Search

Study abroad host families and communities in the Global South frequently provide learning experiences to study abroad programs in search of 'intercultural experiences' and 'global competency' to students from the Global North. This paper shares findings from a multi-sited ethnographic research project exploring cultural and economic impacts on host communities in Thailand who hosted U.S. study abroad programs and students. The study found that rather than participating solely for economic gain, host families participated in the global study abroad economy to preserve local knowledge, learn about cultural others, and leverage this knowledge and affiliations in negotiations with local government over land use and the right of communities remain in place. It also found that creation of systems of distributive benefit (systems that ensured transparency and equal sharing of economic benefits received from hosting students) by local government helped to mitigate unwanted impacts from outside visitors while allowing host communities opportunities to engage with the global study abroad economy.

What is the relationship between Indigenous peoples and violent reactions to contemporary states? This research explores differing, culturally informed notions of attachment to land or place territory. Mechanistic ties and organic ties to land are linked to a key distinction between Indigenous peoples and non-Indigenous peoples. Utilizing the Minorities at Risk (MAR) data set, a subset relationship is explored addressing propensity for Indigenous peoples to rebel against state encroachment of their lands. The results of this research must be considered with the serious limitations of MAR in mind. Within the marginalized groups in the Americas, 28 have an attachment to a place territory. Of these 28 groups, 22 are Indigenous and of the 22 groups, 13 have exhibited some form of rebellious behavior between 1945 and 2003. The power of attachment to place territory, specifically the organic attachment most often displayed by Indigenous peoples of the Americas, is a strong tie surviving 500 years of European encroachment. The findings are indicative of an attachment that Indigenous peoples retain to their specific homelands. The findings suggest a plethora of future research questions. (Contains 8 tables, 3 figures, and 41 notes.)

While students may acknowledge the impact that land use and development have on our environment, they do not necessarily understand the relationship between human activities and ecosystem responses. Therefore, the nature of the relationships leaves the science teacher to most often present information in a purely narrative form without any hands-on or experimental experience. In this article, the authors introduce a free, simple, and realistic computer simulation program, SimRiver, which allows students to develop a river basin and identify how human activity affects producers, specifically diatoms. This allows students to develop a skill set for understanding nonlinear problems where relationships are not simply cause and effect. (Contains 6 figures.)

On August 1st, 2007, Indigenous nations from within the United States, Canada, Australia, and Aotearoa (New Zealand) signed a treaty to found the United League of Indigenous Nations. The Treaty of Indigenous Nations offers a historic opportunity for sovereign Indigenous governments to build intertribal cooperation outside the framework of the colonial settler states. Just as the Pacific Rim states have cooperated to limit Native sovereign rights and build polluting industries, Indigenous nations can cooperate to decolonize ancestral territories and protect their common natural resources for future generations. The treaty process has involved Indigenous political alliances such as the National Congress of American Indians (NCAI), the Assembly of First Nations (AFN) in Canada, and the Mataatua Assembly (including forty-four Maori tribes) in Aotearoa. The treaty identifies four main areas of cooperation: increasing trade among Indigenous nations, protecting cultural properties, easing border crossings, and responding to the urgent threat of climate change. The Treaty of Indigenous Nations builds a sense of community by including other tribal nations in the community, even those who live on the other side of imposed colonial borders or on the other side of the ocean. Indigenous peoples have survived the effects of colonialism and environmental destruction only by cooperating with each other. It is no longer just a good idea to build these relationships; climate change makes them much more urgent. This article explores some of the relationships being built, or that have the potential to be built, among Indigenous nations, local governments, national governments, and international agencies. (Contains 3 figures and 69 notes.)

This paper examines the relationship between various quantitative measures of urban centralization and urban housing prices through the use of a 2000 data set from the 452 Census designated urbanized areas in the United States. An empirical study of this type is necessary because: (1) the theoretical influence of creating more centralized urban areas--or what many would consider less "sprawl"--on what people pay for housing is indeterminate, (2) now popular "Smart Growth" policies advocate more centralized urban areas, and (3) some have argued that a cost of this centralization is an increase in the price of homes. After controlling for differences across United States urbanized areas in residents' economic status and demographics, number and type of households, climate, household growth, nonresidential land uses, and the structural characteristics of houses, we find that a more centralized area exhibits a lower median home value and percentage of homes in an upper-end price category. Therefore, we offer no evidence to support the contention that a successful effort to further centralize an urban area raises the price of homes in that urban area.

The global push for renewable energy must overcome the local challenge of convincing neighboring landowners to lease their properties for wind power. Is this challenge more or less pronounced in rural landscapes with small landholdings? Our theoretical model combines ideas from literatures on the commons, anticommons, and spatial externalities to explain conditions when small landholdings could promote or inhibit voluntary leasing. Empirically, we estimate the effects of landholding size and landscape fragmentation on wind farm uptake across rural areas of the United States over the past 20 years. Evidence from three spatial levels of analysis (counties, square‐mile sections, and individual parcels) indicates that areas with more landowners have less installed wind capacity after controlling for windiness, access to transmission lines, and other relevant factors that vary across and within counties. The findings imply that fragmented ownership, which is an overlooked factor in studies of the feasibility of decarbonization, will pose an impediment to future wind expansion on private land as remaining areas without wind development become disproportionately fragmented. [ABSTRACT FROM AUTHOR]

Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per‐capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm‐season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios. Key Points: Consistent, reproducible estimates of monthly water withdrawals were generated at the spatial resolution of USA water service areasSpatial and temporal variability of public supply withdrawal is driven by a complex array of explanatory featuresAn operational machine learning framework was developed to estimate water withdrawals, prediction uncertainty, and feature importance [ABSTRACT FROM AUTHOR]

Native ecosystem and biodiversity loss from land use conversion into human‐modified landscapes are evident in the United States and globally. In addition to public land conservation, there is an increase in private land conservation through conservation easements (CEs) across exurban landscapes. Not every CE was established strictly for biodiversity protection and permitted land uses can increase human modification. No research of which we are aware has examined the actual tax assessor's land use designations (LUDs) through time. We constructed granular CE datasets (GCED) of CEs and their parcels' tax assessment LUDs for 1997–2008/2009, based on original data from 12 counties in six US states. Using the GCED, we examined patterns in the LUDs, with implications for land uses that could impact CE biological outcomes. We show that LUDs on exurban private conservation lands were predominately residential and agricultural, with increased residential over time. Critically, the LUDs lack a biological conservation exempt designation/category. There is no consistent trend in association between the primary CE reason and its parcel's LUD, suggesting that they coincide in some circumstances but in others, the CE may be a response to contravene the LUD. The majority of the first CE reasons are focused on open space preservation, except in some counties where agricultural land uses and agricultural CEs are associated. The economically and human‐focused LUD is one of many social factors that should be considered in a classification system for private land conservation and CEs more specifically. These results prompt the land conservation, conservation biology, and environmental planning communities to explore assessed land uses' impact on biodiversity conservation objectives. [ABSTRACT FROM AUTHOR]

