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The question of whether migratory birds track a specific climatic niche by seasonal movements has important implications for understanding the evolution of migration, the factors affecting species' distributions, and the responses of migrants to climate change. Despite much research, previous studies of bird migration have produced mixed results. However, whether migrants track climate is only one half of the question, the other being why residents remain in the same geographic range year‐round. We provide a literature overview and test the hypothesis of seasonal niche tracking by evaluating seasonal climatic niche overlap across 437 migratory and resident species from eight clades of passerine birds. Seasonal climatic niches were based on a new global dataset of breeding and nonbreeding ranges. Overlap between climatic niches was quantified using ordination methods. We compared niche overlap of migratory species to two null expectations, (a) a scenario in which they do not migrate and (b) in comparison with the overlap experienced by closely related resident species, while controlling for breeding location and range size. Partly in accordance with the hypothesis of niche tracking, we found that the overlap of breeding versus nonbreeding climatic conditions in migratory species was greater than the overlap they would experience if they did not migrate. However, this was only true for migrants breeding outside the tropics and only relative to the overlap species would experience if they stayed in the breeding range year‐round. In contrast to the hypothesis of niche tracking, migratory species experienced lower seasonal climatic niche overlap than resident species, with significant differences between tropical and nontropical species. Our study suggests that in seasonal nontropical environments migration away from the breeding range may serve to avoid seasonally harsh climate; however, different factors may drive seasonal movements in the climatically more stable tropical regions., By examining seasonal niche overlap in migratory and resident bird species, we show that niche tracking varies depending on (a) the perspective in which the question was examined (i.e., from the perspective of the individual migrant or in comparison with resident species, (b) the direction of migration (i.e., whether the species is moving from the breeding or non‐breeding range), and (c) geographic location. Altogether, these results suggest that the drivers of migration vary depending on direction of migration as well as geographically, offering explanations for the mixed results from previous studies.

Although the links between species richness and diversification rates with clade age have been studied extensively, few studies have investigated the relationship between the rates of trait evolution and clade age. The rate of morphological trait evolution has repeatedly been shown to vary through time, as expected, for example, for adaptive radiations, but the strength and sources of this variation are not well understood. We compare the relationship between the rates of trait evolution and clade age across eight monophyletic clades of passerine birds by investigating ecomorphological traits, i.e. morphological traits that influence the ecology of the species directly. We study the ecomorphological divergence pattern using analyses of the disparity through time and determine the best-fitting model of evolution for each trait in each clade. We find no support for a consistent dependence of evolutionary rates on clade age across wing, tail, tarsus and beak shape in our eight clades and also show that early burst models of trait evolution are rarely the best-fitting models within these clades. These results suggest that key innovations or adaptive radiations might be less common evolutionary patterns and processes than generally thought or might depend on the taxonomic level investigated.

AIM: We advocate an interdisciplinary approach to biogeography, integrating geology and paleobiology to examine how biodiversity dynamics evolved as mountain ranges formed through (geological) time. LOCATION: Global; case study: Anatolia (Turkey). METHODS: We discuss the links between surface uplift and biodiversity dynamics and review recent developments for reconstructing the history of geography and biodiversity. To illustrate an integrative approach to biogeography, we present a case study of Neogene Anatolia. In particular, we reconstruct Anatolian paleogeography based on a synthesis of both quantitative and qualitative evidence, and review the fossil record of the regional flora and fauna, to identify changes in compositions that might be induced by surface uplift and associated environmental changes. RESULTS: The Central Anatolian Plateau and its mountainous margins display different histories of surface uplift during the late Miocene to Pliocene, which are detectable in the regional fossil record of large mammals. Overall changes in vegetation and climatic conditions for the whole region also align with the general time frame of surface uplift. MAIN CONCLUSIONS: Our discussion and case study highlight the value of an integrative biogeographic framework, by combining knowledge and techniques from geology and paleobiology to simultaneously consider the biotic and environmental dynamics in space and time. Neogene surface uplift in Anatolia has affected the regional biota, particularly the diversity of plants and large mammals, along with well‐known global and regional changes in climate and other environmental factors. To disentangle the effects of different, but most likely interactive environmental changes at various scales, we call for rigorous examination of the geological record in a biogeographic framework, using innovative methods to uncover how environmental and biotic processes have shaped mountain biodiversity.

