Leclère, D. et al. Bending the curve of terrestrial biodiversity needs an integrated strategy. Nature 585, 551–556 (2020).
Google Scholar
Pillay, R. et al. Tropical forests are home to over half of the world’s vertebrate species. Front. Ecol. Environ. 20, 10–15 (2022).
Google Scholar
Turubanova, S., Potapov, P. V., Tyukavina, A. & Hansen, M. C. Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environ. Res. Lett. 13, 074028 (2018).
Google Scholar
Matricardi, E. A. T. et al. Long-term forest degradation surpasses deforestation in the Brazilian Amazon. Science 369, 1378–1382 (2020).
Google Scholar
Gibson, L. et al. Primary forests are irreplaceable for sustaining tropical biodiversity. Nature 478, 378–381 (2011).
Google Scholar
Barlow, J. et al. Anthropogenic disturbance in tropical forests can double biodiversity loss from deforestation. Nature 535, 144–147 (2016).
Google Scholar
Watson, J. E. M. et al. The exceptional value of intact forest ecosystems. Nat. Ecol. Evol. 2, 599–610 (2018).
Google Scholar
Hansen, A. et al. Global humid tropics forest structural condition and forest structural integrity maps. Sci. Data 6, 232 (2019).
Google Scholar
Hansen, A. J. et al. A policy-driven framework for conserving the best of Earth’s remaining moist tropical forests. Nat. Ecol. Evol. 4, 1377–1384 (2020).
Google Scholar
COP 11 Decision X/2. Strategic Plan for Biodiversity 2011–2020 (Convention on Biological Diversity, 2010).
New York Declaration on Forests (UN, 2014).
Transforming our World: The 2030 Agenda for Sustainable Development. A/RES/70/1 Resolution Adopted by the United Nations General Assembly (UN, 2015).
Adoption of the Paris Agreement. Proposal by the President. Draft Decision -/CP.21 (UNFCCC, 2015).
Hansen, A. J. et al. Toward monitoring forest ecosystem integrity within the post-2020 Global Biodiversity Framework. Conserv. Lett. 14, e12822 (2021).
Google Scholar
Scholes, R. et al. (eds) Summary for Policymakers of the Assessment Report on Land Degradation and Restoration (IPBES, 2018).
First Draft of the Post-2020 Global Biodiversity Framework (Convention on Biological Diversity, 2021).
Williams, B. A. et al. Change in terrestrial human footprint drives continued loss of intact ecosystems. One Earth 3, 371–382 (2020).
Google Scholar
The IUCN Red List of Threatened Species Version 2020–1 (IUCN, 2020).
Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. Bioscience 67, 534–545 (2017).
Google Scholar
Ives, A. R. & Garland, T. Phylogenetic logistic regression for binary dependent variables. Syst. Biol. 59, 9–26 (2010).
Google Scholar
Di Marco, M., Ferrier, S., Harwood, T. D., Hoskins, A. J. & Watson, J. E. M. Wilderness areas halve the extinction risk of terrestrial biodiversity. Nature 573, 582–585 (2019).
Google Scholar
Betts, M. G. et al. Global forest loss disproportionately erodes biodiversity in intact landscapes. Nature 547, 441–444 (2017).
Google Scholar
Fletcher, R. & Fortin, M.-J. Spatial Ecology and Conservation Modeling: Applications with R (Springer, 2018). https://doi.org/10.1007/978-3-030-01989-1
Briant, G., Gond, V. & Laurance, S. G. W. Habitat fragmentation and the desiccation of forest canopies: a case study from eastern Amazonia. Biol. Conserv. 143, 2763–2769 (2010).
Google Scholar
Anderegg, W. R. L. et al. Climate-driven risks to the climate mitigation potential of forests. Science 368, eaaz7005 (2020).
Google Scholar
Pillay, R. et al. Using interview surveys and multispecies occupancy models to inform vertebrate conservation. Conserv. Biol. 36, e13832 (2022).
Google Scholar
Agresti, A. Categorical Data Analysis (John Wiley and Sons, 2002).
Smith, A. C., Koper, N., Francis, C. M. & Fahrig, L. Confronting collinearity: comparing methods for disentangling the effects of habitat loss and fragmentation. Landsc. Ecol. 24, 1271–1285 (2009).
Google Scholar
Mittermeier, R. A. et al. Wilderness and biodiversity conservation. Proc. Natl Acad. Sci. USA 18, 10309–10313 (2003).
Google Scholar
Turner, I. M. & Corlett, R. T. The conservation value of small, isolated fragments of lowland tropical rain forest. Trends Ecol. Evol. 11, 330–333 (1996).
Google Scholar
Tulloch, A. I. T., Barnes, M. D., Ringma, J., Fuller, R. A. & Watson, J. E. M. Understanding the importance of small patches of habitat for conservation. J. Appl. Ecol. 53, 418–429 (2016).
Google Scholar
Wintle, B. A. et al. Global synthesis of conservation studies reveals the importance of small habitat patches for biodiversity. Proc. Natl Acad. Sci. USA 116, 909–914 (2019).
Google Scholar
Hansen, M. C. et al. The fate of tropical forest fragments. Sci. Adv. 6, eaax8574 (2020).
Google Scholar
Prugh, L. R., Hodges, K. E., Sinclair, A. R. E. & Brashares, J. S. Effect of habitat area and isolation on fragmented animal populations. Proc. Natl Acad. Sci. USA 105, 20770–20775 (2008).