Aim: Species distribution models (SDMs) are increasingly applied across macroscales using detection‐nondetection data. These models typically assume that a single set of regression coefficients can adequately describe species–environment relationships and/or population trends. However, such relationships often show nonlinear and/or spatially varying patterns that arise from complex interactions with abiotic and biotic processes that operate at different scales. Spatially varying coefficient (SVC) models can readily account for variability in the effects of environmental covariates. Yet, their use in ecology is relatively scarce due to gaps in understanding the inferential benefits that SVC models can provide compared to simpler frameworks. Innovation: Here we demonstrate the inferential benefits of SVC SDMs, with a particular focus on how this approach can be used to generate and test ecological hypotheses regarding the drivers of spatial variability in population trends and species–environment relationships. We illustrate the inferential benefits of SVC SDMs with simulations and two case studies: one that assesses spatially varying trends of 51 forest bird species in the eastern United States over two decades and a second that evaluates spatial variability in the effects of five decades of land cover change on grasshopper sparrow (Ammodramus savannarum) occurrence across the continental United States. Main conclusions: We found strong support for SVC SDMs compared to simpler alternatives in both empirical case studies. Factors operating at fine spatial scales, accounted for by the SVCs, were the primary divers of spatial variability in forest bird occurrence trends. Additionally, SVCs revealed complex species–habitat relationships with grassland and cropland area for grasshopper sparrow, providing nuanced insights into how future land use change may shape its distribution. These applications display the utility of SVC SDMs to help reveal the environmental factors that drive species distributions across both local and broad scales. We conclude by discussing the potential applications of SVC SDMs in ecology and conservation. [ABSTRACT FROM AUTHOR]

Background: Two major factors that determine the efficiency of programs designed to mitigate greenhouse gases by encouraging voluntary changes in U.S. agricultural land management are the effect of land use changes on producers' profitability and the net sequestration those changes create. In this work, we investigate how the interaction of these factors produces spatial heterogeneity in the cost-efficiency of voluntary programs incentivizing tillage reduction and cover-cropping practices. We map county-level predicted rates of adoption for each practice with the greenhouse gas mitigation or carbon sequestration benefits expected from their use. Then, we use these bivariate maps to describe how the cost efficiency of agricultural mitigation efforts is likely to vary spatially in the United States. Results: Our results suggest the combination of high adoption rates and large reductions in net emissions make reduced tillage programs most cost efficient in the Chesapeake Bay watershed or the Upper Mississippi and Lower Missouri sub-basins of the Mississippi River. For programs aiming to reduce net emissions by incentivizing cover-cropping, we expect cost-efficiency to be greatest in the areas near the main stem of the Mississippi River within its Middle and Lower sections. Conclusions: Many voluntary agricultural conservation programs offer the same incentives across the United States. Yet spatial variation in profitability and efficacy of conservation practices suggest that these uniform approaches are not cost-effective. Spatial targeting of voluntary agricultural conservation programs has the potential to increase the cost-efficiency of these programs due to regional heterogeneity in the profitability and greenhouse gas mitigation benefits of agricultural land management practices across the continental United States. We illustrate how predicted rates of adoption and greenhouse gas sequestration might be used to target regions where efforts to incentivize cover-cropping and reductions in tillage are most likely to be cost -effective. [ABSTRACT FROM AUTHOR]

Land use intensification has led to conspicuous changes in plant and animal communities across the world. Shifts in trait‐based functional composition have recently been hypothesized to manifest at lower levels of environmental change when compared to species‐based taxonomic composition; however, little is known about the commonalities in these responses across taxonomic groups and geographic regions. We investigated this hypothesis by testing for taxonomic and geographic similarities in the composition of riverine fish and insect communities across gradients of land use in major hydrological regions of the conterminous United States. We analyzed an extensive data set representing 556 species and 33 functional trait modalities from 8023 fish communities and 1434 taxa and 50 trait modalities from 5197 aquatic insect communities. Our results demonstrate abrupt threshold changes in both taxonomic and functional community composition due to land use conversion. Functional composition consistently demonstrated lower land use threshold responses compared to taxonomic composition for both fish (urban p = 0.069; agriculture p = 0.029) and insect (urban p = 0.095; agriculture p = 0.043) communities according to gradient forest models. We found significantly lower thresholds for urban versus agricultural land use for fishes (taxonomic and functional p < 0.001) and insects (taxonomic p = 0.001; functional p = 0.033). We further revealed that threshold responses in functional composition were more geographically consistent than for taxonomic composition to both urban and agricultural land use change. Traits contributing the most to overall functional composition change differed along urban and agricultural land gradients and conformed to predicted ecological mechanisms underpinning community change. This study points to reliable early‐warning thresholds that accurately forecast compositional shifts in riverine communities to land use conversion, and highlight the importance of considering trait‐based indicators of community change to inform large‐scale land use management strategies and policies. [ABSTRACT FROM AUTHOR]

Earth system models (ESMs) are progressively advancing towards the kilometer scale (k-scale). However, the surface parameters for Land Surface Models (LSMs) within ESMs running at the k11 scale are typically derived from coarse resolution and outdated datasets. This study aims to develop a new set of global land surface parameters with a resolution of 1 km for multiple years from 2001 to 2020, utilizing the latest and most accurate available datasets. Specifically, the datasets consist of parameters related to land use and land cover, vegetation, soil, and topography. To demonstrate the capability of these new parameters, we conducted 1 km resolution simulations using the E3SM Land Model version 2 (ELM2) over the contiguous United States. Our results demonstrate that land surface parameters contribute to significant spatial heterogeneity in ELM2 simulations of soil moisture, latent heat, emitted longwave radiation, and absorbed shortwave radiation. On average, about 31% to 54% of spatial information is lost by upscaling the 1 km ELM2 simulations to a 12 km resolution. Using eXplainable Machine Learning (XML) methods, the influential factors driving the spatial variability and spatial information loss of ELM2 simulations were identified, highlighting the substantial impact of the spatial variability and information loss of various land surface parameters, as well as the mean climate conditions. The new land surface parameters are tailored to meet the emerging needs of k-scale LSMs and ESMs modeling with significant implications for advancing our understanding of water, carbon, and energy cycles under global change. [ABSTRACT FROM AUTHOR]

Current residential land use in the United States has been disastrous for the environment. Land use is largely regulated by local zoning laws, and in many states, property taxes are set at a local level as well. The relationship between the two is complex, but put simply, having both policy tools in the hands of local governments creates problematic incentives. Jurisdictions often use land use laws to protect their tax base, and one way to do this is to engage in exclusionary zoning. Exclusionary zoning codes prioritize large single-family homes, which leads to suburban sprawl. Sprawl, in turn, has negative environmental consequences by increasing reliance on cars, requiring extra heating and cooling services for single-family homes, and other harmful externalities. Additionally, lower-income people of color bear the brunt of these harmful effects due to both historic and current transportation policies. However, property tax reform would reduce incentives for communities to engage in exclusionary zoning by making it less lucrative to exclude apartments. Thus, the reform proposed in this Note is to set property tax rates at the statewide level rather than at the local level in order to shift incentives that impact zoning. Although there are potential political and social drawbacks that make change challenging, property tax reform is a promising means to both ease and prevent sprawl. Property tax reform would thus eliminate one of the root causes of environmental harms: the fact that the current tax code and local government structure incentivize bad land use decisions. [ABSTRACT FROM AUTHOR]

