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The National Land Cover Database (NLCD) provides time-series data characterizing the land surface for the United States, including land cover and tree canopy cover (NLCD-TC). NLCD-TC was first published for 2001, followed by versions for 2011 (released in 2016) and 2011 and 2016 (released in 2019). As the only nationwide tree canopy layer, there is value in assessing NLCD-TC accuracy, given the need for cross-city comparisons of urban forest characteristics. Accuracy assessments have only been conducted for the 2001 data and suggest substantial inaccuracies for that dataset in cities. For the most recent NLCD-TC version, we used various datasets that characterize the built environment, weather, and climate to assess their accuracy in different contexts within 27 cities. Overall, NLCD underestimates tree canopy in urban areas by 9.9% when compared to estimates derived from those high-resolution datasets. Underestimation is greater in higher-density urban areas (13.9%) than in suburban areas (11.0%) and undeveloped areas (6.4%). To evaluate how NLCD-TC error in cities could be reduced, we developed a decision tree model that uses various remotely sensed and built-environment datasets such as building footprints, urban morphology types, NDVI (Normalized Difference Vegetation Index), and surface temperature as explanatory variables. This predictive model removes bias and improves the accuracy of NLCD-TC by about 3%. Finally, we show the potential applications of improved urban tree cover data through the examples of ecosystem accounting in Seattle, WA, and Denver, CO. The outputs of rainfall interception and urban heat mitigation models were highly sensitive to the choice of tree cover input data. Corrected data brought results closer to those from high-resolution model runs in all cases, with some variation by city, model, and ecosystem type. This suggests paths forward for improving the quality of urban environmental models that require tree canopy data as a key model input.

Intensive tree cover loss and gain have been significantly influencing the environment and society. It is essential to identify the potential factors and to evaluate their importance. A large body of literature has investigated the factors influencing tree cover loss, usually at the global or regional scale and focusing on the quantity issue: how are the rate and extent of tree cover loss influenced by different factors? This paper has two objectives. The first is to pinpoint factors influencing the locations of tree cover loss and gain (the location issue) at the pixel level. The second is to evaluate the heterogeneous importance of factors in two periods of 1991 through 2002 and 2002 through 2013 and in four counties within the Li River Basin, Guangxi Zhuang Autonomous Region, China. The random forests technique was adopted to model the responses of tree cover loss and gain probabilities of sampled pixels to initial landscape pattern factors, biophysical factors and proximity factors. A ranking of factor importance and a set of important factors were derived for each county and time period. The partial dependence plots were generated for the most important factors to reveal how exactly tree cover loss and gain probabilities change as influenced by these factors. The results confirmed that factor importance varied across time and space, and the variability of proximity factors and initial landscape pattern factors were more pronounced. The furthered understanding of the heterogeneous importance of different factors on the locations of tree cover loss and gain can support more sustainable forest management practices and the development of more effective policies regarding ecosystem conservation and economic development.

Despite global recognition of the social, economic and ecological impacts of deforestation, the world is losing forests at an alarming rate. Global and regional efforts by policymakers and donors to reduce deforestation need science-driven information on where forest loss is happening, and where it may happen in the future. We used spatially-explicit globally-consistent variables and global historical tree cover and loss to analyze how global- and regional-scale variables contributed to historical tree cover loss and to model future risks of tree cover loss, based on a business-as-usual scenario. Our results show that (1) some biomes have higher risk of tree cover loss than others; (2) variables related to tree cover loss at the global scale differ from those at the regional scale; and (3) variables related to tree cover loss vary by continent. By mapping both tree cover loss risk and potential future tree cover loss, we aim to provide decision makers and donors with multiple outputs to improve targeting of forest conservation investments. By making the outputs readily accessible, we anticipate they will be used in other modeling analyses, conservation planning exercises, and prioritization activities aimed at conserving forests to meet national and global climate mitigation targets and biodiversity goals.

It has been suggested that tropical forest and savanna could represent alternative stable states, implying critical transitions at tipping points in response to altered climate or other drivers. So far, evidence for this idea has remained elusive, and integrated climate models assume smooth vegetation responses. We analyzed data on the distribution of tree cover in Africa, Australia, and South America to reveal strong evidence for the existence of three distinct attractors: forest, savanna, and a treeless state. Empirical reconstruction of the basins of attraction indicates that the resilience of the states varies in a universal way with precipitation. These results allow the identification of regions where forest or savanna may most easily tip into an alternative state, and they pave the way to a new generation of coupled climate models.

