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Abstract Proactively identifying where land conversion might occur is critical to targeted and effective conservation planning. Previous efforts to map future habitat loss have largely focused on forested systems and have been limited in their consideration of drivers of loss. We developed a 1-km resolution, global map of land conversion pressure from multiple drivers, referred to as the conversion pressure index (CPI). The CPI combines past rates of anthropogenic change, as measured by temporal human modification maps, with suitability maps for potential future expansion by large-scale development. The CPI thus offers a new way to measure a cumulative gradient of anthropogenic pressure as opposed to categorical land cover change. We find that nearly 23% of land across 200 countries have relatively high conversion pressure, potentially impacting over 460 million ha of intact natural lands. We illustrate how this information can be used to identify areas for proactive conservation to avoid future loss and ensure that national commitments under the Kunming-Montreal Global Biodiversity and Paris Agreement Climate Frameworks are upheld.

Abstract Measuring connectivity is key to track progress toward broad conservation goals, such as the United Nations Convention on Biological Diversity's proposed Post‐2020 Global Biodiversity Framework. The framework includes an area‐based target for the protection of 30% of lands and seas globally—through well‐connected systems of protected areas. Although the field of connectivity science has grown rapidly, limited progress has been made in tracking conservation connectivity in practice. This is in part due to the lack of a standardizing framework to clarify different purposes, approaches, and datasets—particularly in differentiating a metric from its application within a broader connectivity framework—as well as a benchmark to quantitatively compare alternative approaches. To address this science‐practice gap, we developed a novel metric of connectivity called the Protected Network metric (ProNet). ProNet is designed to assess the structural connectivity of a protected area network in a way that can be easily described, clearly communicated, and rapidly computed at high resolution. We evaluated how ProNet adheres to fundamental conservation science principles using a library of hypothetical landscapes, compared it to two commonly used existing connectivity metrics, and demonstrated its performance in assessing connectivity for a set of real‐world landscapes selected across the gradient of human modification. More broadly, ProNet is a powerful tool to galvanize emerging connectivity conservation as a countermeasure to increasing fragmentation of global ecosystems.

Abstract Protecting or restoring habitat connectivity in landscapes undergoing rapid environmental change requires multiple conservation and restoration strategies. These strategies have different risk profiles, costs, and require various types of technical expertise to conduct. This diversity in landscape context and strategic approach requires more nuance and flexibility than traditional connectivity conservation plans have supported. We present a novel, spatially‐explicit framework for developing connectivity conservation priorities and strategies based on Omniscape, an adaptation of Circuitscape, a common tool for mapping habitat connectivity. Using California (USA) as a case study, we mapped structural connectivity and developed a classification of connectivity conservation and restoration categories across the gradient of land use intensities, as well as by land ownership. The most constrained areas with highly concentrated flow (movement potential) make up 3% of the state and occur primarily on private lands. Conversely, intact areas with diffuse flow that indicate multiple connectivity options cover 55% of the state, including the majority of the desert and mountain ecoregions. This “strategy mapping” approach can be used to identify priority areas for conservation investment and suites of potential implementation mechanisms and partners, which in turn may improve the efficiency and effectiveness of connectivity conservation in this era of global change.

Abstract Although natural habitats are being lost globally, the extent and fate of natural habitats on private lands in the United States have not been quantified at the resolution relevant for conservation planning. Here we provide information on the locations and risk of loss of areas of natural vegetation cover (NVC) on private lands across the northwestern United States to motivate discussion on needs and opportunities to slow their loss. Specific questions were as follows: (1) Where are the remaining areas of NVC on private lands? (2) Which regions and communities have had the highest loss rates of NVC? and (3) In which socioecological settings is NVC at greatest risk of loss? NVC location and change were mapped using two land cover classifications during 2001–2011, the most recent period with available data. Associations between NVC loss and market proximity, demographic, infrastructure, natural amenity, and climate factors were used to model probability of NVC loss in 2011. We found that NVC covered 64% of the study area in 2011. During 2001–2011, 2.5% of the area of NVC in 2001 was converted to development and croplands. Rates of loss were as high as 12% in some regions (e.g., western Washington). Housing development accounted for the majority of this NVC loss, increasing by 8% while croplands increased by 5%. Conversion of NVC for development and crops during 2001–2011 per capita varied 20–40 fold among “city spheres” (urban areas >10,000 people and 40‐min commuting distance). NVC loss was statistically associated with urban fringe development, forest edge vegetation, proximity to highways, public land, and waterbodies and was associated with New West demographic city spheres. Of the NVC on private lands in 2011, 11% was projected to have >20% probability of future loss over the next decade. We conclude that portions of the northwestern United States, one of the last stronghold for extensive natural habitats in the contiguous United States, are rapidly losing NVC to development, particularly in the New West communities that typically have the highest motivation and capacity to conserve them.