Linking pattern to process across spatial and temporal scales has been a key goal of the field of biogeography. In January 2017, the 8th biennial conference of the International Biogeography Society sponsored a symposium on Building up biogeography—process to pattern that aimed to review progress towards this goal. Here we present a summary of the symposium, in which we identified promising areas of current research and suggested future research directions. We focus on (1) emerging types of data such as behavioural observations and ancient DNA, (2) how to better incorporate historical data (such as fossils) to move beyond what we term “footprint measures” of past dynamics and (3) the role that novel modelling approaches (e.g. maximum entropy theory of ecology and approximate Bayesian computation) and conceptual frameworks can play in the unification of disciplines. We suggest that the gaps separating pattern and process are shrinking, and that we can better bridge these aspects by considering the dimensions of space and time simultaneously.

Due to concerns about data quality, McKechnie, Coe, Gerson, and Wolf (2016) questioned the conclusions of our study (Khaliq et al., 2015) published in this journal. Here, we argue that most of the questioned data points are in fact useful for macrophysiological analyses, mostly because the vast majority of data are explicitly reported in the peer-reviewed physiological literature. Furthermore, we show that our conclusions remain largely robust irrespective of the data inclusion criterion. While we think that constructive debates about the adequate use of primary data in meta-studies as well as more transparency in data inclusion criteria are indeed useful, we also emphasize that data suitability should be evaluated in the light of the scope and scale of the study in which they are used. We hope that this discussion will not discourage the exchange between disciplines such as biogeography and physiology, as this integration is needed to address some of the most urgent scientific challenges.

Speciation is thought to be predominantly driven by the geographical separation of populations of the ancestral species. Yet, in the marine realm, there is substantial biological diversity despite a lack of pronounced geographical barriers. Here, we investigate this paradox by considering the biogeography of marine mammals: cetaceans (whales and dolphins) and pinnipeds (seals and sea lions). We test for associations between past evolutionary diversification and current geographical distributions, after accounting for the potential effects of current environmental conditions. In general, cetacean lineages are widely dispersed and show few signs of geographically driven speciation, albeit with some notable exceptions. Pinnipeds, by contrast, show a more mixed pattern, with true seals (phocids) tending to be dispersed, whereas eared seals (otariids) are more geographically clustered. Both cetaceans and pinnipeds show strong evidence for environmental clustering of their phylogenetic lineages in relation to factors such as sea temperature, the extent of sea ice, and nitrate concentrations. Overall, current marine mammal biogeography is not indicative of geographical speciation mechanisms, with environmental factors being more important determinants of current taxonomic distributions. However, geographical isolation appears to have played a role in some important taxa, with evidence from the fossil record showing good support for these cases.

Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this "Big Data" trend, with a strong rise in the volume of data that we are using for our research. Here, we summarize the most recent developments in macroecology in the age of Big Data that were presented at the 2018 annual meeting of the Specialist Group Macroecology of the Ecological Society of Germany, Austria and Switzerland (Gfo). Supported by computational advances, macroecology has been a rapidly developing field over recent years. Our meeting highlighted important avenues for further progress in terms of standardized data collection, data integration, method development and process integration. In particular, we focus on (a) important data gaps and new initiatives to close them, for example through space- and airborne sensors, (b) how various data sources and types can be integrated, (c) how uncertainty can be assessed in data-driven analyses and (d) how Big Data and machine learning approaches have opened new ways of investigating processes rather than simply describing patterns. We discuss how Big Data opens up new opportunities, but also poses new challenges to macroecological research. In the future, it will be essential to carefully assess data quality, the reproducibility of data compilation and analytical methods, and the communication of uncertainties. Major progress in the field will depend on the definition of data standards and workflows for macroecology, such that scientific quality and integrity are guaranteed, and collaboration in research projects is made easier.