The biodiversity of stream fishes is critically threatened globally, and a major factor leading to the loss of biodiversity is anthropogenic land use in stream catchments, which act as stressors to stream fishes. Declines in the biodiversity of stream fish are often identified by a loss of species or fewer individuals comprising assemblages, but biological degradation can also occur with increases in non-native species and/or the spread of fish tolerant to anthropogenic land use, suggesting the importance of accounting for the distinctness of assemblages along with richness and diversity to best characterize the response of stream fish assemblages to anthropogenic landscape stressors. We summarized stream fish assemblages from 10,522 locations through multiple biodiversity indices and then quantified index responsiveness to natural landscape variables and anthropogenic land use in stream network catchments across five freshwater ecoregions in the temperate mesic portion of the United States. Indices included species richness, Shannon's diversity, Pielou's evenness, beta diversity, taxonomic diversity, and taxonomic distinctness. First, we tested for correlations among indices across freshwater ecoregions and found that while species richness and Shannon's diversity were always highly correlated, taxonomic distinctiveness was not highly correlated with other biodiversity indices measured except taxonomic diversity. Then, we used multiple linear regression to predict biodiversity indices in each of the five freshwater ecoregions to identify significant landscape variables from natural landscape and anthropogenic land uses. Most indices were consistently predicted by catchment area, and many were predicted by elevation, except for beta diversity, emphasizing the importance of these natural landscape variables on biodiversity. In contrast, taxonomic distinctness was often predicted by the amount of urban land use in the catchment, but the direction of the relationship varied. The proportion of agriculture land use in the network catchment was a more consistent predictor of species richness, beta diversity, and Shannon's diversity. Our analyses show that taxonomic distinctness in freshwater fishes characterize a unique element of biodiversity in relationships with anthropogenic land uses in a streams network catchment. Taxonomic distinctness may also be an effective metric for the bioassessment of stream fishes along with richness and diversity indices to help preserve biodiversity in regard to current and future anthropogenic land uses. [ABSTRACT FROM AUTHOR]

The article discusses environmental justice and the special use permit applications of fossil fuel industries in the U.S. Topics explored include the links between land use planning, municipal zoning, and environmental justice, the special use permit review and approval process being conducted by a local zoning board, and two case studies in rural Virginia which involve fracked gas infrastructure expansion in Appalachia.

The land of the conterminous United States (CONUS) has been transformed dramatically by humans over the last four centuries through land clearing, agricultural expansion and intensification, and urban sprawl. High-resolution geospatial data on long-term historical changes in land use and land cover (LULC) across the CONUS are essential for predictive understanding of natural–human interactions and land-based climate solutions for the United States. A few efforts have reconstructed historical changes in cropland and urban extent in the United States since the mid-19th century. However, the long-term trajectories of multiple LULC types with high spatial and temporal resolutions since the colonial era (early 17th century) in the United States are not available yet. By integrating multi-source data, such as high-resolution remote sensing image-based LULC data, model-based LULC products, and historical census data, we reconstructed the history of land use and land cover for the conterminous United States (HISLAND-US) at an annual timescale and 1 km × 1 km spatial resolution in the past 390 years (1630–2020). The results show widespread expansion of cropland and urban land associated with rapid loss of natural vegetation. Croplands are mainly converted from forest, shrub, and grassland, especially in the Great Plains and North Central regions. Forest planting and regeneration accelerated the forest recovery in the Northeast and Southeast since the 1920s. The geospatial and long-term historical LULC data from this study provide critical information for assessing the LULC impacts on regional climate, hydrology, and biogeochemical cycles as well as achieving sustainable use of land in the nation. The datasets are available at 10.5281/zenodo.7055086 (Li et al., 2022). [ABSTRACT FROM AUTHOR]

The scale and pace of energy infrastructure development required to achieve netzero greenhouse gas (GHG) emissions are unprecedented, yet our understanding of how to minimize its potential impacts on land and ocean use and natural resources is inadequate. Using high-resolution energy and land-use modeling, we developed spatially explicit scenarios for reaching an economy-wide net-zero GHG target in the western United States by 2050. We found that among net-zero policy cases that vary the rate of transportation and building electrification and use of fossil fuels, nuclear generation, and biomass, the "High Electrification" case, which utilizes electricity generation the most efficiently, had the lowest total land and ocean area requirements (84,000 to 105,000 km² vs. 88,100 to 158,000 km² across all other cases). Different levels of land and ocean use protections were applied to determine their effect on siting, environmental and social impacts, and energy costs. Meeting the net-zero target with stronger land and ocean use protections did not significantly alter the share of different energy generation technologies and only increased system costs by 3%, but decreased additional interstate transmission capacity by 20%. Yet, failure to avoid development in areas with high conservation value is likely to result in substantial habitat loss. [ABSTRACT FROM AUTHOR]

Floods are one of the most dangerous water-related risks. Numerous sources of uncertainty affect flood modeling. High-resolution land-cover maps along with appropriate Manning's roughness values are the most significant parameters for building an accurate 2D flood model. Two land-cover datasets are available: the National Land Cover Database (NLCD 2019) and the Land Use/Land Cover for Environmental Systems Research Institute (LULC 2020-ESRI). The NLCD 2019 dataset has national coverage but includes references to Manning's roughness values for each class obtained from earlier studies, in contrast to the LULC 2020-ESRI dataset, which has global coverage but without an identified reference to Manning's roughness values yet. The main objectives of this study are to assess the accuracy of using the LULC 2020-ESRI dataset compared with the NLCD 2019 dataset and propose a standard reference to Manning's roughness values for the classes in the LULC 2020-ESRI dataset. To achieve the research objectives, a confusion matrix using 548,117 test points in the conterminous United States was prepared to assess the accuracy by quantifying the cross-correspondence between the two datasets. Then statistical analyses were applied to the global maps to detect the appropriate Manning's roughness values associated with the LULC 2020-ESRI map. Compared to the NLCD 2019 dataset, the proposed Manning's roughness values for the LULC 2020-ESRI dataset were calibrated and validated using 2D flood modeling software (HEC-RAS V6.2) on nine randomly chosen catchments in the conterminous United States. This research's main results show that the LULC 2020-ESRI dataset achieves an overall accuracy of 72% compared to the NLCD 2019 dataset. The findings demonstrate that, when determining the appropriate Manning's roughness values for the LULC 2020-ESRI dataset, the weighted average technique performs better than the average method. The calibration and validation results of the proposed Manning's roughness values show that the overall Root Mean Square Error (RMSE) in depth was 2.7 cm, and the Mean Absolute Error (MAE) in depth was 5.32 cm. The accuracy of the computed peak flow value using LULC 2020-ESRI was with an average error of 5.22% (2.0% min. to 8.8% max.) compared to the computed peak flow values using the NLCD 2019 dataset. Finally, a reference to Manning's roughness values for the LULC 2020-ESRI dataset was developed to help use the globally available land-use/land-cover dataset to build 2D flood models with an acceptable accuracy worldwide. [ABSTRACT FROM AUTHOR]

Land use change analysis provides valuable information for landscape monitoring, managing, and prioritizing large area conservation practices. There has been significant interest in the southeastern United States (SEUS) due to substantial land change from various economic activities since the 1940s. This study uses quantitative data from the Economic Research Service (ERS) for landscape change analysis, addressing land change among five major land types for twelve states in the SEUS from 1945 to 2012. The study also conducted a literature review using the PSALSAR framework to identify significant drivers related to land type changes from research articles within the region. The analysis showed how each land type changed over the period for each state in the time period and the percentage change for the primary drivers related to land use change. The literature review identified significant drivers of land use and land cover change (LULCC) within the SEUS. The associated drivers were categorized into natural and artificial drivers, then further subdivided into eight categories related to land type changes in the region. A schematic diagram was developed to show land type changes that impacted environmental changes from various studies in the SEUS. The results concluded that Forest land accounted for 12% change and agricultural land for 20%; population growth in the region is an average of 2.59% annually. It also concluded that the need for research to understand past land use trends, direction and magnitude of land cover changes is essential. Significant drivers such as urban expansion and agriculture are critical to the impending use of land in the region; their impacts are attributed to environmental changes in the region and must be monitored. [ABSTRACT FROM AUTHOR]