Abstract Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors.

Recent guidance on environmental modeling and global land-cover validation stresses the need for a probability-based design. Additionally, spatial balance has also been recommended as it ensures more efficient sampling, which is particularly relevant for understanding land use change. In this paper I describe a global sample design and database called the Global Grid (GG) that has both of these statistical characteristics, as well as being flexible, multi-scale, and globally comprehensive. The GG is intended to facilitate collaborative science and monitoring of land changes among local, regional, and national groups of scientists and citizens, and it is provided in a variety of open source formats to promote collaborative and citizen science. Since the GG sample grid is provided at multiple scales and is globally comprehensive, it provides a universal, readily-available sample. It also supports uneven probability sample designs through filtering sample locations by user-defined strata. The GG is not appropriate for use at locations above ±85° because the shape and topological distortion of quadrants becomes extreme near the poles. Additionally, the file sizes of the GG datasets are very large at fine scale (resolution ~600 m × 600 m) and require a 64-bit integer representation.

In the United States, citizens, policy makers, and natural resource managers alike have become concerned about urban sprawl, both locally and nationally. Most assessments of sprawl, or undesired growth patterns, have focused on quantifying land-use changes in urban and metropolitan areas. It is critical for ecologists to examine and improve understanding of land-use changes beyond the urban fringe - also called exurban sprawl - because of the extensive and widespread changes that are occurring, and which often are located adjacent to or nearby "protected" lands. The primary goal of this paper is to describe the development of a nationwide, fine-grained database of historical, current, and forecasted housing density, which enables these changes to be quantified as a foundation for inference of possible ecological effects. Forecasted patterns were generated by the Spatially Explicit Regional Growth Model, which relates historical growth patterns with accessibility to urban and protected lands. Secondary goals are to report briefly on the status and trend of exurban land-use changes across the U.S., and to introduce a landscape sprawl metric that captures patterns of land-use change. In 2000, there were 125 729 km2 in urban and suburban (

We evaluate the world terrestrial network of protected areas (PAs) for its partnership potential in responding to climate change. That is, if a PA engaged in collaborative, trans-boundary management of species, by investing in conservation partnerships with neighboring areas, what climate change adaptation benefits might accrue? We consider core tenets of conservation biology related to protecting large areas with high environmental heterogeneity and low climate change velocity and ask how a series of biodiversity adaptation indicators change across spatial scales encompassing potential PA and non-PA partners. Less than 1% of current world terrestrial PAs equal or exceed the size of established and successful conservation partnerships. Partnering at this scale would increase the biodiversity adaptation indicators by factors up to two orders of magnitude, compared to a null model in which each PA is isolated. Most partnership area surrounding PAs is comprised of non-PAs (70%), indicating the importance of looking beyond the current network of PAs when promoting climate change adaptation. Given monumental challenges with PA-based species conservation in the face of climate change, partnerships provide a logical and achievable strategy for helping areas adapt. Our findings identify where strategic partnering efforts in highly vulnerable areas of the world may prove critical in safeguarding biodiversity.

Riparian habitats have been frequently identified as priority areas for conservation under climate change because they span climatic gradients and have cool, moist microclimates relative to surrounding areas. They are therefore expected to act as dispersal corridors for climate-induced species range shifts and to provide microclimatic refugia from warming. Despite recognition of these values, rigorous methods to identify which riparian areas are most likely to facilitate range shifts and provide refugia are currently lacking. We completed a novel analysis across the Pacific Northwest, USA, that identifies potential riparian corridors featuring characteristics expected to enhance their ability to facilitate range shifts and provide refugia. These features include large temperature gradients, high canopy cover, large relative width, low exposure to solar radiation, and low levels of human modification. These variables were used to calculate a riparian climate-corridor index using a multi-scale approach that incorporates results ranging in scale from local watersheds to the entire Pacific Northwest. Resulting index values for potential riparian corridors in the Pacific Northwest were highest within mountainous areas and lowest within relatively flat, lowland regions. We also calculated index values within ecoregions, to better identify high-value riparian climate corridors within the relatively flat, degraded areas where they may most contribute to climate adaptation. We found that high-value riparian climate-corridors are least protected in flat, lowland areas, suggesting that such corridors should be high priorities for future conservation effort. Our analysis provides critical information on valuable riparian climate-corridors to guide climate adaptation efforts (and riparian management and restoration efforts) in the Pacific Northwest, while offering a novel approach that may be applied to similar efforts in other geographies.