The protection of forests is crucial to providing important ecosystem services, such as supplying clean air and water, safeguarding critical habitats for biodiversity, and reducing global greenhouse gas emissions. Despite this importance, global forest loss has steadily increased in recent decades. Protected Areas (PAs) currently account for almost 15% of Earth’s terrestrial surface and protect 5% of global tree cover and were developed as a principal approach to limit the impact of anthropogenic activities on natural, intact ecosystems and habitats. We assess global trends in forest loss inside and outside of PAs, and land cover following this forest loss, using a global map of tree cover loss and global maps of land cover. While forests in PAs experience loss at lower rates than non-protected forests, we find that the temporal trend of forest loss in PAs is markedly similar to that of all forest loss globally. We find that forest loss in PAs is most commonly—and increasingly—followed by shrubland, a broad category that could represent re-growing forest, agricultural fallows, or pasture lands in some regional contexts. Anthropogenic forest loss for agriculture is common in some regions, particularly in the global tropics, while wildfires, pests, and storm blowdown are a significant and consistent cause of forest loss in more northern latitudes, such as the United States, Canada, and Russia. Our study describes a process for screening tree cover loss and agriculture expansion taking place within PAs, and identification of priority targets for further site-specific assessments of threats to PAs. We illustrate an approach for more detailed assessment of forest loss in four case study PAs in Brazil, Indonesia, Democratic Republic of Congo, and the United States.

\"In this new edition of Forest Canopies, over 50 scientists and educators from around the world examine the biodiversity, ecology, evolution, and conservation of forest canopy ecosystems. This book explores the discoveries and opportunities that have emerged in the treetops of the world and offers an authoritative synthesis of studies in ecology and evolution.\" \"Forest Canopies is intended for ecologists, botanists, foresters, naturalists, policymakers, zoologists, conservationists, researchers, educators, students, and anyone interested in forest canopies and the life that they support above the forest floor.\"--Jacket.

We examined the distribution of heat risk-related land cover (HRRLC) characteristics across racial/ethnic groups and degrees of residential segregation. Block group-level tree canopy and impervious surface estimates were derived from the 2001 National Land Cover Dataset for densely populated urban areas of the United States and Puerto Rico, and linked to demographic characteristics from the 2000 Census. Racial/ethnic groups in a given block group were considered to live in HRRLC if at least half their population experienced the absence of tree canopy and at least half of the ground was covered by impervious surface (roofs, driveways, sidewalks, roads). Residential segregation was characterized for metropolitan areas in the United States and Puerto Rico using the multigroup dissimilarity index. After adjustment for ecoregion and precipitation, holding segregation level constant, non-Hispanic blacks were 52% more likely (95% CI: 37%, 69%), non-Hispanic Asians 32% more likely (95% CI: 18%, 47%), and Hispanics 21% more likely (95% CI: 8%, 35%) to live in HRRLC conditions compared with non-Hispanic whites. Within each racial/ethnic group, HRRLC conditions increased with increasing degrees of metropolitan area-level segregation. Further adjustment for home ownership and poverty did not substantially alter these results, but adjustment for population density and metropolitan area population attenuated the segregation effects, suggesting a mediating or confounding role. Land cover was associated with segregation within each racial/ethnic group, which may be explained partly by the concentration of racial/ethnic minorities into densely populated neighborhoods within larger, more segregated cities. In anticipation of greater frequency and duration of extreme heat events, climate change adaptation strategies, such as planting trees in urban areas, should explicitly incorporate an environmental justice framework that addresses racial/ethnic disparities in HRRLC.

