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International audience; In patients with non-small cell lung cancer (NSCLC) treated with immunotherapy, individual biological and PET imaging prognostic biomarkers have been recently identified. However, combination of biomarkers has not been studied yet. The purpose of this study is to combine clinical, biological and 18FDG PET/CT parameters and use machine-learning algorithms to build more accurate prognostic models of NSCLC response to immunotherapy

Additional file 1. Contains Tables S1-S4 and Figures S1-S6, providing further information on data sources, model structures and results of sensitivity analyses.

This dataset comprises 1,040,752 measurements, collated from 9,544 sampling locations in 46 countries and representing 10,635 species. The data was collated from 115 existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database was assembled as part of the PREDICTS project - Projecting Responses of Ecological Diversity In Changing Terrestrial Systems; https://www.nhm.ac.uk/our-science/our-work/biodiversity/predicts.html This release is an addition to the data presented with The 2016 release of the PREDICTS database (available on the NHM Data Portal: https://data.nhm.ac.uk/dataset/the-2016-release-of-the-predicts-database).

The site-level data frame and code to reproduce models in Burton et al. Land use and soil characteristics affect soil organisms differently from above-ground assemblages. Human activities, particularly land-use change and habitat degradation, are driving major changes in biodiversity worldwide. However, studies of such effects have overwhelmingly focused on above-ground taxa: the effects on soil biodiversity are less well known, despite the importance of soil organisms in developing soil structure, nutrient cycling and water drainage. Modelling data collated as part of the Projecting Responses of Ecological Diversity in Changing Terrestrial Systems (PREDICTS) project, we compared how the abundance of soil-dwelling and above-ground organisms responded to land-use and soil properties. We found that land use affects overall abundance differently in soil and above-ground assemblages. Abundance of soil organisms was markedly lower in cropland and plantation habitats than in primary vegetation and pasture. Soil properties influenced the overall abundance of soil biota in ways that differed among land uses, suggesting they shape both abundance and its response to land use. Soil properties also influenced the response of above-ground assemblages, but in ways that differed from their influence on soil assemblages. Our results caution against assuming that models or indicators derived from above-ground data can apply to soil assemblages, and highlight the potential value of incorporating soil properties into models of both soil and above-ground biodiversity.

Using the PREDICTS database of local biodiversity measures at thousands of sites around the world, we statistically modelled how total abundance of organisms and compositional similarity responded to land use and related pressures. We combined these models with spatio-temporal projections of explanatory variables (at 0.25 degrees spatial resolution) from the year 1970 to 2050 under five Shared Socioeconomic Pathways (SSPs) to project the Biodiversity Intactness Index (BII). Mean BII (weighted by cell area) was calculated at the country, subregion, interregion and global level. We used cross-validation (leaving one biome out in turn) to produce decadal upper and lower uncertainty margins for 1970-2050. These summary data were uploaded to the Natural History Museum's Biodiversity Trends Explorer on 2021-10-27. We have also provided mean values of some of the pressures, as changes in these contribute to changes in BII. Superseded by: none (current version)

Human use of the land (for agriculture and settlements) has a substantial negative effect on biodiversity globally. However, not all species are adversely affected by land use, and indeed, some benefit from the creation of novel habitat. Geographically rare species may be more negatively affected by land use than widespread species, but data limitations have so far prevented global multi-clade assessments of land-use effects on narrow-ranged and widespread species. We analyse a large, global database to show consistent differences in assemblage composition. Compared with natural habitat, assemblages in disturbed habitats have more widespread species on average, especially in urban areas and the tropics. All else being equal, this result means that human land use is homogenizing assemblage composition across space. Disturbed habitats show both reduced abundances of narrow-ranged species and increased abundances of widespread species. Our results are very important for biodiversity conservation because narrow-ranged species are typically at higher risk of extinction than widespread species. Furthermore, the shift to more widespread species may also affect ecosystem functioning by reducing both the contribution of rare species and the diversity of species’ responses to environmental changes among local assemblages., Author summary Previous studies have shown that human use of the land, mainly for agriculture and settlements, causes a detectable but relatively small net loss of biodiversity. However, not all species are affected equally, and some species even benefit from the new habitats we create. One group of species of particular concern for biodiversity conservation are those that inhabit only a small area. These narrow-ranged species are at higher risk of extinction because it is more likely that any threats to the species (including human land use) will affect their entire range. Such species can also play a unique role in the healthy functioning of ecosystems. Here, we show that the observed small declines in biodiversity in human-disturbed land can be broken down into large declines in narrow-ranged species, offset by increases in wide-ranged species. All else being equal, this finding means that ecological communities are losing their distinctive, narrow-ranged species and are becoming dominated by the same species everywhere, leading to a reduction in global biodiversity. The divergent effects of human land use on narrow-ranged and widespread species are important for the conservation of already threatened, narrow-ranged species and may lead to a negative effect on the functioning of ecosystems.