Conservation scientists emphasize the importance of maintaining a connected network of protected areas to prevent ecosystems and populations from becoming isolated, reduce the risk of extinction, and ultimately sustain biodiversity. Keeping protected areas connected in a network is increasingly recognized as a conservation priority in the current era of rapid climate change. Models that identify suitable linkages between core areas have been used to prioritize potentially important corridors for maintaining functional connectivity. Here, we identify the most "natural" (i.e., least human-modified) corridors between large protected areas in the contiguous Unites States. We aggregated results from multiple connectivity models to develop a composite map of corridors reflecting agreement of models run under different assumptions about how human modification of land may influence connectivity. To identify which land units are most important for sustaining structural connectivity, we used the composite map of corridors to evaluate connectivity priorities in two ways: (1) among land units outside of our pool of large core protected areas and (2) among units administratively protected as Inventoried Roadless (IRAs) or Wilderness Study Areas (WSAs). Corridor values varied substantially among classes of "unprotected" non-core land units, and land units of high connectivity value and priority represent diverse ownerships and existing levels of protections. We provide a ranking of IRAs and WSAs that should be prioritized for additional protection to maintain minimal human modification. Our results provide a coarse-scale assessment of connectivity priorities for maintaining a connected network of protected areas.

Key to understanding the implications of climate and land use change on biodiversity and natural resources is to incorporate the physiographic platform on which changes in ecological systems unfold. Here, we advance a detailed classification and high-resolution map of physiography, built by combining landforms and lithology (soil parent material) at multiple spatial scales. We used only relatively static abiotic variables (i.e., excluded climatic and biotic factors) to prevent confounding current ecological patterns and processes with enduring landscape features, and to make the physiographic classification more interpretable for climate adaptation planning. We generated novel spatial databases for 15 landform and 269 physiographic types across the conterminous United States of America. We examined their potential use by natural resource managers by placing them within a contemporary climate change adaptation framework, and found our physiographic databases could play key roles in four of seven general adaptation strategies. We also calculated correlations with common empirical measures of biodiversity to examine the degree to which the physiographic setting explains various aspects of current biodiversity patterns. Additionally, we evaluated the relationship between landform diversity and measures of climate change to explore how changes may unfold across a geophysical template. We found landform types are particularly sensitive to spatial scale, and so we recommend using high-resolution datasets when possible, as well as generating metrics using multiple neighborhood sizes to both minimize and characterize potential unknown biases. We illustrate how our work can inform current strategies for climate change adaptation. The analytical framework and classification of landforms and parent material are easily extendable to other geographies and may be used to promote climate change adaptation in other settings.

Wild pigs (Sus scrofa), also known as wild swine, feral pigs, or feral hogs, are one of the most widespread and successful invasive species around the world. Wild pigs have been linked to extensive and costly agricultural damage and present a serious threat to plant and animal communities due to their rooting behavior and omnivorous diet. We modeled the current distribution of wild pigs in the United States to better understand the physiological and ecological factors that may determine their invasive potential and to guide future study and eradication efforts. Using national-scale wild pig occurrence data reported between 1982 and 2012 by wildlife management professionals, we estimated the probability of wild pig occurrence across the United States using a logistic discrimination function and environmental covariates hypothesized to influence the distribution of the species. Our results suggest the distribution of wild pigs in the U.S. was most strongly limited by cold temperatures and availability of water, and that they were most likely to occur where potential home ranges had higher habitat heterogeneity, providing access to multiple key resources including water, forage, and cover. High probability of occurrence was also associated with frequent high temperatures, up to a high threshold. However, this pattern is driven by pigs' historic distribution in warm climates of the southern U.S. Further study of pigs' ability to persist in cold northern climates is needed to better understand whether low temperatures actually limit their distribution. Our model highlights areas at risk of invasion as those with habitat conditions similar to those found in pigs' current range that are also near current populations. This study provides a macro-scale approach to generalist species distribution modeling that is applicable to other generalist and invasive species.

