Current And Future Land Use Around A Nationwide Protected Area Network

Land-use change around protected areas can reduce their effective size and limit their ability to conserve biodiversity because land-use change alters ecological processes and the ability of organisms to move freely among protected areas. The goal of our analysis was to inform conservation planning efforts for a nationwide network of protected lands by predicting future land use change. We evaluated the relative effect of three economic policy scenarios on land use surrounding the U.S. Fish and Wildlife Service\u27s National Wildlife Refuges. We predicted changes for three land-use classes (forest/range, crop/pasture, and urban) by 2051. Our results showed an increase in forest/range lands (by 1.9% to 4.7% depending on the scenario), a decrease in crop/pasture between 15.2% and 23.1%, and a substantial increase in urban land use between 28.5% and 57.0%. The magnitude of land-use change differed strongly among different USFWS administrative regions, with the most change in the Upper Midwestern US (approximately 30%), and the Southeastern and Northeastern US (25%), and the rest of the U.S. between 15 and 20%. Among our scenarios, changes in land use were similar, with the exception of our restricted-urban-growth\u27\u27 scenario, which resulted in noticeably different rates of change. This demonstrates that it will likely be difficult to influence land-use change patterns with national policies and that understanding regional land-use dynamics is critical for effective management and planning of protected lands throughout the U.S

Economic insecurities and patient-reported outcomes in patients with systemic lupus erythematosus in the USA: a cross-sectional analysis of data from the California Lupus Epidemiology Study

Background Social determinants of health are consistently associated with systemic lupus erythematosus (SLE) outcomes. However, social determinants of health are typically measured with conventional socioeconomic status factors such as income or education. We assessed the association of economic insecurities (ie, food, housing, health care, and financial insecurity) with patient-reported outcomes in a cohort of patients with SLE.Methods In this cross-sectional analysis, data were derived from the California Lupus Epidemiology Study based in the San Francisco Bay Area, CA, USA. Participants were recruited between Feb 25, 2015, and Jan 10, 2018, from rheumatology clinics. Inclusion criteria were Bay Area residency; oral fluency in English, Spanish, Cantonese, or Mandarin; 18 years or older; ability to provide informed consent; and a physician confirmed SLE diagnosis. Food, housing, health care, and financial economic insecurities were assessed by validated screening tools. Patient-reported outcomes were obtained using PROMIS, Quality of Life in Neurological Disorders (known as Neuro-QoL) Cognitive Function short form, Patient Health Questionnaire (PHQ)-8, and General Anxiety Disorder (GAD)-7 instruments. Poverty was defined as household income of 125% or less of the federal poverty limit. Lower education was defined as less than college-graduate education. The association of economic insecurities with patient-reported outcomes was assessed by multivariable linear regression models adjusting for demographics, SLE disease characteristics, and comorbidities. We tested for interactions of insecurities with poverty and education.Findings The final cohort included 252 participants. Mean age was 49·7 (SD 13·4) years, 228 (90%) of 252 were women and 24 (10%) were men. 80 (32%) individuals self-identified as Asian, 26 (10%) as Black, 101 (40%) as White, eight (3%) as mixed race, and 37 (15%) as other race; 59 (23%) self-identified as Hispanic. 135 (54%) individuals had at least one insecurity. Insecurities were highly prevalent, and more common in those with poverty and lower education. Adjusted multivariate analyses revealed that participants with any insecurity had significantly worse scores across all measured patient-reported outcomes. For physical function, no insecurity had an adjusted mean score of 48·9 (95% CI 47·5–50·3) and any insecurity had 45·7 (44·3–47·0; p=0·0017). For pain interference, no insecurity was 52·0 (50·5–53·5) and any insecurity was 54·4 (53·0–55·8; p=0·031). For fatigue, no insecurity was 50·5 (48·8–52·3) and any insecurity was 54·9 (53·3–56·5; p=0·0005). For sleep disturbance, no insecurity was 49·9 (48·3–51·6) and any insecurity was 52·9 (51·4–54·5; p=0·012). For cognitive function, no insecurity was 49·3 (47·7–50·9) and any insecurity was 45·6 (44·1–47·0; p=0·0011). For PHQ-8, no insecurity was 4·4 (3·6–5·1) and any insecurity was 6·1 (5·4–6·8; p=0·0013). For GAD-7, no insecurity was 3·3 (2·6–4·1) and any insecurity was 5·2 (4·5–5·9; p=0·0008). Individuals with more insecurities had worse patientreported outcomes. There were no statistically significant interactions between insecurities and poverty or education. Interpretation Having any economic insecurity was associated with worse outcomes for people with SLE regardless of poverty or education. The findings of this study provide insight into the relationship between economic insecurities and SLE outcomes and underscore the need to assess whether interventions that directly address these insecurities can reduce health disparities in SL

Current and Future Land Use around a Nationwide Protected Area Network

Land-use change around protected areas can reduce their effective size and limit their ability to conserve biodiversity because land-use change alters ecological processes and the ability of organisms to move freely among protected areas. The goal of our analysis was to inform conservation planning efforts for a nationwide network of protected lands by predicting future land use change. We evaluated the relative effect of three economic policy scenarios on land use surrounding the U.S. Fish and Wildlife Service’s National Wildlife Refuges. We predicted changes for three land-use classes (forest/range, crop/pasture, and urban) by 2051. Our results showed an increase in forest/range lands (by 1.9% to 4.7% depending on the scenario), a decrease in crop/pasture between 15.2% and 23.1%, and a substantial increase in urban land use between 28.5% and 57.0%. The magnitude of land-use change differed strongly among different USFWS administrative regions, with the most change in the Upper Midwestern US (approximately 30%), and the Southeastern and Northeastern US (25%), and the rest of the U.S. between 15 and 20%. Among our scenarios, changes in land use were similar, with the exception of our ‘‘restricted-urban-growth’’ scenario, which resulted in noticeably different rates of change. This demonstrates that it will likely be difficult to influence land-use change patterns with national policies and that understanding regional land-use dynamics is critical for effective management and planning of protected lands throughout the U.S

