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The many Gondwanic vegetation types found across the extensive latitudes and elevation gradients of South America's southern cone contribute to Chile's global biodiversity hotspot ranking. Species loss in global biodiversity hotspots is an ongoing climate change concern and land managers need spatially explicit climate risk maps to adapt conservation strategies to climate change in these areas. We modeled future climate risk for Chile's terrestrial vegetation using a high-resolution vegetation map and tested the relationship to climate risk for each type's latitudinal and elevation range. We found that 43.6% of all vegetation has high climate risk in Global Circulation Models (GCMs) under a high emissions scenario (RCP8.5). All forest types in the country, including Southern Beech (Nothofagus sp.), Alerce (Fitzroya cupressoides), Araucaria (Araucaria araucana), and Sclerophyllous, as well as the Valdivian rainforest, Altiplanic Steppes, and Salares, face high levels of climate risk. Tests for trends in risk across elevation and latitude showed that exposure for all types increased with elevation based on the MIROC5 GCM, and decreased with latitude based on the Had2GEM-ES GCM. Our results suggest that vegetation types with smaller latitudinal ranges typically have higher levels of climate risk, but a type's elevation range is not significantly correlated with risk of exposure. We identified climatically stable areas which could act as vegetation refugia in Patagonia, the central Andes mountains between latitudes 27.5°S and 32.5°S, and some coastal areas. Conservation strategies in Chile should include the protection of climatically stable areas to safeguard current Gondwanic biodiversity and active habitat restoration in climatically exposed areas to facilitate vegetation shifts.

ArticleOpen AccessPublished: 24 April 2020Topography and human pressure in mountain ranges alter expected species responses to climate changePaul R. Elsen, William B. Monahan & Adina M. Merenlender Nature Communications volume 11, Article number: 1974 (2020) Cite this article 2845 Accesses120 Altmetric MetricsdetailsAbstractClimate change is leading to widespread elevational shifts thought to increase species extinction risk in mountains. We integrate digital elevation models with a metric of human pressure to examine changes in the amount of intact land area available for species undergoing elevational range shifts in all major mountain ranges globally (n = 1010). Nearly 60% of mountainous area is under intense human pressure, predominantly at low elevations and mountain bases. Consequently, upslope range shifts generally resulted in modeled species at lower elevations expanding into areas of lower human pressure and, due to complex topography, encountering more intact land area relative to their starting position. Such gains were often attenuated at high elevations as land-use constraints diminished and topographic constraints increased. Integrating patterns of topography and human pressure is essential for accurate species vulnerability assessments under climate change, as priorities for protecting, connecting, and restoring mountain landscapes may otherwise be misguided.

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Species distribution models are vital to management decisions that require understanding habitat use patterns, particularly for species of conservation concern. However, the production of distribution maps for individual species is often hampered by data scarcity, and existing species maps are rarely spatially validated due to limited occurrence data. Furthermore, communitylevel maps based on stacked species distribution models lack important community assemblage information (e.g., competitive exclusion) relevant to conservation. Thus, multispecies, guild, or community models are often used in conservation practice instead. To address these limitations, we aimed to generate fine-scale, spatially continuous, nationwide maps for species represented in the North American Breeding Bird Survey (BBS) between 1992 and 2019. We developed ensemble models for each species at three spatial resolutions--0.5, 2.5, and 5 km--across the conterminous United States. We also compared species richness patterns from stacked single-species models with those of 19 functional guilds developed using the same data to assess the similarity between predictions. We successfully modeled 192 bird species at 5-km resolution, 160 species at 2.5-km resolution, and 80 species at 0.5-km resolution. However, the species we could model represent only 28%-56% of species found in the conterminous US BBSs across resolutions owing to data limitations. We found that stacked maps and guild maps generally had high correlations across resolutions (median = 84%), but spatial agreement varied regionally by resolution and was most pronounced between the East and West at the 5-km resolution. The spatial differences between our stacked maps and guild maps illustrate the importance of spatial validation in conservation planning. Overall, our species maps are useful for single-species conservation and can support fine-scale decision-making across the United States and support community-level conservation when used in tandem with guild maps. However, there remain data scarcity issues for many species of conservation concern when using the BBS for single-species models. [ABSTRACT FROM AUTHOR]

Grassland ecosystems cover up to 40% of the global land area and provide many ecosystem services directly supporting the livelihoods of over 1 billion people. Monitoring long-term changes in grasslands is crucial for food security, biodiversity conservation, achieving Land Degradation Neutrality goals, and modeling the global carbon budget. Although long-term grassland monitoring using remote sensing is extensive, it is typically based on a single vegetation index and does not account for temporal and spatial autocorrelation, which means that some trends are falsely identified while others are missed. Our goal was to analyze trends in grasslands in Eurasia, the largest continuous grassland ecosystems on Earth. To do so, we calculated Cumulative Endmember Fractions (annual sums of monthly ground cover fractions) derived from MODIS 2002-2020 time series, and applied a new statistical approach PARTS that explicitly accounts for temporal and spatial autocorrelation in trends. We examined trends in green vegetation, non-photosynthetic vegetation, and soil ground cover fractions considering their independent change trajectories and relations among fractions over time. We derived temporally uncorrelated pixel-based trend maps and statistically tested whether observed trends could be explained by elevation, land cover, SPEI3, climate, country, and their combinations, all while accounting for spatial autocorrelation. We found no statistical evidence for a decrease in vegetation cover in grasslands in Eurasia. Instead, there was a significant map-level increase in non-photosynthetic vegetation across the region and local increases in green vegetation with a concomitant decrease in soil fraction. Independent environmental variables affected trends significantly, but effects varied by region. Overall, our analyses show in a statistically robust manner that Eurasian grasslands have changed considerably over the past two decades. Our approach enhances remote sensing-based monitoring of trends in grasslands so that underlying processes can be discerned. [ABSTRACT FROM AUTHOR]

Rapid climate change is impacting biodiversity, ecosystem function, and human well‐being. Though the magnitude and trajectory of climate change are becoming clearer, our understanding of how these changes reshape terrestrial life zones—distinct biogeographic units characterized by biotemperature, precipitation, and aridity representing broad‐scale ecosystem types—is limited. To address this gap, we used high‐resolution historical climatologies and climate projections to determine the global distribution of historical (1901–1920), contemporary (1979–2013), and future (2061–2080) life zones. Comparing the historical and contemporary distributions shows that changes from one life zone to another during the 20th century impacted 27 million km2 (18.3% of land), with consequences for social and ecological systems. Such changes took place in all biomes, most notably in Boreal Forests, Temperate Coniferous Forests, and Tropical Coniferous Forests. Comparing the contemporary and future life zone distributions shows the pace of life zone changes accelerating rapidly in the 21st century. By 2070, such changes would impact an additional 62 million km2 (42.6% of land) under "business‐as‐usual" (RCP8.5) emissions scenarios. Accelerated rates of change are observed in hundreds of ecoregions across all biomes except Tropical Coniferous Forests. While only 30 ecoregions (3.5%) had over half of their areas change to a different life zone during the 20th century, by 2070 this number is projected to climb to 111 ecoregions (13.1%) under RCP4.5 and 281 ecoregions (33.2%) under RCP8.5. We identified weak correlations between life zone change and threatened vertebrate richness, levels of vertebrate endemism, cropland extent, and human population densities within ecoregions, illustrating the ubiquitous risks of life zone changes to diverse social–ecological systems. The accelerated pace of life zone changes will increasingly challenge adaptive conservation and sustainable development strategies that incorrectly assume current ecological patterns and livelihood provisioning systems will persist. [ABSTRACT FROM AUTHOR]