The composition of land use/land cover (LULC) in coastal watersheds has many implications for estuarine system ecological function. Land use/land cover can influence allochthonous inputs and can enhance or degrade the physical characteristics of estuaries, which in turn affects estuaries' ability to support local biota. However, these implications for estuaries are often poorly considered when assessing the value of lands for conservation. The focus of research regarding terrestrial and estuarine interfaces often evaluates how LULC may stress estuarine ecosystems, but in this study we sought to understand how LULC may both positively and negatively affect estuaries using measures of observed biotic richness as proxies for estuarine function. We investigated the influence of LULC on estuarine biotic richness with Bayesian hierarchical models using multiple geospatial data sets from 33 estuaries and their associated watersheds along the Gulf of Mexico coastal region of the United States. We designed the hierarchical models with observed species richness of three functional groups (FGs) (i.e., pelagic fishes, forage fishes, and shrimp) from fishery‐independent trawl surveys as response variables. We then set salinity and water temperature as trawl‐specific covariates and measures of influence from six LULC classes as estuary‐specific covariates and allowed the models to vary by estuary, trawl program, salinity, and temperature. The model results indicated that the observed richness of each FG was both positively and negatively associated with different LULC classes, with estuarine wetlands and forested lands demonstrating the strongest positive influences on each FG. The results are generally consistent with past studies, and the modeling framework provides a promising way to systematically quantify LULC linkages with the biotic health of estuaries for the purposes of potentially valuing the estuarine implications of land conservation. [ABSTRACT FROM AUTHOR]

Atmospheric deposition of nitrogen (N) and sulfur (S) compounds from human activity has greatly declined in the United States (US) over the past several decades in response to emission controls set by the Clean Air Act. While many observational studies have investigated spatial and temporal trends of atmospheric deposition, modeling assessments can provide useful information over areas with sparse measurements, although they usually have larger horizontal resolutions and are limited by input data availability. In this analysis, we evaluate wet, dry, and total N and S deposition from multiyear simulations within the contiguous US (CONUS). Community Multiscale Air Quality (CMAQ) model estimates from the EPA's (Environmental Protection Agency) Air QUAlity TimE Series (EQUATES) project contain important model updates to atmospheric deposition algorithms compared to previous model data, including the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model which contains land-use-specific resistance parameterization and land-use-specific deposition estimates needed to estimate the differential impacts of N deposition to different land use types. First, we evaluate model estimates of wet deposition and ambient concentrations, finding underestimates of SO 4 , NO 3 , and NH 4 wet deposition compared to National Atmospheric Deposition Program observations and underestimates of NH 4 and SO 4 and overestimates of SO 2 and TNO 3 (HNO 3+ NO 3) compared to the Clean Air Status and Trends Network (CASTNET) ambient concentrations. Second, a measurement–model fusion approach employing a precipitation and bias correction to wet-deposition estimates is found to reduce model bias and improve correlations compared to the unadjusted model values. Model agreement of wet deposition is poor over parts of the West and Northern Rockies, due to errors in precipitation estimates caused by complex terrain and uncertainty in emissions at the relatively coarse 12 km grid resolution used in this study. Next, we assess modeled N and S deposition trends across climatologically consistent regions in the CONUS. Total deposition of N and S in the eastern US is larger than the western US with a steeper decreasing trend from 2002–2017; i.e., total N declined at a rate of approximately -0.30 kg N ha -1 yr -1 in the Northeast and Southeast and by -0.02 kg N ha -1 yr -1 in the Northwest and Southwest. Widespread increases in reduced N deposition across the Upper Midwest, Northern Rockies, and West indicate evolving atmospheric composition due to increased precipitation amounts over some areas, growing agricultural emissions, and regional NOx/SOx emission reductions shifting gas–aerosol partitioning; these increases in reduced N deposition are generally masked by the larger decreasing oxidized N trend. We find larger average declining trends of total N and S deposition between 2002–2009 than 2010–2017, suggesting a slowdown of the rate of decline likely in response to smaller emission reductions. Finally, we document changes in the modeled total N and S deposition budgets. The average annual total N deposition budget over the CONUS decreases from 7.8 in 2002 to 6.3 kg N ha -1 yr -1 in 2017 due to declines in oxidized N deposition from NO x emission controls. Across the CONUS during the 2002–2017 time period, the average contribution of dry deposition to the total N deposition budget drops from 60 % to 52 %, whereas wet deposition dominates the S budget rising from 45 % to 68 %. Our analysis extends upon the literature documenting the growing contribution of reduced N to the total deposition budget, particularly in the Upper Midwest and Northern Rockies, and documents a slowdown of the declining oxidized N deposition trend, which may have consequences on vegetation diversity and productivity. [ABSTRACT FROM AUTHOR]

Multiple aspects of our society are reflected in how we have transformed land through time. However, limited availability of historical-spatial data at fine granularity have hindered our ability to advance our understanding of the ways in which land was developed over the long-term. Using a proprietary, national housing and property database, which is a result of large-scale, industry-fuelled data harmonization efforts, we created publicly available sequences of gridded surfaces that describe built land use progression in the conterminous United States at fine spatial (i.e., 250 m × 250 m) and temporal resolution (i.e., 1 year - 5 years) between the years 1940 and 2015. There are six land use classes represented in the data product: agricultural, commercial, industrial, residential-owned, residential-income, and recreational facilities, as well as complimentary uncertainty layers informing the users about quantifiable components of data uncertainty. The datasets are part of the Historical Settlement Data Compilation for the U.S. (HISDAC-US) and enable the creation of new knowledge of long-term land use dynamics, opening novel avenues of inquiry across multiple fields of study. Measurement(s) Structural Land Use Technology Type(s) Python Sample Characteristic - Organism Structures Sample Characteristic - Environment Built Environment Sample Characteristic - Location United States [ABSTRACT FROM AUTHOR]

Managing ecological systems for resilience can increase their capacity to maintain key functions even under global change. Oxygenated coldwater (oxythermal) habitat in lakes is an important ecological resource that is threatened by both climate change and eutrophication. Here, we quantify the resilience of oxythermal habitat in over 10,000 glacial lakes in the upper Midwestern United States to climate change and watershed disturbance and classify lakes for conservation prioritization based on their current conditions and resilience. Oxythermal habitat was predicted by lake morphometry, July air temperatures, and watershed land use. Temperatures are projected to increase by mid‐century, and the magnitude of warming, its effect on oxythermal habitat, and the uncertainty surrounding that effect varied among lakes. Under mid‐century climate conditions, the number of lakes containing suitable coldwater habitat was predicted to decline by 67%, while the number of lakes with unsuitable habitat was predicted to increase by over 200%. Lakes varied in the amount of temperature increase that they could sustain without a resultant change in habitat tier (i.e., their climate resilience). Median climate resilience was 4.3°C, with some lakes capable of remaining in their habitat tier even with temperature increases up to 14°C. Changing watershed land use was predicted to influence oxythermal habitat in 24% of lakes (n = 2391). We used the magnitude of increase in watershed development that a lake could sustain while remaining in its current habitat class as a measure of its resilience to watershed disturbance. Conversely, decreased watershed development may improve oxythermal habitat conditions and push a lake into an improved condition, and this value represented a lake's restoration potential. We classified lakes into seven management classes based on their current oxythermal habitat conditions and the resilience of oxythermal habitat to climate and watershed disturbance. To facilitate management on individual lakes, we also assessed the vulnerability and resilience of individual lakes and the uncertainty surrounding these estimates. By quantifying the resilience of lakes and how it is influenced by local action across a multistate region, we can prioritize conservation action across multiple scales to maintain the critical habitat and ecosystem function of glacial lakes. [ABSTRACT FROM AUTHOR]