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity. EEA Santa Cruz Fil: Hudson, Lawrence N. Natural History Museum. Department of Life Sciences; Reino Unido Fil: Newbold, Tim. World Conservation Monitoring Centre. United Nations Environment Programme; Reino Unido Fil: Newbold, Tim. University College London. Centre for Biodiversity and Environment, Research. Department of Genetics, Evolution and Environment; Reino Unido Fil: Contu, Sara. Natural History Museum. Department of Life Sciences; Reino Unido Fil: Hill, Samantha L. L. Natural History Museum. Department of Life Sciences; Reino Unido Fil: Hill, Samantha L. L. World Conservation Monitoring Centre. United Nations Environment Programme; Reino Unido Fil: Lysenko, Igor. Imperial College London. Department of Life Sciences; Reino Unido Fil: De Palma, Adriana. Natural History Museum. Department of Life Sciences; Reino Unido Fil: De Palma, Adriana. Imperial College London. Department of Life Sciences; Reino Unido Fil: Phillips, Helen R. P. Natural History Museum. Department of Life Sciences; Reino Unido Fil: Phillips, Helen R. P. Imperial College London. Department of Life Sciences; Reino Unido Fil: Alhusseini, Tamera I. Imperial College London. South Kensington; Reino Unido Fil: Bedford, Felicity E. Cambridge University. Department of Zoology; Reino Unido Fil: Bennett, Dominic J. Imperial College London. Department of Life Sciences; Reino Unido Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina. Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Purvis, Andy. Natural History Museum. Department of Life Sciences; Reino Unido Fil: Purvis, Andy. Imperial College London. Department of Life Sciences; Reino Unido

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity., published version, peerReviewed

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

This is the data used to plot figure S4 in Newbold et al. (2016) “Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment”, Science 353:288-29, doi 10.1126/science.aaf2201. The variable plotted, Biodiversity Intactness Index, is the modeled average abundance of originally-present species, relative to their abundance in an intact ecosystem. Please refer to Newbold et al. (2016) for all details, and please cite it when using these data.

This was the first conference presentation of the PREDICTS project.

This is the site-level data used in Newbold et al. (2016) "Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment", Science, and the Jaccard similarities among land uses from the models in the same paper. Please refer to that paper for details of how the site-level data frame and Jaccard similarity matrix were created, and the README file for column explanations. Identifying information (author, bibliographic details, precise coordinates) have been removed from this data frame so as not to violate agreements with the many data contributors; the full biodiversity data set that underpins these analyses is currently in review (as of May 2016) and will be published on data.nhm.ac.uk, by agreement with the contributors, at which point all the biodiversity data used here will be available.

This was the first conference presentation of the PREDICTS project.

This is the site-level data used to analyses whether sampled biodiversity differs between sites inside and outside protected areas. These data were obtained from the November 2014 version of the full Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (PREDICTS) database (described in Hudson et al. 2014 The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts Ecol. Evol. 4: 4701-4735 DOI: 10.1002/ece3.1303), but include only studies that had sites both inside and outside of protected areas (as described by IUCN and UNEP (2014) The World Database on Protected Areas, July 2014. UNEP-WCMC, Cambridge. Available at www.protectedplanet.net). The data contain the source, study, block and site IDs. For each site the following variables are given: country, latitude, longitude, diversity measure (abundance or occurrence), land use (both as an eight level and three level factor), use intensity, the start date of sampling, the realm, latitudinal zone, broad taxonomic group, the four response variables analysed (abundance, species richness, rarefied species richness and community weighted mean range size), data on covariates (slope, elevation and agricultural suitability) and whether each site fell within a protected area or not. For each protected site, the following variables from the July 2014 World Database on Protected Areas are provided: IUCN category (1.5 = I & II, 4.5 = III to VI, 7 = unreported), the GIS_AREA, STATUS_YEAR, duration of protection (status year minus earliest sampling date at that site), and the size/age class of the protected area. Variables are also included to specify which sites were used in the matched landuse analyses and the species richness/rarefied richness models (which included only sites for which multiple taxa were surveyed).

This dataset contains site-level summaries of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The underlying database is being assembled as part of the [PREDICTS project](https://www.nhm.ac.uk/our-science/our-work/biodiversity/predicts.html) - Projecting Responses of Ecological Diversity In Changing Terrestrial Systems. A complete description of the data is given in [https://doi.org/10.1002/ece3.1303](https://doi.org/10.1002/ece3.1303).

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local‐scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site‐level summary data available alongside this article. The full database will be publicly available in 2015.