Land cover maps reasonably depict areas that are strongly converted by human activities, but typically are unable to resolve low-density but widespread development patterns. Data products specifically designed to resolve land uses complement land cover datasets and likely improve our ability to understand the extent and complexity of human modification. Methods for developing a comprehensive land use classification system are described, and a map of land use for the conterminous United States is presented to reveal what we are doing on the land. The comprehensive, detailed and high-resolution dataset was developed through spatial analysis of nearly two-dozen publicly-available, national spatial datasets--predominantly based on census housing, employment, and infrastructure, as well as land cover from satellite imagery. This effort resulted in 79 land use classes that fit within five main land use groups: built-up, production, recreation, conservation, and water. Key findings from this study are that built-up areas occupy 13.6% of mainland US, but that the majority of this occurs as low-density exurban/rural residential (9.1% of the US), while more intensive built-up land uses occupy 4.5%. For every acre of urban and suburban residential land, there are 0.13 commercial, 0.07 industrial, 0.48 institutional, and 0.29 acres of interstates/highways. This database can be used to address a variety of natural resource applications, and I provide three examples here: an entropy index of the diversity of land uses for smart-growth planning, a power-law scaling of metropolitan area population to developed footprint, and identifying potential conflict areas by delineating the urban interface.

Landscape connectivity is crucial for many ecological processes, including dispersal, gene flow, demographic rescue, and movement in response to climate change. As a result, governmental and non-governmental organizations are focusing efforts to map and conserve areas that facilitate movement to maintain population connectivity and promote climate adaptation. In contrast, little focus has been placed on identifying barriers-landscape features which impede movement between ecologically important areas-where restoration could most improve connectivity. Yet knowing where barriers most strongly reduce connectivity can complement traditional analyses aimed at mapping best movement routes. We introduce a novel method to detect important barriers and provide example applications. Our method uses GIS neighborhood analyses in conjunction with effective distance analyses to detect barriers that, if removed, would significantly improve connectivity. Applicable in least-cost, circuit-theoretic, and simulation modeling frameworks, the method detects both complete (impermeable) barriers and those that impede but do not completely block movement. Barrier mapping complements corridor mapping by broadening the range of connectivity conservation alternatives available to practitioners. The method can help practitioners move beyond maintaining currently important areas to restoring and enhancing connectivity through active barrier removal. It can inform decisions on trade-offs between restoration and protection; for example, purchasing an intact corridor may be substantially more costly than restoring a barrier that blocks an alternative corridor. And it extends the concept of centrality to barriers, highlighting areas that most diminish connectivity across broad networks. Identifying which modeled barriers have the greatest impact can also help prioritize error checking of land cover data and collection of field data to improve connectivity maps. Barrier detection provides a different way to view the landscape, broadening thinking about connectivity and fragmentation while increasing conservation options.

Abstract Invasion of grasslands by woody plants has been identified as a key indicator of changes in ecosystem structure and function in arid and semi-arid rangelands throughout the world. We investigated changes in the balance between woody and herbaceous components of a semi-arid landscape in western Colorado (USA) using historical aerial photography. Aerial photographs from 1937, 1965–67, and 1994 were sampled at matched locations within overlapping photographs. We modeled change in spatial pattern and heterogeneity across the entire landscape and found a small, net decrease in woody canopy cover; however means disguised normal distributions of change that demonstrated offsetting increases and decreases. We described a region of widespread canopy decline within piñon-juniper forests between 2300 and 2600 m (7500–8500 feet) and a region of predominant increase at lower elevations, between 1800 and 2250 m (5900–7400 feet). It remains unclear whether this shift was driven by climate or by human-caused or natural disturbance. Mean conifer cover decreased within coniferous forests, which counteracted a trend of increased conifer cover in mixed forests, savanna-like woodlands, and the shrub steppe. Disturbance had a significant interaction with cover change in several communities, including forests, savanna and shrublands. Anthropogenic disturbances counteracted successional trends toward canopy closure more than wildfires, but this did not entirely explain observed canopy decline. The natural dynamics in this region also caused diverse changes rather than a simple progression towards increased forest cover. Importantly, temporal change in vegetation varied spatially across the landscape illustrating the importance of landscape level, spatially explicit analyses in characterizing temporal dynamics. [ABSTRACT FROM AUTHOR]