Determining the genetic consequences of both historical and contemporary events can clarify the effects of the environment on population connectivity and inform conservation decisions. Historical events (like glaciations) and contemporary factors (like logging) can disrupt gene flow between populations. This is especially true among species with specialized ecological requirements and low dispersal ability, like amphibians. We test for the genetic consequences of historical and contemporary disturbances in the coastal giant salamander (Dicamptodon tenebrosus) in the Pacific Northwest of the United States. We consider predictions based on the contemporary landscape (habitat connectivity, logging, forest fires, and topography), in addition to relatively ancient post-Pleistocene range expansion (following the last glacial retreat). To assess local versus larger-scale effects, we sampled 318 individuals across 23 sites, which were clustered in five sampling regions. Genetic variation was assessed using five microsatellite markers. We found evidence of (i) historical regional isolation, with decreased genetic diversity among more recently colonized northern sites, as well as (ii) high levels of inbreeding and loss of heterozygosity at local scales, despite relatively low overall population differentiation (FST) or strong evidence for population bottlenecks. Genetic diversity was not associated with contemporary disturbances (logging or fire), and there were no detectable effects on the genetic connectivity of populations based on intervening landscape features (habitat fragmentation and topography). However, lower genetic diversity in more northern regions indicates a lag in recovery of genetic diversity following post-Pleistocene expansion. Additionally, some populations had evidence of having undergone a recent genetic bottleneck or had high inbreeding (FIS) values. Lower genetic diversity in more northern sites means populations may be more vulnerable to future environmental changes, and managing for connectivity alone may not be sufficient given low mobility. Recent apparent reductions in some populations were not clearly linked to anthropogenic disturbances we examined. This suggests the type of disturbances this species is sensitive to may not be well understood. [ABSTRACT FROM AUTHOR]

This paper describes GCAM-USA v5.3_water_dispatch, an open-source model that represents key interactions across economic, energy, water, and land systems in a consistent global framework with subnational detail in the United States. GCAM-USA divides the world into 31 geopolitical regions outside the United States (US) and represents the US economy and energy systems in 51 state-level regions (50 states plus the District of Columbia). The model also includes 235 water basins and 384 land use regions, and 23 of each fall at least partially within the United States. GCAM-USA offers a level of process and temporal resolution rare for models of its class and scope, including detailed subnational representation of US water demands and supplies and sub-annual operations (day and night for each month) in the US electric power sector. GCAM-USA can be used to explore how changes in socioeconomic drivers, technological progress, or policy impact demands for (and production of) energy, water, and crops at a subnational level in the United States while maintaining consistency with broader national and international conditions. This paper describes GCAM-USA's structure, inputs, and outputs, with emphasis on new model features. Four illustrative scenarios encompassing varying socioeconomic and energy system futures are used to explore subnational changes in energy, water, and land use outcomes. We conclude with information about how public users can access the model. [ABSTRACT FROM AUTHOR]

Historically, grasslands with limited tree presence were embedded in a matrix of predominantly open oak and pine forests in the eastern United States. These open ecosystems mostly have been lost to other land uses, particularly agriculture, and also to closed forests under fire exclusion because frequent surface fire prevents tree encroachment. We located the potential extent of eastern fire‐maintained grasslands by applying the random forests and C5.0 classifiers to determine the relationship between mapped areas of historical grasslands and topography and wind speed, which are proxies for surface fire frequency. A generalized ruleset was that fire‐maintained grasslands occurred at roughness values of less than 95, or flatter sites, and wind speeds ≥3.4 m s−1, which created large fire compartments. Potential grasslands covered 27 million ha, or 14% of the 200 million ha of the eastern United States, although these fire‐maintained locations also may have been savannas or open woodlands historically. Currently, potential grassland locations are 40% crops, 25% pasture, 18% forests, and 13% developed land, with about 1.5% each of herbaceous upland vegetation, herbaceous wetlands, and shrublands. According to historical accounts, fire‐maintained grasslands generally transitioned to dense young tree growth within a 20‐year interval after fire exclusion; in Kentucky, the transition transpired during the periods 1790–1810 or 1810–1830, but dates vary with Euro‐American settlement time. Finding the forgotten grasslands of the eastern United States, with this mechanistic approach to estimate fire disturbance, is an important first step for recovering and managing eastern grassland biodiversity. [ABSTRACT FROM AUTHOR]

Copyright of Fire Ecology is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

America is the continent with the largest area of genetically modified crops, the United States being the leading producer. Numerous studies show a panorama of potential exposure from agricultural pesticide use for this types of crops near to cities across a vast region of the United States. For the reasons mentioned above, we have chosen to investigate the following issues in this study: How does the implementation of an indexbased spatial modeling tool effectively rank the proximity of peri-urban crops, and what factors impact its effectiveness across diverse peri-urban agricultural landscapes? To address these questions, the research employs the Crop Proximity Index (CPI) model in various cities across the Midwest region of the United States. Six hundred and seventy cities in the state of Iowa were selected, and their peripheries were analysed using weighted perimeter rings, from 0 to 2000 m. The Crop Proximity Index was used to simulate a model of proximity to crops by considering the spatial quantification occupied by agriculture, forest cover, shrubs, pastures and buffer zones. This index varies from 0 to 1 and serves to rank the cities under study. It was estimated that a Crop Proximity Index equal to or >0.8 is a good approximation to a model with less proximity of crops and that only 62 cities (9%) meet this condition. Some 457 cities (68%) have CPIs equal to or <0.5 due to the large areas of crops and the low peripheral forest levels. The CPI is an index that makes it possible to obtain vital exploratory data in order to focus on future research that would determine how the proximity of agro-industrial crops has possible negative consequences for the environment and human health in greater detail. • A CPI ranking of 670 cities was determined to assess the degree of exposure to agro-industrial activity. • Only 9% of the cities analysed have a CPI >0.8 (lowest proximity model). • Transgenic crops that use pesticides are very close to urban populations. • Many cities have low forest periurban cover means less protection from potential pesticide drift [ABSTRACT FROM AUTHOR]

Understanding resource demands and tradeoffs among energy, water, and land socioeconomic sectors requires an explicit consideration of spatial scale. However, incorporation of land dynamics within the energy-water nexus has been limited due inconsistent spatial units of observation from disparate data sources. Herein we describe the development of a National Water and Energy Land Dataset (NWELD) for the conterminous United States. NWELD is a 30-m, 86-layer rasterized dataset depicting the land use of mappable components of the United States energy sector life cycles (and related water used for energy), specifically the extraction, development, production, storage, distribution, and operation of eight renewable and non-renewable technologies. Through geospatial processing and programming, the final products were assembled using four different methodologies, each depending upon the nature and availability of raw data sources. For validation, NWELD provided a relatively accurate portrayal of the spatial extent of energy life cycles yet displayed low measures of association with mainstream land cover and land use datasets, indicating the provision of new land use information for the energy-water nexus. Measurement(s) land use of renewable and nonrenewable technologies Technology Type(s) Esri Arcmap Sample Characteristic - Environment terrestrial; • aquatic Sample Characteristic - Location United States [ABSTRACT FROM AUTHOR]