Plant–animal interactions are fundamentally important in ecosystems, but have often been ignored by studies of climate-change impacts on biodiversity. Here, we present a trait-based framework for predicting the responses of interacting plants and animals to climate change. We distinguish three pathways along which climate change can impact interacting species in ecological communities: (i) spatial and temporal mismatches in the occurrence and abundance of species, (ii) the formation of novel interactions and secondary extinctions, and (iii) alterations of the dispersal ability of plants. These pathways are mediated by three kinds of functional traits: response traits, matching traits, and dispersal traits. We propose that incorporating these traits into predictive models will improve assessments of the responses of interacting species to climate change.

Aim Despite the central role of species distributions in ecology and conservation, occurrence information remains geographically and taxonomically incomplete and biased. Efforts to address this problem, such as targeted data mobilization and advanced distribution modelling, all crucially rely on a solid understanding of the patterns and determinants of occurrence information. Numerous socio-economic and ecological drivers of uneven record collection and mobilization among species have been suggested, but the generality of their effects remains untested. Here, we provide the first global analysis of patterns and drivers of species-level variation in different metrics of occurrence information. Location Global, including separate analyses for six zoogeographical realms. Methods We evaluated three alternative metrics of occurrence information: (1) the record count per species, (2) the coverage of a range with records and (3) the geographical bias in how the records represent different range parts. To this end, we developed scale-independent metrics of range coverage and geographical record bias. We applied the three metrics to 2.8 million point-occurrence records and extent-of-occurrence range maps of 3625 mammalian species. We used multi-model inference to evaluate 13 putative drivers of species-level variation in data availability. Results All three metrics of occurrence information revealed severe species-level biases. These data limitations were mainly linked to range size and shape, and the within-range geography of socio-economic conditions. Species attributes related to detection and collection probabilities, such as body size or diurnality, were remarkably weak predictors of record count and range coverage. Main conclusions Species-level biases in mobilized occurrence information hamper its broader application in basic and applied biodiversity research. To successfully account for these limitations, the site-specific socio-economic constraints to record collection and mobilization, rather than species-specific constraints to detection, should be explicitly incorporated into ecological models. Furthermore, our results strongly suggest that range-restricted species should be prioritized in future data mobilization efforts.

International audience; The latitudinal diversity gradient (LDG) is one of the most widely debated patterns in ecology and evolution, associated with hundreds of papers, dozens of hypotheses, and disagreements about its underlying processes. The lack of agreement stems from 1) the verbal nature of existing hypotheses, 2) the failure to mechanistically integrate all relevant ecological and evolutionary processes to the LDG, and 3) the degree to which many empirical patterns are consistent with multiple LDG explanations. We show how mapping LDG hypotheses to a set of key ecological and evolutionary processes leads to a better understanding of the internal logic of those hypotheses. The codification of those processes within a mechanistic eco-evolutionary model is essential for contrasting support for hypotheses and for understanding the relative importance of the processes themselves.

The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α-diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.

