Integrating biodiversity distribution knowledge: toward a global map of life.

Global knowledge about the spatial distribution of species is orders of magnitude coarser in resolution than other geographically-structured environmental datasets such as topography or land cover. Yet such knowledge is crucial in deciphering ecological and evolutionary processes and in managing global change. In this review, we propose a conceptual and cyber-infrastructure framework for refining species distributional knowledge that is novel in its ability to mobilize and integrate diverse types of data such that their collective strengths overcome individual weaknesses. The ultimate aim is a public, online, quality-vetted 'Map of Life' that for every species integrates and visualizes available distributional knowledge, while also facilitating user feedback and dynamic biodiversity analyses. First milestones toward such an infrastructure have now been implemented.

[1]  J. Andrew Royle,et al.  Hierarchical Modeling and Inference in Ecology: The Analysis of Data from Populations, Metapopulations and Communities , 2008 .

[2]  Antoine Guisan,et al.  Are niche-based species distribution models transferable in space? , 2006 .

[3]  Georgina M. Mace,et al.  Distorted Views of Biodiversity: Spatial and Temporal Bias in Species Occurrence Data , 2010, PLoS biology.

[4]  Keywan Riahi,et al.  Downscaling socioeconomic and emissions scenarios for global environmental change research: a review , 2010 .

[5]  J. Andrew Royle,et al.  Estimating species richness and accumulation by modeling species occurrence and detectability. , 2006, Ecology.

[6]  Kalle Ruokolainen,et al.  Analysing botanical collecting effort in Amazonia and correcting for it in species range estimation , 2007 .

[7]  P. Webber,et al.  Woodland Transects of the Frontenac Axis Region, Ontario , 1962 .

[8]  M. Whitlock Data archiving in ecology and evolution: best practices. , 2011, Trends in ecology & evolution.

[9]  Mathieu Marmion,et al.  Evaluation of consensus methods in predictive species distribution modelling , 2009 .

[10]  W. Cramer,et al.  A global biome model based on plant physiology and dominance, soil properties and climate , 1992 .

[11]  S. Suárez‐Seoane,et al.  Non‐stationarity and local approaches to modelling the distributions of wildlife , 2007 .

[12]  Simon Ferrier,et al.  Extracting More Value from Biodiversity Change Observations through Integrated Modeling , 2011 .

[13]  Arwyn Jones,et al.  Harmonized World Soil Database (HWSD) , 2014 .

[14]  A. Hahs,et al.  A dispersal-constrained habitat suitability model for predicting invasion of alpine vegetation. , 2008, Ecological applications : a publication of the Ecological Society of America.

[15]  Walter Jetz,et al.  Species richness, hotspots, and the scale dependence of range maps in ecology and conservation , 2007, Proceedings of the National Academy of Sciences.

[16]  Walter Jetz,et al.  Cross-scale variation in species richness–environment associations , 2011 .

[17]  S. Ferrier Mapping spatial pattern in biodiversity for regional conservation planning: where to from here? , 2002, Systematic biology.

[18]  A. Gelfand,et al.  Modelling species diversity through species level hierarchical modelling , 2005 .

[19]  Shanshan Wu,et al.  Building statistical models to analyze species distributions. , 2006, Ecological applications : a publication of the Ecological Society of America.

[20]  D J Patterson,et al.  Names are key to the big new biology. , 2010, Trends in ecology & evolution.

[21]  R. G. Wright,et al.  GAP ANALYSIS: A GEOGRAPHIC APPROACH TO PROTECTION OF BIOLOGICAL DIVERSITY , 1993 .

[22]  Jane Elith,et al.  Error and uncertainty in habitat models , 2006 .

[23]  L. Boitani,et al.  Research Techniques in Animal Ecology: Controversies and Consequences , 2001 .

[24]  M. Luoto,et al.  Biotic interactions improve prediction of boreal bird distributions at macro‐scales , 2007 .

[25]  J. Elith,et al.  Sensitivity of predictive species distribution models to change in grain size , 2007 .

[26]  Walter Jetz,et al.  The Scaling of Animal Space Use , 2004, Science.

[27]  M. Fladeland,et al.  Remote sensing for biodiversity science and conservation , 2003 .

[28]  Walter Jetz,et al.  Global patterns and predictors of marine biodiversity across taxa , 2010, Nature.

[29]  Matthew B. Jones,et al.  Challenges and Opportunities of Open Data in Ecology , 2011, Science.

[30]  J. Andrew Royle,et al.  Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys , 2008 .

[31]  Andrew K. Skidmore,et al.  Modeling species distribution with GIS , 2000 .

[32]  Trevor Hastie,et al.  Making better biogeographical predictions of species’ distributions , 2006 .

[33]  Qinghua Guo,et al.  The point-radius method for georeferencing locality descriptions and calculating associated uncertainty , 2004, Int. J. Geogr. Inf. Sci..