To help avoid the most catastrophic effects of climate change, society needs to achieve net-zero greenhouse gas emissions by mid-century. Wind energy provides a clean, renewable source of electricity; however, improperly sited wind facilities pose known threats to wildlife populations and contribute to degradation of natural habitats. To support a rapid transition to low-carbon energy while protecting imperiled species, we identified potential low-impact areas for wind development in a 19-state region of the central U.S. by excluding areas with known wildlife sensitivities. By combining maps of sensitive habitats and species with wind speed and land use information, we demonstrate that there is significant potential to develop wind energy in the region while avoiding significant negative impacts to wildlife. These low-impact areas have the potential to yield between 930 and 1550 GW of name-plate wind capacity. This is equivalent to 8–13 times current U.S. installed wind capacity. Our analysis demonstrates that ambitious low-carbon energy goals are achievable while minimizing risks to wildlife. [ABSTRACT FROM AUTHOR]

Transparent, consistent, and statistically reliable land use/ land cover area estimates are needed to assess land use change and greenhouse gas emissions associated with biofuel production and other land uses that are influenced by policy. As relevant studies have increased rapidly during past decades, the methods used to combine data extracted from land use land cover (LULC) surveys and remote sensing-based products and track or report sources of uncertainty vary notably. This paper reviews six data sources that are most commonly used to investigate LULC and change in the contiguous U.S. by highlighting the main characteristics, strengths and weaknesses and considering how uncertainty is assessed by the June Area Survey (JAS), the Census of Agriculture (COA), the Farm Survey Agency (FSA) acreage, the National Resources Inventory (NRI), the National Wetlands Inventory (NWI), and the Forest Inventory and Analysis (FIA); and two remote sensing-based data products, the Cropland Data Layer (CDL) and the National Land Cover Database (NLCD). The summary and conclusion identify important research gaps or challenges limiting current land use/land cover and change studies (e.g., lack of high-quality reference data and uncertainty quantification, etc.) and opportunities and emerging techniques (data fusion and machine learning) that will improve reliability of land use/land cover assessments and associated policies. Blended approaches that marry high quality ground truth data that are more finely resolved than data supplied by government surveys with multitemporal imagery are needed track use of non-agricultural lands vulnerable to agricultural expansion. These considerations are notably important as the U.S. considers the renewal and possibly revision of its Renewable Fuel Standard, which includes provisions that require monitoring of agricultural land expansion. • Producers and consumers of land use change information rely on key data sources that are being continually updated and improved. • Strengths, weaknesses and data gaps associated with key survey and remote sensing products are reviewed. • Trust in land use and biofuels policies that are reliant on accurate land use allocation will increase with transparency and consistency in methods used. [ABSTRACT FROM AUTHOR]

Background: Quantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Forest inventories, processes-based biogeochemical models, and inversion methods have all been used to estimate the contribution of U.S. forests to the global terrestrial carbon sink. However, estimates have ranged widely, largely based on the approach used, and no single system is appropriate for operational carbon quantification and forecasting. We present estimates obtained using a new spatially explicit modeling framework utilizing a "gain–loss" approach, by linking the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Results: We estimated forest ecosystems in the conterminous United States stored 52.0 Pg C across all pools. Between 2001 and 2020, carbon storage increased by 2.4 Pg C at an annualized rate of 126 Tg C year−1. Our results broadly agree with other studies using a variety of other methods to estimate the forest carbon sink. Climate variability and change was the primary driver of annual variability in the size of the net carbon sink, while land-use and land-cover change and disturbance were the primary drivers of the magnitude, reducing annual sink strength by 39%. Projections of carbon change under climate scenarios for the western U.S. find diverging estimates of carbon balance depending on the scenario. Under a moderate emissions scenario we estimated a 38% increase in the net sink of carbon, while under a high emissions scenario we estimated a reversal from a net sink to net source. Conclusions: The new approach provides a fully coupled modeling framework capable of producing spatially explicit estimates of carbon stocks and fluxes under a range of historical and/or future socioeconomic, climate, and land management futures. [ABSTRACT FROM AUTHOR]

Pollen is a unique vehicle for viral spread. Pollen-associated viruses hitchhike on or within pollen grains and are transported to other plants by pollinators. They are deposited on flowers and have a direct pathway into the plant and next generation via seeds. To discover the diversity of pollen-associated viruses and identify contributing landscape and floral features, we perform a species-level metagenomic survey of pollen from wild, visually asymptomatic plants, located in one of four regions in the United States of America varying in land use. We identify many known and novel pollen-associated viruses, half belonging to the Bromoviridae, Partitiviridae, and Secoviridae viral families, but many families are represented. Across the regions, species harbor more viruses when surrounded by less natural and more human-modified environments than the reverse, but we note that other region-level differences may also covary with this. When examining the novel connection between virus richness and floral traits, we find that species with multiple, bilaterally symmetric flowers and smaller, spikier pollen harbored more viruses than those with opposite traits. The association of viral diversity with floral traits highlights the need to incorporate plant-pollinator interactions as a driver of pollen-associated virus transport into the study of plant-viral interactions. Pollen can be a vehicle for viral spread among plants. Here, Fetters et al. apply viral metagenomics to characterize the pollen virome of a diverse set of wild plants, find known and previously un-known viruses and show that wild plant species harbor more viruses when surrounded by less natural vegetation and when they have traits that promote increased plant-pollinator vector interactions. [ABSTRACT FROM AUTHOR]

The article explores the use of state licensing schemes for recovery homes as an exercise of implicit preemption. It mentions local siting trends locally undesirable land uses (LULUs) with the development of legal protections for recovery homes as a subtype of group homes, and the nature of subsequent local regulation. It also mentions the legal bounds of coercive licensing models, given Fair Housing Act (FHA) safeguards against discrimination.

The recent introduction of large geospatial databases and virtual measurement devices for streams of the United States have the potential to greatly improve stream classification systems as well as answer fundamental questions about river morphology. The physical condition of over 800 streams of the adjoining Upper Midwest and Temperate Plains ecoregions of the northcentral US were analyzed using principle components analysis of 10 selected site variables. Delineation was along three axes, with the first axis corresponding to differences in base flow, temperature, and soil permeability; the second corresponding to stream gradient, depth to bedrock and water table, and composite topographic index; and the third corresponding to stream sinuosity. Separation of streams into the two ecoregions was distinct, and primarily along axis 1. Adding a secondary matrix of 10 anthropogenic and geographic predictor variables produced a similar ecoregional separation, with latitude, percent of non-native plants, and overall intact habitat corresponding with axis 1. Natural and anthropogenic differences in streams of these two ecoregions appear inexorably linked, a situation probably common throughout the developed world. [ABSTRACT FROM AUTHOR]

White‐tailed deer (Odocoileus virginianus) populations have recovered to about 30 million animals in the United States, but land cover has changed during the interval of recovery. To address the relationship between deer densities and current land cover at regional scales, I applied random forests and extreme gradient boosting classifiers to model low and high deer density classes, at two different thresholds (5.8 and 11.6 deer/km2), and land classes in three regions during approximately 2003. For low and high deer density classes divided at 5.8 deer/km2, deciduous broadleaf forest overall was the most influential and positive variable in the central east and central regions and crop and pasture were the most influential and negative variables in the southeast region. Deer density increased with area of deciduous and mixed forests, woody wetlands, and shrub in all regions. Deer density decreased with area of crop, developed open space, and developed low and medium residential density in all regions. For density classes divided at 11.6 deer/km2, deer density had the strongest relationship with woody wetlands in the central east region, mixed and deciduous forest in the southeast region, and woody wetlands and herbaceous vegetation in the central region. Deer density increased with deciduous and mixed forests, woody wetlands, and shrub in all regions. Conversely, deer density decreased with herbaceous vegetation, crop, and developed low residential densities in all regions. Therefore, at regional scales, deer overall occurred at greater densities in forests and woody wetlands and lower densities in agricultural and residential development, which did not appear to support more deer. Deer preference for forests does result in damage to forest products, but alternatively, some may consider that deer provide important socioeconomic and ecological services by reducing number of small trees, particularly in the absence of other disturbances that historically controlled tree biomass. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