Made available in DSpace on 2018-11-26T17:44:52Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-26 Robert Bosch Foundation 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. Senckenberg Gesell Naturforsch, Senckenberg Biodivers & Climate Res Ctr, D-60325 Frankfurt, Main, Germany Goethe Univ, Dept Biol Sci, D-60438 Frankfurt, Main, Germany Univ Maryland, Dept Biol, College Pk, MD 20742 USA Univ Maryland, SESYNC, Annapolis, MD 21401 USA Univ Guelph, Dept Integrat Biol, Guelph, ON N1G 2W1, Canada Norwegian Inst Nat Res, POB 5685 Torgard, NO-7485 Trondheim, Norway Duke Univ, Dept Biol, Durham, NC 27708 USA Duke Univ, Dept Evolut Anthropol, Durham, NC 27708 USA Hirola Conservat Programme, Garissa, Kenya Swedish Univ Agr Sci, Dept Wildlife Fish & Environm Studies, S-90183 Umea, Sweden Radboud Univ Nijmegen, Dept Anim Ecol & Physiol, Inst Water & Wetland Res, NL-6500 GL Nijmegen, Netherlands Univ Fed Mato Grosso do Sul, Ecol & Conservat Grad Program, Campo Grande, MS, Brazil Univ Alberta, Dept Biol Sci, Edmonton, AB, Canada Univ London, Royal Vet Coll, Struct & Motion Lab, London NW1 0TU, England Wildlife Conservat Soc, Mongolia Program, Ulaanbaatar, Mongol Peo Rep Mississippi State Univ, Forest & Wildlife Res Ctr, Carnivore Ecol Lab, Box 9690, Mississippi State, MS USA Sao Paulo State Univ, Anim Biol Postgra Program, BR-15054000 Sao Jose Do Rio Preto, SP, Brazil Michigan Dept Nat Resources, 1990 US 41 South, Marquette, MI 49855 USA Univ Calif Davis, Dept Anthropol, Davis, CA 95616 USA Aarhus Univ, Dept Biosci, DK-4000 Roskilde, Denmark Max Planck Inst Ornithol, Vogelwarte Radolfzell, D-78315 Radolfzell am Bodensee, Germany Wildlife Conservat Soc, Bronx, NY 10460 USA Univ Potsdam, Plant Ecol & Nat Conservat, D-14476 Potsdam, Germany Middle Tennessee State Univ, Dept Biol, Murfreesboro, TN 37132 USA Univ Pretoria, Dept Zool & Entomol, Mammal Res Inst, ZA-0028 Gauteng, South Africa Fdn Edmund Mach, Res & Innovat Ctr, Dept Biodivers & Mol Ecol, I-38010 San Michele All Adige, TN, Italy Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USA Natl Zool Pk, Smithsonian Conservat Biol Inst, Front Royal, VA USA Univ Evora, Depat Fitotecn, P-7002554 Evora, Portugal Univ Evora, ICAAM, Inst Mediterranean Agr & Environm Sci, Evora, Portugal Univ Montpellier, Univ Paul Valery Montpellier, CNRS,EPHE, Ctr Ecol Fonctionnelle & Evolut,UMR 5175, F-34293 Montpellier 5, France Phillip Isl Nat Parks, Cowes, Vic, Australia Monash Univ, Sch Biol Sci, Melbourne, Vic, Australia Ohio State Univ, Dept Civil Environm & Geodet Engn, Columbus, OH 43210 USA Fiji Natl Univ, Dept Biol, POB 5529, Natabua, Lautoka, Fiji Univ Massachusetts, US Geol Survey, Massachusetts Cooperat Fish & Wildlife Res Unit, Amherst, MA 01003 USA Penn State Univ, US Geol Survey, Penn Cooperat Fish & Wildlife Res Unit, University Pk, PA 16802 USA Univ Oxford, Dept