Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km²resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km²pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Tropical forest degradation emits carbon at a rate of ~0.5 Pg·y⁻¹, reduces biodiversity, and facilitates forest clearance. Understanding degradation drivers and patterns is therefore crucial to managing forests to mitigate climate change and reduce biodiversity loss. Putative patterns of degradation affecting forest stocks, carbon, and biodiversity have variously been described previously, but these have not been quantitatively assessed together or tested systematically. Economic theory predicts a systematic allocation of land to its highest use value in response to distance from centers of demand. We tested this theory to see if forest exploitation would expand through time and space as concentric waves, with each wave targeting lower value products. We used forest data along a transect from 10 to 220 km from Dar es Salaam (DES), Tanzania, collected at two points in time (1991 and 2005). Our predictions were confirmed: high-value logging expanded 9 km·y⁻¹, and an inner wave of lower value charcoal production 2 km·y⁻¹. This resource utilization is shown to reduce the public goods of carbon storage and species richness, which significantly increased with each kilometer from DES [carbon, 0.2 Mg·ha⁻¹; 0.1 species per sample area (0.4 ha)]. Our study suggests that tropical forest degradation can be modeled and predicted, with its attendant loss of some public goods. In sub-Saharan Africa, an area experiencing the highest rate of urban migration worldwide, coupled with a high dependence on forest-based resources, predicting the spatiotemporal patterns of degradation can inform policies designed to extract resources without unsustainably reducing carbon storage and biodiversity.

Understanding the effects of cash crop expansion on natural forest is of fundamental importance. However, for most crops there are no remotely sensed global maps¹, and global deforestation impacts are estimated using models and extrapolations. Natural rubber is an example of a principal commodity for which deforestation impacts have been highly uncertain, with estimates differing more than fivefold^1–4. Here we harnessed Earth observation satellite data and cloud computing⁵ to produce high-resolution maps of rubber (10 m pixel size) and associated deforestation (30 m pixel size) for Southeast Asia. Our maps indicate that rubber-related forest loss has been substantially underestimated in policy, by the public and in recent reports^6–8. Our direct remotely sensed observations show that deforestation for rubber is at least twofold to threefold higher than suggested by figures now widely used for setting policy⁴. With more than 4 million hectares of forest loss for rubber since 1993 (at least 2 million hectares since 2000) and more than 1 million hectares of rubber plantations established in Key Biodiversity Areas, the effects of rubber on biodiversity and ecosystem services in Southeast Asia could be extensive. Thus, rubber deserves more attention in domestic policy, within trade agreements and in incoming due-diligence legislation.

Aim: Climate change is expected to impact mountain biodiversity by shifting species ranges and the biomes they shape. The extent and regional variation in these impacts are still poorly understood, particularly in the highly biodiverse Andes. Regional syntheses of climate change impacts on vegetation are pivotal to identify and guide research priorities. Here we review current data, knowledge and uncertainties in past, present and future climate change impacts on vegetation in the Andes.Location: Andes.Taxon: Plants.Methods: We (i) conducted a literature review on Andean vegetation responses to past and contemporary climatic change, (ii) analysed future climate projections for different elevations and slope orientations at 19 Andean locations using an ensemble of model outputs from the Coupled Model Intercomparison Project 5, and (iii) calculated changes in the suitable climate envelope area of Andean biomes and compared these results to studies that used species distribution models.Results: Future climatic changes (2040–2070) are projected to be stronger at high‐elevation areas in the tropical Andes (up to 4°C under RCP 8.5), while in the temperate Andes temperature increases are projected to be up to 2°C. Under this worst‐case scenario, temperate deciduous forests and the grasslands/steppes from the Central and Southern Andes are predicted to show the greatest losses of suitable climatic space (30% and 17%–23%, respectively). The high vulnerability of these biomes contrasts with the low attention from researchers modelling Andean species distributions. Critical knowledge gaps include a lack of an Andean wide plant checklist, insufficient density of weather stations at high‐elevation areas, a lack of high‐resolution climatologies that accommodates the Andes' complex topography and climatic processes, insufficient data to model demographic and ecological processes, and low use of palaeo data for distribution modelling.Main conclusions: Climate change is likely to profoundly affect the extent and composition of Andean biomes. Temperate Andean biomes in particular are susceptible to substantial area contractions. There are, however, considerable challenges and uncertainties in modelling species and biome responses and a pressing need for a region‐wide approach to address knowledge gaps and improve understanding and monitoring of climate change impacts in these globally important biomes.

Aim  Effective conservation of biodiversity relies on an unbiased knowledge of its distribution. Conservation priority assessments are typically based on the levels of species richness, endemism and threat. Areas identified as important receive the majority of conservation investments, often facilitating further research that results in more species discoveries. Here, we test whether there is circularity between funding and perceived biodiversity, which may reinforce the conservation status of areas already perceived to be important while other areas with less initial funding may remain overlooked.Location  Eastern Arc Mountains, Tanzania.Methods  We analysed time series data (1980–2007) of funding (n = 134 projects) and plant species records (n = 75,631) from a newly compiled database. Perceived plant diversity, over three decades, is regressed against funding and environmental factors, and variances decomposed in partial regressions. Cross‐correlations are used to assess whether perceived biodiversity drives funding or vice versa.Results  Funding explained 65% of variation in perceived biodiversity patterns – six times more variation than accounted for by 34 candidate environmental factors. Cross‐correlation analysis showed that funding is likely to be driving conservation priorities and not vice versa. It was also apparent that investment itself may trigger further investments as a result of reduced start‐up costs for new projects in areas where infrastructure already exists. It is therefore difficult to establish whether funding, perceived biodiversity, or both drive further funding. However, in all cases, the results suggest that regional assessments of biodiversity conservation importance may be biased by investment. Funding effects might also confound studies on mechanisms of species richness patterns.Main conclusions  Continued biodiversity loss commands urgent conservation action even if our knowledge of its whereabouts is incomplete; however, by concentrating inventory funds in areas already perceived as important in terms of biodiversity and/or where start‐up costs are lower, we risk losing other areas of underestimated or unknown value.

China is investing immense resources for planting trees, totalling more than US$ 100 billion in the past decade alone. Every year, China reports more afforestation than the rest of the world combined. Here, we show that China's forest cover gains are highly definition-dependent. If the definition of ‘forest’ follows FAO criteria (including immature and temporarily unstocked areas), China has gained 434 000 km ² between 2000 and 2010. However, remotely detectable gains of vegetation that non-specialists would view as forest (tree cover higher than 5 m and minimum 50% crown cover) are an order of magnitude less (33 000 km ² ). Using high-resolution maps and environmental modelling, we estimate that approximately 50% of the world's forest with minimum 50% crown cover has been lost in the past approximately 10 000 years. China historically lost 1.9–2.7 million km ² (59–67%), and substantial losses continue. At the same time, most of China's afforestation investment targets environments that our model classes as unsuitable for trees. Here, gains detectable via satellite imagery are limited. Conversely, the regions where modest gains are detected are environmentally suitable but have received little afforestation investment due to conflicting land-use demands for agriculture and urbanization. This highlights the need for refined forest monitoring, and greater consideration of environmental suitability in afforestation programmes.