Google Scholar
Grantham, H. S. et al. Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity. Nat. Commun. 11, 5978 (2020).
Google Scholar
Beyer, H. L., Venter, O., Grantham, H. S. & Watson, J. E. M. Substantial losses in ecoregion intactness highlight urgency of globally coordinated action. Conserv. Lett. 13, e12692 (2020).
Google Scholar
Ehbrecht, M. et al. Global patterns and climatic controls of forest structural complexity. Nat. Commun. 12, 519 (2021).
Google Scholar
França, F. et al. Do space-for-time assessments underestimate the impacts of logging on tropical biodiversity? An Amazonian case study using dung beetles. J. Appl. Ecol. 53, 1098–1105 (2016).
Google Scholar
Di Marco, M., Venter, O., Possingham, H. P. & Watson, J. E. M. Changes in human footprint drive changes in species extinction risk. Nat. Commun. 9, 4621 (2018).
Google Scholar
Betts, M. G. et al. Forest degradation drives widespread avian habitat and population declines. Nat. Ecol. Evol. 6, 709–719 (2022).
Google Scholar
Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).
Google Scholar
Basset, Y. et al. Arthropod diversity in a tropical forest. Science 338, 1481–1484 (2012).
Google Scholar
Cardillo, M. et al. Multiple causes of high extinction risk in large mammal species. Science 309, 1239–1241 (2005).
Google Scholar
Newbold, T. et al. Ecological traits affect the response of tropical forest bird species to land-use intensity. Proc. R. Soc. B 280, 20122131 (2013).
Google Scholar
Maron, M., Simmonds, J. S. & Watson, J. E. M. Bold nature retention targets are essential for the global environment agenda. Nat. Ecol. Evol. 2, 1194–1195 (2018).
Google Scholar
Díaz, S. et al. Set ambitious goals for biodiversity and sustainability. Science 370, 411–413 (2020).
Google Scholar
Bird Species Distribution Maps of the World Version 2018.1 (BirdLife International, accessed 16 August 2019).
Roll, U. et al. The global distribution of tetrapods reveals a need for targeted reptile conservation. Nat. Ecol. Evol. 1, 1677–1682 (2017).
Google Scholar
González-del-Pliego, P. et al. Phylogenetic and trait-based prediction of extinction risk for data-deficient amphibians. Curr. Biol. 29, 1557–1563 (2019).
Google Scholar
IUCN Habitats Classification Scheme Version 3.1 (IUCN, 2012).
Böhm, M. et al. The conservation status of the world’s reptiles. Biol. Conserv. 157, 372–385 (2013).
Google Scholar
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Google Scholar
Hansen, M. C. et al. Mapping tree height distributions in Sub-Saharan Africa using Landsat 7 and 8 data. Remote Sens. Environ. 185, 221–232 (2016).
Google Scholar
Sanderson, E. W. et al. The human footprint and the last of the wild. Bioscience 52, 891–904 (2002).
Google Scholar
Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun. 7, 12558 (2016).
Google Scholar
Di Marco, M., Watson, J. E. M., Possingham, H. P. & Venter, O. Limitations and trade-offs in the use of species distribution maps for protected area planning. J. Appl. Ecol. 54, 402–411 (2017).
Google Scholar
Jenkins, C. N., Pimm, S. L. & Joppa, L. N. Global patterns of terrestrial vertebrate diversity and conservation. Proc. Natl Acad. Sci. USA 110, E2603–E2610 (2013).
Google Scholar
Simard, M., Pinto, N., Fisher, J. B. & Baccini, A. Mapping forest canopy height globally with spaceborne lidar. J. Geophys. Res. Biogeosci. 116, G04021 (2011).
Google Scholar
Sexton, J. O. et al. Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error. Int. J. Digit. Earth 6, 427–448 (2013).
Google Scholar
Potapov, P. et al. Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sens. Environ. 253, 112165 (2021).
Google Scholar
Upham, N. S., Esselstyn, J. A. & Jetz, W. Inferring the mammal tree: species-level sets of phylogenies for questions in ecology, evolution, and conservation. PLoS Biol. 17, e3000494 (2019).
Google Scholar
Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).
Google Scholar
Tonini, J. F. R., Beard, K. H., Ferreira, R. B., Jetz, W. & Pyron, R. A. Fully-sampled phylogenies of squamates reveal evolutionary patterns in threat status. Biol. Conserv. 204, 23–31 (2016).
Google Scholar
Jetz, W. & Pyron, R. A. The interplay of past diversification and evolutionary isolation with present imperilment across the amphibian tree of life. Nat. Ecol. Evol. 2, 850–858 (2018).
Google Scholar
Ho, L. S. T. & Ané, C. A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Syst. Biol. 63, 397–408 (2014).
Google Scholar
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
Verhoeven, K. J. F., Simonsen, K. L. & McIntyre, L. M. Implementing false discovery rate control: increasing your power. Oikos 108, 643–647 (2005).
Google Scholar
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).
Bivand, R. et al. spdep: Spatial dependence: weighting schemes, statistics and models. R package version 0.7-4 (2017).
Bjornstad, O. N. ncf: Spatial covariance functions. R package version 1.2-1 (2018).
Source: Ecology - nature.com