[34]  C. Marshall Encyclopedia of Life , 2008 .

[35]  W. Thuiller,et al.  Predicting species distribution: offering more than simple habitat models. , 2005, Ecology letters.

[36]  D. Pauly,et al.  Mapping world-wide distributions of marine mammal species using a relative environmental suitability (RES) model , 2006 .

[37]  Hugh P. Possingham,et al.  How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabies Petrogale penicillata , 2009 .

[38]  M. Torre Jorgenson,et al.  climate change 1 , 2010 .

[39]  S. Reddy,et al.  Geographical sampling bias and its implications for conservation priorities in Africa , 2003 .

[40]  Helen M. Regan,et al.  Mapping epistemic uncertainties and vague concepts in predictions of species distribution , 2002 .

[41]  Catherine H. Graham,et al.  A comparison of methods for mapping species ranges and species richness , 2006 .

[42]  G. Powell,et al.  Mapping More of Terrestrial Biodiversity for Global Conservation Assessment , 2004 .

[43]  Jane Elith,et al.  Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities , 2011 .

[44]  Hirofumi Hashimoto,et al.  Monitoring and forecasting ecosystem dynamics using the Terrestrial Observation and Prediction System (TOPS) , 2009 .

[45]  J. Elith,et al.  Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment , 2007 .

[46]  T. Dawson,et al.  Selecting thresholds of occurrence in the prediction of species distributions , 2005 .

[47]  J. Nichols,et al.  ESTIMATING SITE OCCUPANCY, COLONIZATION, AND LOCAL EXTINCTION WHEN A SPECIES IS DETECTED IMPERFECTLY , 2003 .

[48]  Walter Jetz,et al.  Phylogenetic conservatism of environmental niches in mammals , 2011, Proceedings of the Royal Society B: Biological Sciences.

[49]  Ethan P. White,et al.  Disparity between range map- and survey-based analyses of species richness: patterns, processes and implications , 2005 .

[50]  A. Hirzel,et al.  Habitat suitability modelling and niche theory , 2008 .

[51]  Walter Jetz,et al.  Ecological Correlates and Conservation Implications of Overestimating Species Geographic Ranges , 2008, Conservation biology : the journal of the Society for Conservation Biology.

[52]  S. Beissinger,et al.  Detecting range shifts from historical species occurrences: new perspectives on old data. , 2009, Trends in ecology & evolution.

[53]  Bronwyn Price,et al.  Using a Bayesian belief network to predict suitable habitat of an endangered mammal – The Julia Creek dunnart (Sminthopsis douglasi) , 2007 .

[54]  Christina M. Trexler,et al.  Does size matter for dispersal distance , 2007 .

[55]  Mevin B. Hooten,et al.  Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model , 2003, Landscape Ecology.

[56]  J. Watson,et al.  Conservation Biogeography: assessment and prospect , 2005 .

[57]  K. Mengersen,et al.  Bayesian model averaging for harmful algal bloom prediction. , 2009, Ecological applications : a publication of the Ecological Society of America.

[58]  M. Austin Species distribution models and ecological theory: A critical assessment and some possible new approaches , 2007 .

[59]  Chris J. Johnson,et al.  Mapping uncertainty: sensitivity of wildlife habitat ratings to expert opinion , 2004 .

[60]  Hugh P Possingham,et al.  Tradeoffs of different types of species occurrence data for use in systematic conservation planning. , 2006, Ecology letters.

[61]  W. Jetz,et al.  Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder , 2009 .

[62]  J. D. Hoyo,et al.  Handbook of the Birds of the World , 2010 .

[63]  Heather A. Piwowar,et al.  Biology Needs a Modern Assessment System for Professional Productivity , 2011 .

[64]  Andre Zerger,et al.  Eliciting and integrating expert knowledge for wildlife habitat modelling , 2003 .

[65]  R. Swihart,et al.  Absent or undetected? Effects of non-detection of species occurrence on wildlife-habitat models , 2004 .

[66]  Steven J. Phillips,et al.  Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. , 2009, Ecological applications : a publication of the Ecological Society of America.

[67]  Fridolin Zimmermann,et al.  Testing expert groups for a habitat suitability model for the lynx Lynx lynx in the Swiss Alps , 2007 .

[68]  W. Jetz,et al.  Type and spatial structure of distribution data and the perceived determinants of geographical gradients in ecology : the species richness of African birds , 2007 .

[69]  Walter Jetz,et al.  Projected range contractions of montane biodiversity under global warming , 2010, Proceedings of the Royal Society B: Biological Sciences.

[70]  J. Townshend,et al.  Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm , 2003 .

[71]  A. Dobson,et al.  Projected Impacts of Climate and Land-Use Change on the Global Diversity of Birds , 2007, PLoS biology.

[72]  W. Thuiller BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change , 2003 .

[73]  Kathleen E. Franzreb,et al.  Testing habitat-relationship models for forest birds of the southeastern United States , 2002 .