our understanding of community assembly. This approach, at the crossroads between community ecology and biogeography, is a promising avenue for a better understanding of species co-existence and biodiversity distribution.","DOI":"10.1111/j.1461-0248.2012.01772.x","ISSN":"1461-0248","language":"eng","author":[{"family":"Boulangeat","given":"Isabelle"},{"family":"Gravel","given":"Dominique"},{"family":"Thuiller","given":"Wilfried"}],"issued":{"date-parts":[[2012,6]]},"PMID":"22462813","PMCID":"PMC3999639","container-title-short":"Ecol. Lett."},
  {"id":"lege14irr","type":"article-journal","title":"Interpreting the replacement and richness difference components of beta diversity: Replacement and richness difference components","container-title":"Global Ecology and Biogeography","page":"1324-1334","volume":"23","issue":"11","source":"CrossRef","URL":"http://doi.wiley.com/10.1111/geb.12207","DOI":"10.1111/geb.12207","ISSN":"1466822X","language":"en","author":[{"family":"Legendre","given":"Pierre"}],"issued":{"date-parts":[[2014,11]]},"accessed":{"date-parts":[["2017",1,27]]},"title-short":"Interpreting the replacement and richness difference components of beta diversity"},
  {"id":"vize14pei","type":"article-journal","title":"Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird-plant network","container-title":"Proceedings of the Royal Society B: Biological Sciences","page":"20132397-20132397","volume":"281","issue":"1780","source":"CrossRef","URL":"http://rspb.royalsocietypublishing.org/cgi/doi/10.1098/rspb.2013.2397","DOI":"10.1098/rspb.2013.2397","ISSN":"0962-8452, 1471-2954","language":"en","author":[{"family":"Vizentin-Bugoni","given":"J."},{"family":"Maruyama","given":"P. K."},{"family":"Sazima","given":"M."}],"issued":{"date-parts":[[2014,2,19]]},"accessed":{"date-parts":[["2017",1,27]]},"title-short":"Processes entangling interactions in communities"},
  {"id":"hadf13dft","type":"article-journal","title":"Data from: A tale of two phylogenies: comparative analyses of ecological interactions","source":"datadryad.org","archive":"Dryad Digital Repository","abstract":"The evolution of traits involved in ecological interactions such as predator-prey, host-parasite, and plant-pollinator interactions, are likely to be shaped by the phylogenetic history of both parties. We develop generalized linear mixed-effects models (GLMM) that estimate the effect of both parties’ phylogenetic history on trait evolution, both in isolation but also in terms of how the two histories interact. Using data on the incidence and abundance of 206 flea species on 121 mammal species, we illustrate our method and compare it to previously used methods for detecting host-parasite coevolution. At large spatial scales we find that the phylogenetic interaction effect was substantial, indicating that related parasite species were more likely to be found on related host species. At smaller spatial scales, and when sampling effort was not controlled for, phylogenetic effects on the number and types of parasite species harbored by hosts were found to dominate. We go on to show that in situations where these additional phylogenetic effects exist, then previous methods have very high Type I error rates when testing for the phylogenetic interaction. Our GLMM method represents a robust and reliable approach to quantify the phylogenetic effects of traits determined by, or defined by, ecological interactions and has the advantage that it can easily be extended and interpreted in a broader context than existing permutation tests.","DOI":"10.5061/dryad.jf3tj","note":"{:itemType: dataset}","author":[{"family":"Hadfield","given":"Jarrod D."},{"family":"Krasnov","given":"Boris R."},{"family":"Poulin","given":"Robert"},{"family":"Shinichi","given":"Nakagawa"}],"issued":{"date-parts":[[2013,12,30]]},"accessed":{"date-parts":[["2017",1,27]]}},
  {"id":"lege01emt","type":"article-journal","title":"Ecologically meaningful transformations for ordination of species data","container-title":"Oecologia","page":"271-280","volume":"129","issue":"2","source":"CrossRef","URL":"http://link.springer.com/10.1007/s004420100716","DOI":"10.1007/s004420100716","ISSN":"0029-8549, 1432-1939","author":[{"family":"Legendre","given":"Pierre"},{"family":"Gallagher","given":"Eugene"}],"issued":{"date-parts":[[2001,10,1]]},"accessed":{"date-parts":[["2017",1,27]]}}
]