Woody encroachment in ‘open’ biomes like grasslands and savannahs is occurring globally. Both local and global drivers, including elevated CO2, have been implicated in these increases. The relative importance of different processes is unresolved as there are few multi-site, multi-land-use evaluations of woody plant encroachment. We measured 70 years of woody cover changes over a 1020 km2 area covering four land uses (commercial ranching, conservation with elephants, conservation without elephants and communal rangelands) across a rainfall gradient in South African savannahs. Different directions of woody cover change would be expected for each different land use, unless a global factor is causing the increases. Woody cover change was measured between 1940 and 2010 using the aerial photo record. Detection of woody cover from each aerial photograph was automated using eCognitions' Object-based image analysis (OBIA). Woody cover doubled in all land uses across the rainfall gradient, except in conservation areas with elephants in low-rainfall savannahs. Woody cover in 2010 in low-rainfall savannahs frequently exceeded the maximum woody cover threshold predicted for African savannahs. The results indicate that a global factor, of which elevated CO2 is the likely candidate, may be driving encroachment. Elephants in low-rainfall savannahs prevent encroachment and localized megafaunal extinction is a probable additional cause of encroachment. This article is part of the themed issue ‘Tropical grassy biomes: linking ecology, human use and conservation’.

Disturbances from fire and herbivory strongly affect savanna vegetation dynamics. In some savannas, fire especially may be instrumental in preserving the coexistence of trees and grasses. The role of herbivory by large mammals is less clear; herbivory has been shown variously to promote and to suppress tree establishment. Here we ask how interactions between herbivory and fire act to shape savanna vegetation dynamics via their effects on tree populations in Hluhluwe iMfolozi Park in KwaZulu Natal, South Africa, a savanna with a full complement of native large mammals. We examined the effects of herbivore exclusion on tree growth, mortality, and seedling establishment from 2000 to 2007 at 10 sites located in areas of low and high herbivore pressure throughout the park. Results were analyzed statistically and using Leslie matrix models of population dynamics. Herbivory and fire acted primarily to suppress sapling growth rather than on sapling mortality or seedling establishment. This indicates that browsing, like fire, suppresses tree density by imposing a demographic bottleneck on the maturation of saplings to adults. Model results suggest that, while browsing and fire each alone impacted growth, a combination of browsing and fire had much greater effects on tree density. Only fire and browsing together were able to prevent increases in tree density. These results suggest that, while soil resources, including nutrients and moisture, are probably instrumental in determining tree growth rates, disturbances from fire and herbivory may be instrumental in limiting tree cover and facilitating the coexistence of trees and grasses in savannas.

China is reported as the leading country in the Earth's greening. However, it is a challenge to capture the gradual recovery in forest cover and distinguish the contribution of trees from herbaceous vegetation using remote sensing data. We developed a new fractional tree cover product (GLOBMAP FTC China) from MODIS time series data to investigate change patterns of China's forests during 2000–2022. This annual product showed high consistency with China's National Forest Inventory. We found a significant increase (∼4 Mha/year) in the annual forest area in China from ∼154.47 Mha in 2000 to ∼236.01 Mha in 2015. This rate then slowed by 50% in 2015–2022 (∼2 Mha/year). The forest recovery primarily started in 2000–2004, and reached saturation in 2015. It was primarily contributed by the tree cover gain (92%) from forest conservation and restoration programs. Our findings can support forest management and carbon neutrality achievement for the country. Plain Language Summary As the largest carbon reservoir in terrestrial ecosystems, forests are an indispensable part of China's carbon sink. Explicitly monitoring when, where, and how the forest recovery happening in China is crucial. In this work, a fractional tree cover product (named GLOBMAP FTC China) is generated, providing the coverage of trees within pixels. Compared to other remote sensing products, this product is proved to have the best consistency with China's National Forest Inventory (NFI). Applying the product for analysis, we found that China's forests have been recovering since 2000, and the increasing rate then slowed by 50% after 2015. Forest area in southwestern China shows the fastest increasing rate during 2000–2022, which is more than 0.2 Mha per year. The changes primarily show a stepwise transition from forests with a low fractional tree cover to forests with a higher fractional tree cover, which mainly thanks to the forest conservation and restoration programs. This study underscores that trees' growth dominates the greening in China's forests, highlighting the importance of the new fractional tree cover product for future accurate forest change studies and implications for forest management. Our findings are crucial for climate change mitigation as proposed by the Paris Agreement. Key Points This work generates a fractional tree cover product GLOBMAP to separate the mixed effect of herbaceous vegetation from woody cover Using GLOBMAP, we can obtain detailed and nuanced forest recovery in China, which is consistent with China's National Forest Inventory During 2000–2022, China's forests primarily presented as a stepwise transition from low tree cover forests to higher ones