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Anthropogenic features such as urbanization, roads, and power lines, are increasing in western United States landscapes in response to rapidly growing human populations. However, their spatial effects have not been evaluated. Our goal was to model the human footprint across the western United States. We first delineated the actual area occupied by anthropogenic features, the physical effect area. Next, we developed the human footprint model based on the ecological effect area, the zone influenced by features beyond their physical presence, by combining seven input models: three models quantified top-down anthropogenic influences of synanthropic predators (avian predators, domestic dog and cat presence risk), and four models quantified bottom-up anthropogenic influences on habitat (invasion of exotic plants, human-caused fires, energy extraction, and anthropogenic wildland fragmentation). Using independent bird population data, we found bird abundance of four synanthropic species to correlate positively with human footprint intensity and negatively for three of the six species influenced by habitat fragmentation. We then evaluated the extent of the human footprint in relation to terrestrial (ecoregions) and aquatic systems (major rivers and lakes), regional management and conservation status, physical environment, and temporal changes in human actions. The physical effect area of anthropogenic features covered 13% of the western United States with agricultural land (9.8%) being most dominant. High-intensity human footprint areas (class 8-10) overlapped highly productive low-elevation private landholdings and covered 7% of the western United States compared to 48% for low-intensity areas (class 1-3), which were confined to low-productivity high-elevation federal landholdings. Areas within 1 km of rivers were more affected by the human footprint compared to lakes. Percentage human population growth was higher in low-intensity human footprint areas. The disproportional regional effects of the human footprint on landscapes in the western United States create a challenge to management of ecosystems and wildlife populations. Using footprint models, managers can plan land use actions, develop restoration scenarios, and identify areas of high conservation value at local landscapes within a regional context. Moreover, human footprint models serve as a tool to stratify landscapes for studies investigating floral and faunal response to human disturbance intensity gradients.

One-sixth of the global terrestrial surface nowfallswithin protected areas (PAs), making it essential to understand how far they mitigate the increasing pressures on nature which characterize the Anthropocene. In by far the largest analysis of this question to date and not restricted to forested PAs, we compiled data from 12,315 PAs across 152 countries to investigate their ability to reduce human pressure and how this varies with socioeconomic and management circumstances. While many PAs show positive outcomes, strikingly we find that compared with matched unprotected areas, PAs have on average not reduced a compound index of pressure change over the past 15 y. Moreover, in tropical regions average pressure change from cropland conversion has increased inside PAs even more than in matched unprotected areas. However, our results also confirm previous studies restricted to forest PAs, where pressures are increasing, but less than in counterfactual areas. Our results also show that countries with high national-level development scores have experienced lower rates of pressure increase over the past 15 y within their PAs compared with a matched outside area. Our results caution against the rapid establishment of new PAs without simultaneously addressing the conditions needed to enable their success.

Changes in vegetation activity are driven by multiple natural and anthropogenic factors, which can be reflected by Normalized Difference Vegetation Index (NDVI) derived from satellites. In this paper, NDVI trends from 1982 to 2012 are first estimated by the Theil–Sen median slope method to explore their spatial and temporal patterns. Then, the impact of climate variables and human activity on the observed NDVI trends is analyzed. Our results show that on average, NDVI increased by 0.46 × 10−3 per year from 1982 to 2012 globally with decadal variations. For most regions of the world, a greening (increasing)–browning (decreasing)–greening (G-B-G) trend is observed over the periods 1982–2004, 1995–2004, and 2005–2012, respectively. A positive partial correlation of NDVI and temperature is observed in the first period but it decreases and occasionally becomes negative in the following periods, especially in the Humid Temperate and Dry Domain Regions. This suggests a weakened effect of temperature on vegetation growth. Precipitation, on the other hand, is found to have a positive impact on the NDVI trend. This effect becomes stronger in the third period of 1995–2004, especially in the Dry Domain Region. Anthropogenic effects and human activities, derived here from the Human Footprint Dataset and the associated Human Influence Index (HII), have varied impacts on the magnitude (absolute value) of the NDVI trends across continents. Significant positive effects are found in Asia, Africa, and Europe, suggesting that intensive human activity could accelerate the change in NDVI and vegetation. A more accurate attribution of vegetation change to specific climatic and anthropogenic factors is instrumental to understand vegetation dynamics and requires further research.