Although most landslides are precipitation‐triggered, a number of other complex conditions simultaneously predispose any given slope to failure, with the impact of urbanization posing particular scientific challenges. We use panel regression with fixed effects—which controls for observed and unobserved time‐variant and time‐invariant influences—to quantify the effect of precipitation accumulation on landslide concentration across the Pacific Coast region of the United States. We find that landslide hazard is most sensitive to precipitation variations in urbanized areas. This finding is robust across 1‐day, 10‐day, and 30‐day periods of precipitation accumulation, among individual Pacific Coast states, and when the analysis is confined to the San Francisco Bay Area (a subregion with both urban and rural areas). Our results corroborate existing hypotheses that urbanization increases landslide hazard, while demonstrating the importance of considering interactions with urbanization when predicting landslide hazard in the current climate, and under climate change scenarios. Plain Language Summary: Generalizable understanding of where and how landslides occur may inform efforts to adapt to these devastating natural disasters. While most landslides are triggered by precipitation, a number of other complex factors also play a role in slope destabilization. Employing an empirical framework that accounts for these confounding factors, we find that landslide hazard is most sensitive to precipitation variations in urbanized areas. Our results enhance understanding of the impact of urbanization on precipitation‐triggered landslide hazard and highlight the importance of considering urbanization when predicting landslide hazard, particularly in response to global warming and climate change. Key Points: We quantify the effect of precipitation on landslide concentration within distinct land use types across the US Pacific CoastLandslide hazard is most sensitive to precipitation variations in urbanized areasResults highlight the importance of considering interactions with urbanization when predicting landslide response to climate [ABSTRACT FROM AUTHOR]

Aquatic fecal contamination poses human health risks by introducing pathogens in water that may be used for recreation, consumption, or agriculture. Identifying fecal contaminant sources, as well as the factors that affect their transport, storage, and decay, is essential for protecting human health. However, identifying these factors is often difficult when using fecal indicator bacteria (FIB) because FIB levels in surface water are often the product of multiple contaminant sources. In contrast, microbial source-tracking (MST) techniques allow not only the identification of predominant contaminant sources but also the quantification of factors affecting the transport, storage, and decay of fecal contaminants from specific hosts. We visited 68 streams in the Finger Lakes region of Upstate New York, United States, between April and October 2018 and collected water quality data (i.e., Escherichia coli , MST markers, and physical–chemical parameters) and weather and land-use data, as well as data on other stream features (e.g., stream bed composition), to identify factors that were associated with fecal contamination at a regional scale. We then applied both generalized linear mixed models and conditional inference trees to identify factors and combinations of factors that were significantly associated with human and ruminant fecal contamination. We found that human contaminants were more likely to be identified when the developed area within the 60 m stream buffer exceeded 3.4%, the total developed area in the watershed exceeded 41%, or if stormwater outfalls were present immediately upstream of the sampling site. When these features were not present, human MST markers were more likely to be found when rainfall during the preceding day exceeded 1.5 cm. The presence of upstream campgrounds was also significantly associated with human MST marker detection. In addition to rainfall and water quality parameters associated with rainfall (e.g., turbidity), the minimum distance to upstream cattle operations, the proportion of the 60 m buffer used for cropland, and the presence of submerged aquatic vegetation at the sampling site were all associated based on univariable regression with elevated levels of ruminant markers. The identification of specific features associated with host-specific fecal contaminants may support the development of broader recommendations or policies aimed at reducing levels of aquatic fecal contamination. [ABSTRACT FROM AUTHOR]

Land use and transportation are intricately linked. Transportation intersects with some of the most important issues covered in the land use law curriculum, including among others the wisdom of "Euclidean" zoning ordinances that mandate the segregation of uses, the advantages and disadvantages of ad hoc land use decision-making processes in which local officials have enormous discretion and leverage over landowners, the political economy of land use decisions, the interaction between land use and climate change policy, and questions about racial segregation, gentrification and displacement. Strangely, however, transportation issues are largely neglected in the existing land use curriculum. While concerns about parking and traffic are ever-present in land use disputes, land use casebooks generally treat these concerns as straightforward issues that require little analysis. After all, everyone understands how frustrating it is to get stuck in traffic. But considering how predominant traffic and parking concerns have become in land use practice, teachers may find it useful to probe a bit more deeply into transportation questions in the land use course. After all, land use lawyers often find to their chagrin that they spend relatively little time dealing with juicy constitutional issues like the takings clause and far more time addressing hyperbolic, fact-free predictions of impending traffic nightmares from new development. This symposium contribution offers three ideas about how transportation may be incorporated into the land use curriculum. First, teachers should consider introducing an analysis of "traffic impact studies" into the existing coverage of discretionary land use controls such as subdivision review. Traffic impact studies are among the most important tools used in land use planning today, and although they are often treated as inscrutable and given enormous deference by courts, they are actually incredibly simplistic documents filled with dubious assumptions that reflect an ideological preference for the automobile. Students will find "going under the hood" of a traffic study to be highly illuminating. Second, teachers may find it useful to discuss California's potentially epochal recent shift in measuring traffic impacts from "level of service" to "vehicle miles traveled." This discussion will help students see the disconnect between good policy and good politics when it comes to addressing issues like climate change and housing affordability. Third, I suggest a new approach toward teaching the "new urbanism," a planning movement that seeks to re-imagine the relationship between urban planning and transportation. This approach relies less on the conventional "case method" of law teaching and more on studying critical texts that raise doubts about traditional land use planning practices while also introducing difficult questions of race and inequality that surround efforts to reform those practices. Integrating transportation into the land use curriculum in the manner I describe will hopefully have several beneficial outcomes: first, it will better prepare students to deal with transportation issues in practice; second, it will enrich and deepen the coverage of some of the more arid parts of the land use curriculum, such as the standard of judicial review applied to "quasi-judicial" land use decisions; and third, it will permit the course to branch out into areas that are often neglected in the conventional land use curriculum, such as the debate over gentrification. [ABSTRACT FROM AUTHOR]

Losses from natural hazards are escalating dramatically, with more properties and critical infrastructure affected each year. Although the magnitude, intensity, and/or frequency of certain hazards has increased, development contributes to this unsustainable trend, as disasters emerge when natural disturbances meet vulnerable assets and populations. To diagnose development patterns leading to increased exposure in the conterminous United States (CONUS), we identified earthquake, flood, hurricane, tornado, and wildfire hazard hotspots, and overlaid them with land use information from the Historical Settlement Data Compilation data set. Our results show that 57% of structures (homes, schools, hospitals, office buildings, etc.) are located in hazard hotspots, which represent only a third of CONUS area, and ∼1.5 million buildings lie in hotspots for two or more hazards. These critical levels of exposure are the legacy of decades of sustained growth and point to our inability, lack of knowledge, or unwillingness to limit development in hazardous zones. Development in these areas is still growing more rapidly than the baseline rates for the nation, portending larger future losses even if the effects of climate change are not considered. Key Points: More than half of the structures in the conterminous United States are exposed to potentially devastating natural hazardsGrowth rates in hazard hotspots exceed the national trendRisk assessments can be improved by considering multiple hazards, mitigation history and fine‐scale data on the built environment [ABSTRACT FROM AUTHOR]