Zool, Oxford OX1 3PS, England Giraffe Conservat Fdn, POB 86099, Eros, Namibia German Primate Ctr, Behav Ecol & Sociobiol Unit, D-37077 Gottingen, Germany Tech Univ Munich, Dept Ecol & Ecosyst Management, Restorat Ecol, D-85354 Freising Weihenstephan, Germany Cary Inst Ecosyst Studies, Millbrook, NY 12545 USA Univ British Columbia, Irving K Barber Sch Arts & Sci, Unit 2, Biol, Okanagan Campus, Kelowna, BC V1V 1V7, Canada Univ Zurich, Dept Evolutionary Biol & Environm Studies, CH-8057 Zurich, Switzerland Univ Wyoming, Dept Zool & Physiol, Laramie, WY 82071 USA Univ Washington, Sch Environm & Forest Sci, Seattle, WA 98195 USA Univ Montana, Coll Forestry & Conservat, Dept Ecosyst & Conservat Sci, Wildlife Biol Program, Missoula, MT 59812 USA Bavarian Forest Natl Pk, Dept Conservat & Res, D-94481 Grafenau, Germany Albert Ludwigs Univ Freiburg, Wildlife Ecol & Management, D-79106 Freiburg, Germany Univ Toulouse, INRA, CEFS, Castanet Tolosan, France Univ Calif Davis, Anim Behav Grad Grp, Davis, CA 95616 USA Bionet Natr Onderzoek, NL-6171 EL Stein, Netherlands Univ Vet Med Vienna, Res Inst Wildlife Ecol, A-1160 Vienna, Austria Univ Coll Cork, Sch Biol Earth & Environm Sci, Cork, Ireland Univ Wyoming, US Geol Survey, Dept Zool & Physiol, Wyoming Cooperat Fish & Wildlife Res Unit, Laramie, WY USA North Carolina Museum Nat Sci, Raleigh, NC 27601 USA North Carolina State Univ, Dept Forestry & Environm Resources, Raleigh, NC 27695 USA Karatina Univ, Dept Nat Resource Management, POB 195710101, Karatina, Kenya Univ Lethbridge, Dept Psychol, Lethbridge, AB T1K 3M4, Canada Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY 10964 USA Univ Valencia, Terr Vertebrates Grp, Cavanilles Inst Biodivers & Evolutionary Biol, E-46980 Valencia, Spain SUNY Stony Brook, Dept Anthropol, Stony Brook, NY 11794 USA TSG, SSC, IUCN, Rua Licuala 622,Damha 1,Campo Grande, BR-79046150 Mato Grosso Sul, Brazil IPE Inst Pesquisas Ecol Inst Ecol Res, Caixa Postal 47, BR-12960000 Sao Paulo, Brazil Univ Alicante, Dept Ciencias Ambient & Recursos Natur, Vertebrates Zool Res Grp, Alicante, Spain Embrapa Pantanal, BR-79320900 Corumba, MS, Brazil Chico Mendes Inst Conservat Biodivers, Natl Res Ctr Carnivores Conservat, BR-12952011 Atiba, SP, Brazil Univ Glasgow, Inst Biodivers Anim Hlth & Comparat Med, Glasgow, Lanark, Scotland NYU, Dept Biol, Ctr Genom & Syst Biol, New York, NY 10003 USA Univ Calif Davis, Dept Microbiol & Mol Genet, Davis, CA 95616 USA Univ Oslo, Dept Biosci, Ctr Ecol & Evolutionary Synth, NO-0316 Oslo, Norway Hebrew Univ Jerusalem, Alexander Silberman Inst Life Sci, Dept Ecol Evolut & Behav, Movement Ecol Lab, IL-91904 Jerusalem, Israel Norwegian Inst Nat Res, NO-0349 Oslo, Norway Norwegian Univ Sci & Technol NTNU, Dept Math Sci & Ctr Biodivers Dynam, N-7491 Trondheim, Norway Univ Fed Mato Grosso do Sul, Dept Ecol, BR-79070900 Campo