It is widely accepted that the main driver of the observed decline in biological diversity is increasing human pressure on Earth's ecosystems. However, the spatial patterns of change in human pressure and their relation to conservation efforts are less well known. We developed a spatially and temporally explicit map of global change in human pressure over 2 decades between 1990 and 2010 at a resolution of 10 km². We evaluated 22 spatial data sets representing different components of human pressure and used them to compile a temporal human pressure index (THPI) based on 3 data sets: human population density, land transformation, and electrical power infrastructure. We investigated how the THPI within protected areas was correlated to International Union for Conservation of Nature (IUCN) management categories and the human development index (HDI) and how the THPI was correlated to cumulative pressure on the basis of the original human footprint index. Since the early 1990s, human pressure increased 64% of the terrestrial areas; the largest increases were in Southeast Asia. Protected areas also exhibited overall increases in human pressure, the degree of which varied with location and IUCN management category. Only wilderness areas and natural monuments (management categories Ib and III) exhibited decreases in pressure. Protected areas not assigned any category exhibited the greatest increases. High HDI values correlated with greater reductions in pressure across protected areas, while increasing age of the protected area correlated with increases in pressure. Our analysis is an initial step toward mapping changes in human pressure on the natural world over time. That only 3 data sets could be included in our spatio‐temporal global pressure map highlights the challenge to measuring pressure changes over time.

Human impact on the environment is evident across the planet, including its most biodiverse areas. Of particular interest is the impact on the world’s last wilderness areas, in which the largest patches of land relatively free from human influence remain. Here, we use the human footprint index to measure the extent to which the world’s last wilderness areas have been impacted by human activities—between the years 1993 and 2009—and whether protected areas have been effective in reducing human impact. We found that overall the increase in human footprint was higher in tropical than temperate regions. Moreover, although on average the increase was lower inside protected areas than outside, in half of the fourteen biomes examined the differences were insignificant. Although reasons varied, protected areas alone are unlikely to be ubiquitously successful in protecting wilderness areas. To achieve protection, it is important to address loss and improve environmental governance.

Aim Maintaining connectivity is critical for long‐term persistence of wild carnivores in landscapes fragmented due to anthropogenic activity. We examined spatial genetic structure and the impact of landscape features on genetic structure in four widespread species—jungle cat (Felis chaus), leopard (Panthera pardus), sloth bear (Melursus ursinus) and tiger (Panthera tigris). Location Our study was carried out in the central Indian landscape, a stronghold in terms of distribution and abundance of large mammals. The landscape comprises fragmented forests embedded in a heterogeneous matrix of multiple land use types. Methods Microsatellite data from non‐invasively sampled individuals (90 jungle cats, 82 leopards, 104 sloth bears and 117 tigers) were used to investigate genetic differentiation. Impact of landscape features on genetic structure was inferred using a multimodel landscape resistance optimization approach. Results All four study species revealed significant isolation by distance (IBD). The correlation between genetic and geographic distance was significant only over a short distance for jungle cat, followed by longer distances for sloth bear, leopard and tiger. Overall, human footprint had a high negative impact on gene flow in tigers, followed by leopards, sloth bears and the least on jungle cats. Individual landscape variables—land use, human population density, density of linear features and roads—impacted the study species differently. Although land use was found to be an important variable explaining genetic structure for all four species, the amount of variation explained, and the optimum spatial resolution and the resistance values of different land use classes varied. Main conclusions As expected from theory, but rarely demonstrated using empirical data, the pattern of spatial autocorrelation of genetic variation scaled with dispersal ability and density of the study species. Landscape genetic analyses revealed species‐specific impact of landscape features and provided insights into interactions between species biology and landscape structure. Our results emphasize the need for incorporating functional connectivity data from multiple species for landscape‐level conservation planning.