Property law’s roots are rural. America pursued an early agrarian vision that understood real property rights as instrumental to achieving a country of free, engaged citizens who cared for their communities and stewarded their physical place in it. But we have drifted far from this ideal. Today, American agriculture is industrialized, and rural communities are in decline. The fee simple ownership form has failed every agrarian objective but one: the maintenance of white landownership. For it was also embedded in the original American experiment that land ownership would be racialized for the benefit of its white citizens, through acts of colonialism, slavery, and explicit race-based exclusion in property law. Today, rather than undoing this racialized legacy, modern property rules only further concentrate and homogenize rural landownership. Agricultural landownership remains almost entirely—98 percent—white. This is a critical racial justice issue that converges directly with our impending environmental crisis and the decline of rural communities more generally. This Article builds on work of rural sociologists and farm advocates who demonstrate, again and again, that despite a pervasive narrative of rural places dying for want of population and agricultural systems too far gone for reform, the reality is a crowd of emerging farmers—and farmers of color in particular—clamoring for access. Existing policy efforts to support beginning farmers have focused primarily on supporting a few private land transactions within existing systems. This Article brings property theory to the table for the first time, arguing that property law itself is not only responsible for the original racialized distributions of agricultural land but also actively perpetuates both ongoing racialized disparities and the currently industrialized and depopulated rural landscape. This Article deconstructs our most fundamental land-tenure choice—the fee simple itself—and calls on our collective legal imagination to develop more adaptive, inclusive, and dynamic land-tenure designs rooted in these otherwise overlooked rural places. [ABSTRACT FROM AUTHOR]

In Masterpiece Cakeshop, the baker's lead argument to the Supreme Court was that his cakes were artworks, so antidiscrimination laws could not apply. Across the country, vendors who refuse to provide services for same-sex weddings continue making similar arguments on behalf of their floral arrangements, videos, calligraphy, and graphic design, and the Supreme Court will again be asked to consider their claims. But arguments like these--what we might call "artistic exemption claims," akin to the religious exemptions so much more widely discussed--are actually made throughout the law, not just in public accommodations cases like Masterpiece Cakeshop. In areas ranging from tax and tort, employment and contracting discrimination, to trademark, land use, and criminal law, litigants argue that otherwise generally applicable laws simply do not apply to artists or their artworks. This Article collects these artistic exemption claims together for the first time in order to examine what determines their occasional success--and to ask when and whether they should succeed. The surprising answer is that claims of the form "x is protected because it is art" should never succeed. The category "art" is constitutionally irrelevant. Contrary to widespread assertion among scholars and advocates, a work's status as art has never done any work in the Supreme Court's First Amendment case law. Instead, the Supreme Court emphasizes individual mediums of expression--categories like paintings and protest marches, books and billboards. Compared to the category "art," these mediums of expression are better defined, easier to administer, and more relevant to that which the law most likely and legitimately wants to regulate. Yet they have gotten far less attention from scholars and lower courts than they deserve. Understanding the constitutional irrelevance of art--and the constitutional importance of mediums--casts new light on some of the most prominent recent and looming artistic exemption claims at the Supreme Court: not just those made in same-sex wedding cases like Masterpiece Cakeshop and its kin but also those made in challenges to race discrimination in television and in criminal threat prosecutions brought against rappers. Asking whether a cake, a TV show, or a rap song is art uselessly distracts from the difficult issues actually at stake in those important cases and in First Amendment doctrine more broadly. [ABSTRACT FROM AUTHOR]

This article examines the effect of U.S. Endangered Species Act (ESA) regulations on agricultural values. Agricultural development is an important contributor to habitat and biodiversity loss in the United States. The ESA attempts to limit this loss by prohibiting habitat destruction on private lands, but this practice is controversial because it places much of the burden for conservation on farmers. I measure the effect of these restrictions on agriculture using a hedonic analysis of county‐level agricultural land values, profits, and revenues reported in the last four rounds of the agricultural census. Results provide strong evidence that ESA regulations depress these three economic measures in dryland areas, which includes counties with less than 1% of agricultural land in irrigation. Specifically, I find that farmland value and profit decline 4% after listing on average at the county level in dryland areas with protected habitat. There is no evidence that values are affected in irrigated counties. [ABSTRACT FROM AUTHOR]

Incidence of Lyme disease, a tick-borne illness prevalent in the US, is increasing in endemic regions and regions with no previous history of the disease, significantly impacting public health. We examined space-time patterns of Lyme disease incidence and the influence of ecological and social factors on spatial synchrony, i.e., correlated incidence fluctuations across US counties. Specifically, we addressed these questions: Does Lyme disease incidence exhibit spatial synchrony? If so, what geographic patterns does Lyme disease synchrony exhibit? Are geographic patterns of disease synchrony related to weather, land cover, access to health care, or tick-borne disease awareness? How do effects of these variables on Lyme disease synchrony differ geographically? We used network analysis and matrix regression to examine geographical patterns of Lyme disease synchrony and their potential mechanisms in 399 counties in the eastern and Midwestern US. We found two distinct regions of synchrony in Northeast and upper Midwest regions exhibiting opposing temporal fluctuations in incidence. Spatial patterns of Lyme disease synchrony were partly explained by land cover, weather, poverty, and awareness of tick-borne illness, with significant predictive variables changing regionally. However, the two regions may have become more synchronous over time, potentially leading to higher-amplitude nation-wide fluctuations in disease incidence., (© 2024. The Author(s).)

Atrazine contamination is ubiquitous in North American surface waters, but the dependency of the herbicide's distribution on landscape and within‐lake processes is currently poorly known. We sought to identify novel predictors of atrazine and to build a coherent framework to model its concentration in waterbodies through the development of binomial‐gamma hurdle models and LASSO regression models. We constructed models for over 900 waterbodies in the contiguous United States using data from the 2012 U.S. EPA National Lake Assessment, the 2012 U.S. Department of Agriculture CropScape and the Global HydroLAB HydroLAKES databases. Atrazine was detected in 32% of U.S. waterbodies, with a mean concentration of 0.17 μg L−1 when detected. The two‐part hurdle model explained as much as 75% of the variance in atrazine across a spatially and temporally heterogeneous landscape. Three predictors explained 31% of the variability in atrazine detection in U.S. waterbodies, where the proportion of corn + soy cultures in the watershed was the most important variable. Once atrazine was detected, our models explained an additional 29% of the variability in atrazine concentrations, where the estimated areal weight of atrazine application (kg atrazine km2) in the watershed was the most important predictor. Spatially, water quality variables associated with eutrophication were linked to increased levels of atrazine contamination while cooler water temperatures and natural lakes and landscapes were associated with decreased levels of contamination. Our results suggest that changes in land‐use practices may be the most effective way to mitigate atrazine contamination in waterbodies. [ABSTRACT FROM AUTHOR]

The justification and targeting of conservation policy rests on reliable measures of public and private benefits from competing land uses. Advances in Earth system observation and modeling permit the mapping of public ecosystem services at unprecedented scales and resolutions, prompting new proposals for land protection policies and priorities. Data on private benefits from land use are not available at similar scales and resolutions, resulting in a data mismatch with unknown consequences. Here I show that private benefits from land can be quantified at large scales and high resolutions, and that doing so can have important implications for conservation policy models. I developed high-resolution estimates of fair market value of private lands in the contiguous United States by training tree-based ensemble models on 6 million land sales. The resulting estimates predict conservation cost with up to 8.5 times greater accuracy than earlier proxies. Studies using coarser cost proxies underestimate conservation costs, especially at the expensive tail of the distribution. This has led to underestimations of policy budgets by factors of up to 37.5 in recent work. More accurate cost accounting will help policy makers acknowledge the full magnitude of contemporary conservation challenges and can help improve the targeting of public ecosystem service investments. [ABSTRACT FROM AUTHOR]