Grande, MS, Brazil Field Museum Nat Hist, Integrat Res Ctr, Chicago, IL 60605 USA Consorzio Parco Nazl Stelvio, Bormio, Sondrio, Italy Univ Grenoble Alpes, Irstea, UR LESSEM, BP 76, F-38402 St Martin Dheres, France Univ Bayreuth, BayCEER, D-95447 Bayreuth, Germany Natl Park Schwarzwald, D-77889 Seebach, Germany Univ New South Wales, Evolut & Ecol Res Ctr, Sydney, NSW 2052, Australia Univ New South Wales, Sch Biol Earth & Environm Sci, Sydney, NSW 2052, Australia Penn Game Commiss, Harrisburg, PA 17110 USA Princeton Univ, Dept Ecol & Evolutionary Biol, Princeton, NJ 08544 USA Univ Konstanz, Dept Biol, D-78467 Constance, Germany Off Natl Chasse & Faune Sauvage, Studies & Expertise DRE, F-01330 Birieux, France Univ Haifa, Dept Evolutionary & Environm Biol, IL-3498838 Haifa, Israel Western Ecosyst Technol Inc, Laramie, WY 82070 USA Aarhus Univ, Arctic Res Ctr, DK-8000 Aarhus C, Denmark Polish Acad Sci, Inst Nat Conservat, PL-31120 Krakow, Poland Univ Porto, CIBIO InBIO Associate Lab, P-4485661 Vairao, Portugal Univ Lisbon, Inst Super Agron, InBIO Associate Lab, Ctr Appl Ecol Prof Baeta Neves, P-1349017 Lisbon, Portugal Univ Lisbon, Fac Ciencias, Ctr Ecol Evolut & Environm Changes, P-1749016 Lisbon, Portugal Univ Calif Davis, Dept Environm Sci & Policy, Davis, CA 95616 USA Jackson Hole Conservat, Jackson, WY 83001 USA Univ Vet Med Hannover, Inst Terr & Aquat Wildlife Res, D-30173 Hannover, Germany Univ Calif Santa Cruz, 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Because body size interacts with many fundamental biological properties ofa species, body size evolution can be an essential component of the generationand maintenance of biodiversity. Here we investigate how body sizeevolution can be linked to the clade-specific diversification dynamics indifferent geographical regions. We analyse an extensive body size datasetof Neogene large herbivores (covering approx. 50% of the 970 species inthe orders Artiodactyla and Perissodactyla) in Europe and North Americain a Bayesian framework. We reconstruct the temporal patterns of bodysize in each order on each continent independently, and find significantincreases of minimum size in three of the continental assemblages (exceptEuropean perissodactyls), suggesting an active selection for larger bodies.Assessment of trait-correlated birth-death models indicates that thecommon trend of body size increase is generated by different processes indifferent clades and regions. Larger-bodied artiodactyl species on both continentstend to have higher origination rates, and both clades in NorthAmerica show strong links between large bodies and low extinction rate.Collectively, our results suggest a strong role of species selection and perhapsof higher-taxon sorting in driving body size evolution, and highlightthe value of investigating evolutionary processes in a biogeographic context.

