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1.
Conserv Biol ; 31(4): 848-859, 2017 08.
Artigo em Inglês | MEDLINE | ID: mdl-28218793

RESUMO

Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity-score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions.


Assuntos
Agricultura , Conservação dos Recursos Naturais , Ecossistema , Pradaria
2.
Am J Health Promot ; 19(2): 128-36, 2004.
Artigo em Inglês | MEDLINE | ID: mdl-15559713

RESUMO

PURPOSE: This study evaluates the relationship between neighborhood design and rates of students walking and biking to elementary school. DESIGN: Pairwise correlations and multiple regression models were estimated based on a cross-sectional study of elementary schools and their surrounding neighborhoods. Setting and Subjects. Thirty-four (23%) of 150 California public elementary schools holding October 1999 Walk to School Day events participated in the study. MEASURES: Teachers asked fifth-grade students how they arrived to school 1 week before Walk to School Day. 1990 U.S. Census data measured population density and number of intersections per street mile, whereas 1998-1999 California Department of Education data measured school size, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. RESULTS: Population density (p = .000) and school size (p = .053) were significantly associated with walking and biking rates in regression models controlling for number of intersections per street mile, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. The number of intersections per street mile was associated with walking and biking rates in pairwise correlations (p = .003) but not in regression models. CONCLUSIONS: The results support the hypothesis that the walking and biking rates are higher in denser neighborhoods and to smaller schools but do not support the hypothesis that rates are higher in neighborhoods with a high number of intersections per street mile. We suggest that detailed data for a larger sample of students would allow statistical models to isolate the effect of specific design characteristics.


Assuntos
Ciclismo/estatística & dados numéricos , Características de Residência , Instituições Acadêmicas , Caminhada/estatística & dados numéricos , California , Criança , Estudos Transversais , Feminino , Humanos , Masculino , Análise de Regressão
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