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Environmental impact assessment (EIA) processes are commonly used by government agencies to evaluate the merits and environmental risks of natural resource management decisions. Citing EIA as red tape, decision makers from across the political spectrum are increasingly circumventing EIA to expedite implementation of necessary actions for climate resilience and clean energy. Few studies have quantified the extent that EIA is the main barrier to efficient implementation. We combine administrative data from the US Forest Service with survival analysis to show that, for most actions, the Forest Service takes as long or longer to award first contracts and roll out initial activities than to comply with the 1970 National Environmental Policy Act (NEPA), and that NEPA compliance accounts for approximately one-fifth of planned implementation time.

 

Conserving species' ability to traverse the landscape is vital for maintaining biodiversity in the face of global change. Connectivity conservation requires identifying important pathways for species' movements and aligning societal support for conservation of those pathways. Contemporary connectivity analyses emphasize the impacts of topography, vegetation and human footprint on species' movements; but largely ignore the role that attitudes, economics and institutions play in practitioners' ability to conserve those movements.

We introduce implementation resistance as an analogue of biophysical resistance that combines social, economic and institutional factors that promote or impede connectivity conservation. We demonstrate the utility of integrating implementation resistance as a means of choosing between competing connectivity conservation strategies using wolves in Colorado (USA) as a case study.

Our analysis of five potential corridor locations based on biophysical costs revealed substantial differences in the social costs associated with implementing each corridor despite relatively minimal differences in the biophysical costs.

Our comparison of hypothetical interventions to reduce implementation resistance illustrates that interventions that reduce conflicts between land use and wolves may substantially reduce overall resistance, those reductions are not as well aligned with connectivity priorities as those resulting from changes in land management agency policy.

Our results highlight the need to design conservation interventions that fit both the social and ecological landscape and provide a framework for developing robust, interdisciplinary methods that facilitate implementable connectivity conservation.

Read the freePlain Language Summaryfor this article on the Journal blog.

 

Assessment of socio-environmental problems and the search for solutions often require intersecting geospatial data on environmental factors and human population densities. In the United States, Census data is the most common source for information on population. However, timely acquisition of such data at sufficient spatial resolution can be problematic, especially in cases where the analysis area spans urban-rural gradients. With this data release, we provide a 30-m resolution population estimate for the contiguous United States. The workflow dasymetrically distributes Census block level population estimates across all non-transportation impervious surfaces within each Census block. The methodology is updatable using the most recent Census data and remote sensing-based observations of impervious surface area. The dataset, known as the U.G.L.I (updatable gridded lightweight impervious) population dataset, compares favorably against other population data sources, and provides a useful balance between resolution and complexity.

 

Abstract Reducing invasive species abundance near the leading edge of invasions is important for maintaining diverse, high-functioning ecosystems, but it can be hard to remove invasives present at low levels within desirable plant communities. Focusing on an invasive annual grass, Bromus tectorum , near the edge of its range in the southern Colorado Plateau, we used an observational study to ask what plant community components were associated with lower levels of B. tectorum , and a manipulative experiment to ask if targeted spring grazing or seeding native competitors were effective for reversing low-level invasion. The observational study found that higher C 3 perennial grass cover and shrub cover were associated with lower B. tectorum abundance, and adult Poa fendleriana and Pascopyrum smithii plants had the fewest B. tectorum individuals within 50 cm. Our manipulative experiment used a randomized, hierarchical design to test the relative effectiveness of seeding native perennial grasses using different spatial planting arrangements, seeding rates, seed enhancements, and targeted spring grazing. Two years after seeding, seeded species establishment was 36% greater in high seed rate than unseeded plots, and high rate plots also had lower B. tectorum cover. One season after targeted spring grazing (a single, 2-week spring-grazing treatment 17 months post-seeding), grazed paddocks displayed trends towards higher seeded species densities and lower B. tectorum biomass in certain seeding treatments, compared to ungrazed paddocks. Results suggest high rate native grass seedings may be effective and short-duration spring grazing should be further evaluated as potential tools for preventing ecosystem conversion along invasion fronts. 

The concept of adaptive capacity has received significant attention within social-ecological and environmental change research. Within both the resilience and vulnerability literatures specifically, adaptive capacity has emerged as a fundamental concept for assessing the ability of social-ecological systems to adapt to environmental change. Although methods and indicators used to evaluate adaptive capacity are broad, the focus of existing scholarship has predominately been at the individual- and household- levels. However, the capacities necessary for humans to adapt to global environmental change are often a function of individual and societal characteristics, as well as cumulative and emergent capacities across communities and jurisdictions. In this paper, we apply a systematic literature review and co-citation analysis to investigate empirical research on adaptive capacity that focus on societal levels beyond the household. Our review demonstrates that assessments of adaptive capacity at higher societal levels are increasing in frequency, yet vary widely in approach, framing, and results; analyses focus on adaptive capacity at many different levels (e.g. community, municipality, global region), geographic locations, and cover multiple types of disturbances and their impacts across sectors. We also found that there are considerable challenges with regard to the ‘fit’ between data collected and analytical methods used in adequately capturing the cross-scale and cross-level determinants of adaptive capacity. Current approaches to assessing adaptive capacity at societal levels beyond the household tend to simply aggregate individual- or household-level data, which we argue oversimplifies and ignores the inherent interactions within and across societal levels of decision-making that shape the capacity of humans to adapt to environmental change across multiple scales. In order for future adaptive capacity research to be more practice-oriented and effectively guide policy, there is a need to develop indicators and assessments that are matched with the levels of potential policy applications.

 

The United States Forest Service promulgated new planning regulations under the National Forest Management Act in 2012 (i.e., the Planning Rule). These new regulations include the first requirements in U.S. public land management history for National Forests to evaluate, protect, and/or restore ecological connectivity as they revise their land management plans. Data and resource limitations make single‐species, functional connectivity analyses for the myriad species that occur within the 78 million ha the Forest Service manages implausible. We describe an approach that relies on freely available data and generic species, virtual species whose profile consists of ecological requirements designed to reflect the needs of a group of real species, to address the new Planning Rule requirements. We present high‐resolution connectivity estimates for 10 different generic species across a 379,000 ha study area centered on the Custer Gallatin National Forest (CGNF) in Montana and South Dakota under two different movement models. We identify locations important for connectivity for multiple species and characterize the role of the CGNF for regional connectivity. Our results informed the Plan Revision process on the CGNF and could be readily exported to other National Forests currently or planning to revise their land management plans under the new Planning Rule.

 

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade‐offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.