Developing population models with data from marked individuals

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, densitydependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources -notably, mark-recapture studies -remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark-recapture dataset. Unlike standard mark-recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from markrecapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern

Spring plant phenology and false springs in the conterminous US during the 21st century

The onset of spring plant growth has shifted earlier in the year over the past several decades due to rising global temperatures. Earlier spring onset may cause phenological mismatches between the availability of plant resources and dependent animals, and potentially lead to more false springs, when subsequent freezing temperatures damage new plant growth. We used the extended spring indices to project changes in spring onset, defined by leaf out and by first bloom, and predicted false springs until 2100 in the conterminous United States (US) using statistically-downscaled climate projections from the Coupled Model Intercomparison Project 5 ensemble. Averaged over our study region, the median shift in spring onset was 23 days earlier in the Representative Concentration Pathway 8.5 scenario with particularly large shifts in the Western US and the Great Plains. Spatial variation in phenology was due to the influence of short-term temperature changes around the time of spring onset versus season-long accumulation of warm temperatures. False spring risk increased in the Great Plains and portions of the Midwest, but remained constant or decreased elsewhere. We conclude that global climate change may have complex and spatially variable effects on spring onset and false springs, making local predictions of change difficult

Economic insecurities and patient-reported outcomes in patients with systemic lupus erythematosus in the USA: a cross-sectional analysis of data from the California Lupus Epidemiology Study

BackgroundSocial determinants of health are consistently associated with systemic lupus erythematosus (SLE) outcomes. However, social determinants of health are typically measured with conventional socioeconomic status factors such as income or education. We assessed the association of economic insecurities (ie, food, housing, health care, and financial insecurity) with patient-reported outcomes in a cohort of patients with SLE.MethodsIn this cross-sectional analysis, data were derived from the California Lupus Epidemiology Study based in the San Francisco Bay Area, CA, USA. Participants were recruited between Feb 25, 2015, and Jan 10, 2018, from rheumatology clinics. Inclusion criteria were Bay Area residency; oral fluency in English, Spanish, Cantonese, or Mandarin; 18 years or older; ability to provide informed consent; and a physician confirmed SLE diagnosis. Food, housing, health care, and financial economic insecurities were assessed by validated screening tools. Patient-reported outcomes were obtained using PROMIS, Quality of Life in Neurological Disorders (known as Neuro-QoL) Cognitive Function short form, Patient Health Questionnaire (PHQ)-8, and General Anxiety Disorder (GAD)-7 instruments. Poverty was defined as household income of 125% or less of the federal poverty limit. Lower education was defined as less than college-graduate education. The association of economic insecurities with patient-reported outcomes was assessed by multivariable linear regression models adjusting for demographics, SLE disease characteristics, and comorbidities. We tested for interactions of insecurities with poverty and education.FindingsThe final cohort included 252 participants. Mean age was 49·7 (SD 13·4) years, 228 (90%) of 252 were women and 24 (10%) were men. 80 (32%) individuals self-identified as Asian, 26 (10%) as Black, 101 (40%) as White, eight (3%) as mixed race, and 37 (15%) as other race; 59 (23%) self-identified as Hispanic. 135 (54%) individuals had at least one insecurity. Insecurities were highly prevalent, and more common in those with poverty and lower education. Adjusted multivariate analyses revealed that participants with any insecurity had significantly worse scores across all measured patient-reported outcomes. For physical function, no insecurity had an adjusted mean score of 48·9 (95% CI 47·5-50·3) and any insecurity had 45·7 (44·3-47·0; p=0·0017). For pain interference, no insecurity was 52·0 (50·5-53·5) and any insecurity was 54·4 (53·0-55·8; p=0·031). For fatigue, no insecurity was 50·5 (48·8-52·3) and any insecurity was 54·9 (53·3-56·5; p=0·0005). For sleep disturbance, no insecurity was 49·9 (48·3-51·6) and any insecurity was 52·9 (51·4-54·5; p=0·012). For cognitive function, no insecurity was 49·3 (47·7-50·9) and any insecurity was 45·6 (44·1-47·0; p=0·0011). For PHQ-8, no insecurity was 4·4 (3·6-5·1) and any insecurity was 6·1 (5·4-6·8; p=0·0013). For GAD-7, no insecurity was 3·3 (2·6-4·1) and any insecurity was 5·2 (4·5-5·9; p=0·0008). Individuals with more insecurities had worse patient-reported outcomes. There were no statistically significant interactions between insecurities and poverty or education.InterpretationHaving any economic insecurity was associated with worse outcomes for people with SLE regardless of poverty or education. The findings of this study provide insight into the relationship between economic insecurities and SLE outcomes and underscore the need to assess whether interventions that directly address these insecurities can reduce health disparities in SLE.FundingUS Centers for Disease Control, Rheumatology Research Foundation, and National Institute of Arthritis and Musculoskeletal and Skin Diseases

Long-Term Climate Average Models 2

Second half of data for species distribution models for long-term climate average model