Current patterns of biological diversity are influenced by both historical and present-day factors, yet research in ecology and evolution is largely split between paleontological and neontological studies. Responding to recent calls for integration, we provide a conceptual framework that capitalizes on data and methods from both disciplines to investigate fundamental processes. We highlight the opportunities arising from a combined approach with four examples: (i) which mechanisms generate spatial and temporal variation in diversity; (ii) how traits evolve; (iii) what determines the temporal dynamics of geographical ranges and ecological niches; and (iv) how species-environment and biotic interactions shape community structure. Our framework provides conceptual guidelines for combining paleontological and neontological perspectives to unravel the fundamental processes shaping life on Earth.

Next-Generation Biogeography In 1876, Alfred Russel Wallace mapped the zoogeographical regions of the world, based on the distributions and taxonomic relationships of broadly defined mammalian families. Wallace's classification of zoogeographical regions became a cornerstone of modern biogeography and a reference for a wide variety of biological disciplines, including global biodiversity and conservation sciences. Holt et al. (p. 74 , published online 20 December) present a next-generation map of wallacean zoogeographic regions, incorporating phylogenetic data on >20,000 vertebrate species to discern and characterize their natural biogeographic patterns.

At global and regional scales, primary productivity strongly correlates with richness patterns of extant animals across space, suggesting that resource availability and climatic conditions drive patterns of diversity. However, the existence and consistency of such diversity–productivity relationships through geological history is unclear. Here we provide a comprehensive quantitative test of the diversity–productivity relationship for terrestrial large mammals through time across broad temporal and spatial scales. We combine >14,000 occurrences for 690 fossil genera through the Neogene (23–1.8 Mya) with regional estimates of primary productivity from fossil plant communities in North America and Europe. We show a significant positive diversity–productivity relationship through the 20-million-year record, providing evidence on unprecedented spatial and temporal scales that this relationship is a general pattern in the ecology and paleo-ecology of our planet. Further, we discover that genus richness today does not match the fossil relationship, suggesting that a combination of human impacts and Pleistocene climate variability has modified the 20-million-year ecological relationship by strongly reducing primary productivity and driving many mammalian species into decline or to extinction.

Although the recent historical period is usually treated as a temporal base-line for understanding patterns of mammal extinction, mammalian biodiversity loss has also taken place throughout the Late Quaternary. We explore the spatial, taxonomic and phylogenetic patterns of 241 mammal species extinctions known to have occurred during the Holocene up to the present day. To assess whether our understanding of mammalian threat processes has been affected by excluding these taxa, we incorporate extinct species data into analyses of the impact of body mass on extinction risk. We find that Holocene extinctions have been phylogenetically and spatially concentrated in specific taxa and geographical regions, which are often not congruent with those disproportionately at risk today. Large-bodied mammals have also been more extinction-prone in most geographical regions across the Holocene. Our data support the extinction filter hypothesis, whereby regional faunas from which susceptible species have already become extinct now appear less threatened; they may also suggest that different processes are responsible for driving past and present extinctions. We also find overall incompleteness and inter-regional biases in extinction data from the recent fossil record. Although direct use of fossil data in future projections of extinction risk is therefore not straightforward, insights into extinction processes from the Holocene record are still useful in understanding mammalian threat.

Mountains are key features of the Earth’s surface and host a substantial proportion of the world’s species. However, the links between the evolution and distribution of biodiversity and the formation of mountains remain poorly understood. Here, we integrate multiple datasets to assess the relationships between species richness in mountains, geology and climate at global and regional scales. Specifically, we analyse how erosion, relief, soil and climate relate to the geographical distribution of terrestrial tetrapods, which include amphibians, birds and mammals. We find that centres of species richness correlate with areas of high temperatures, annual rainfall and topographic relief, supporting previous studies. We unveil additional links between mountain-building processes and biodiversity: species richness correlates with erosion rates and heterogeneity of soil types, with a varying response across continents. These additional links are prominent but under-explored, and probably relate to the interplay between surface uplift, climate change and atmospheric circulation through time. They are also influenced by the location and orientation of mountain ranges in relation to air circulation patterns, and how species diversification, dispersal and refugia respond to climate change. A better understanding of biosphere–lithosphere interactions is needed to understand the patterns and evolution of mountain biodiversity across space and time.

Despite the central role of species distributions in ecology and conservation, occurrence information remains geographically and taxonomically incomplete and biased. Numerous socio-economic and ecological drivers of uneven record collection and mobilization among species have been suggested, but the generality of their effects remains untested. We develop scale-independent metrics of range coverage and geographical record bias, and apply them to 2.8M point-occurrence records of 3,625 mammal species to evaluate 13 putative drivers of species-level variation in data availability. We find that data limitations are mainly linked to range size and shape, and the geography of socio-economic conditions. Surprisingly, species attributes related to detection and collection probabilities, such as body size or diurnality, are much weaker predictors of the amount and range coverage of available records. Our results highlight the need to prioritize range-restricted species and to address the key socio-economic drivers of data bias in data mobilization efforts and distribution modeling.