Global landscapes are changing due to human activities with consequences for both biodiversity and ecosystems. For single species, terrestrial mammal population densities have shown mixed responses to human pressure, with both increasing and decreasing densities reported in the literature. How the impacts of human activities on mammal populations translates into altered global density patterns remains unclear. Here we aim to disentangle the effect of human impacts on large‐scale patterns of mammal population densities using a global dataset of 6729 population density estimates for 468 mammal species (representing 59% and 44% of mammalian orders and families). We fitted a mixed effect model to explain the variation in density based on a 1‐degree resolution as a function of the human footprint index (HFI), a global proxy of direct and indirect human disturbances, while accounting for body mass, trophic level and primary productivity (normalized vegetation index; NDVI). We found a significant positive relationship between population density and HFI, where population densities were higher in areas with a higher HFI (e.g. agricultural or suburban areas – no populations were located in very high HFI urban areas) compared to areas with a low HFI (e.g. wilderness areas). We also tested the effect of the individual components of the HFI and still found a consistent positive effect. The relationships remained positive even across populations of the same species, although variability among species was high. Our results indicate shifts in mammal population densities in human modified landscapes, which is due to the combined effect of species filtering, increased resources and a possible reduction in competition and predation. Our study provides further evidence that macroecological patterns are being altered by human activities, where some species will benefit from these activities, while others will be negatively impacted or even extirpated.

Human activities’ negative impact on biodiversity is undisputed, but debate remains vivid on their effect on species richness, a key index in ecology and conservation. While some studies suggest that species richness declines with human pressure, others show that it can be insensitive or even respond positively to some human pressure, because some species (“losers”) are replaced by others (“winners”). However, many winners are favored by intermediate pressure but decline when pressure becomes too high, and we can thus expect species richness to decline above a certain human pressure. Analyzing eBird data in tropical forests, I find that, under a certain threshold, increasing human footprint causes important composition changes, with losers (habitat specialist, endemic, sensitive, and threatened species) being replaced by winners (habitat non-specialist, large-range, human-tolerant, anthropophilic, and non-native species), resulting in a slight increase in species richness. Above this threshold though, richness in winners stops increasing (except for anthropophilic and non-native species), leading to a steep decline in overall species richness. I find that the shape of species richness response to human footprint varies between regions (comparing results from the North America Breeding Bird Survey, PREDICTS database, and eBird data across eight biodiversity hotspots) and identify five different trajectories in species richness response to human pressure. I suggest that they can be classified depending on their slope and monotony in the “replace then remove framework,” unifying contradictory effects of human pressure on species richness.

The human footprint index (HFI) is an extensively used tool for interpreting the accelerating pressure of humanity on Earth. Up to now, the process of creating the HFI has required significant data and modeling, and updated versions of the index often lag the present day by many years. Here we introduce a near-present, global-scale machine learning-based HFI (ml-HFI) which is capable of routine update using satellite imagery alone. We present the most up-to-date map of the HFI, and document changes in human pressure during the past 20 years (2000–2019). Moreover, we demonstrate its utility as a monitoring tool for the United Nations Sustainable Development Goal 15 (SDG15), ‘Life on Land’, which aims to foster sustainable development while conserving biodiversity. We identify 43 countries that are making progress toward SDG15 while also experiencing increases in their ml-HFI. We examine a subset of these in the context of conservation policies that may or may not enable continued progress toward SDG15. This has immediate policy relevance, since the majority of countries globally are not on track to achieve Goal 15 by the declared deadline of 2030. Moving forward, the ml-HFI may be used for ongoing monitoring and evaluation support toward the twin goals of fostering a thriving society and global Earth system.

In the United States, systemic racism has had lasting effects on the structure of cities, specifically due to government-mandated redlining policies that produced racially segregated neighborhoods that persist today. However, it is not known whether varying habitat structures and natural resource availability associated with racial segregation affect the demographics and evolution of urban wildlife populations. To address this question, we repurposed and reanalyzed publicly archived nuclear genetic data from 7,698 individuals spanning 39 terrestrial vertebrate species sampled in 268 urban locations throughout the United States. We found generally consistent patterns of reduced genetic diversity and decreased connectivity in neighborhoods with fewer White residents, likely because of environmental differences across these neighborhoods. The strength of relationships between the racial composition of neighborhoods, genetic diversity, and differentiation tended to be weak relative to other factors affecting genetic diversity, possibly in part due to the recency of environmental pressures on urban wildlife populations. However, the consistency of the direction of effects across disparate taxa suggest that systemic racism alters the demography of urban wildlife populations in ways that generally limit population sizes and negatively affect their chances of persistence. Our results thus support the idea that limited capacity to support large, well-connected wildlife populations reduces access to nature and builds on existing environmental inequities shouldered by predominantly non-White neighborhoods.