Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness.

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures-ways of generating matching pairs at different scales-in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.

Efectos de la Autocorrelación Espacial y el Diseño del Muestreo sobre las Estimaciones de la Efectividad de Áreas Protegidas Resumen La estimación de la efectividad de las áreas protegidas (AP) para reducir la deforestación es útil al momento de respaldar las decisiones que eligen entre invertir en un mejor manejo de las áreas ya protegidas o crear áreas nuevas. El emparejamiento estadístico es la herramienta utilizada con mayor frecuencia para evaluar esta efectividad, pero casi siempre se ignora la autocorrelación especial y las diferencias regionales en la efectividad de la protección. Con Colombia como caso de estudio, empleamos un emparejamiento estadístico para controlar el efecto de factores relacionados con la ubicación la ubicación de los parques y he incluimos el efecto de la autocorrelación especial para determinar la significancia estadística. Comparamos el desempeño de los diferentes procedimientos de emparejamiento - las maneras de generar pares a diferentes escalas - en la estimación de la efectividad de las AP. Las diferencias en los procedimientos de emparejamiento afectaron la similitud de la covarianza entre los pares emparejados (balance) y la estimación de la efectividad de las AP en la reducción de la deforestación. El emparejamiento independiente produjo el mayor balance. En promedio, el 95% de las variables en cada región estuvo balanceado con el emparejamiento independiente, mientras que el 24% de las variables estuvo balanceado cuando se usó el método con el peor desempeño. Las mejores estimaciones sugieren que la deforestación media dentro de las áreas protegidas en Colombia era 40% menor que en los sitios emparejados emparejados. La protección redujo significativamente la deforestación, aunque la efectividad de las AP difirió entre las regiones. Las AP en la región Caribe fueron las más efectivas, mientras que aquellas en la Orinoquía y el Pacífico fueron las menos efectivas. Nuestros resultados demuestran que se necesita considerar la autocorrelación espacial y usar el emparejamiento independiente para cada subconjunto de datos para inferir la efectividad de la protección en la reducción de la deforestación. Si no se considera la autocorrelación espacial, se pueden distorsionar los estimativos de la efectividad de la protección, incrementando los errores de tipo I y II e inflando el tamaño del efecto. Nuestro método permitió obtener mejores estimaciones de la efectividad de la protección en todas las escalas y bajo diferentes condiciones y puede aplicarse a otras regiones para evaluar de manera efectiva el desempeño de las AP.

Inequality in access to cultural ecosystem services from protected areas in the Chilean biodiversity hotspot.

Experiences with nature through visits to protected areas provide important cultural ecosystem services that have the potential to strengthen pro-environmental attitudes and behavior. Understanding accessibility to protected areas and likely preferences for enjoying the benefits of nature visits are key factors in identifying ways to reduce inequality in access and inform the planning and management for future protected areas. We develop, at a regional scale, a novel social media database of visits to public protected areas in part of the Chilean biodiversity hotspot using geotagged photographs and assess the inequality of access using the home locations of the visitors and socio-economic data. We find that 20% of the population of the region make 87% of the visits to protected areas. The larger, more biodiverse protected areas were the most visited and provided most cultural ecosystem services. Wealthier people tend to travel further to visit protected areas while people with lower incomes tend to visit protected areas that are closer to home. By providing information on the current spatial flows of people to protected areas, we demonstrate the need to expand the protected area network, especially in lower income areas, to reduce inequality in access to the benefits from cultural ecosystem services provided by nature to people.

Noninvasive Cardiac Output Estimation by Inert Gas Rebreathing in Mechanically Ventilated Pediatric Patients.

OBJECTIVE: To assess the feasibility and accuracy of inert gas rebreathing (IGR) pulmonary blood flow (Qp) estimation in mechanically ventilated pediatric patients, potentially providing real-time noninvasive estimates of cardiac output. STUDY DESIGN: In mechanically ventilated patients in the pediatric catheterization laboratory, we compared IGR Qp with Qp estimates based upon the Fick equation using measured oxygen consumption (VO2) (FickTrue); for context, we compared FickTrue with a standard clinical short-cut, replacing measured with assumed VO2 in the Fick equation (FickLaFarge, FickLundell, FickSeckeler). IGR Qp and breath-by-breath VO2 were measured using the Innocor device. Sampled pulmonary arterial and venous saturations and hemoglobin concentration were used for Fick calculations. Qp estimates were compared using Bland-Altman agreement and Spearman correlation. RESULTS: The final analysis included 18 patients aged 4-23 years with weight >15 kg. Compared with the reference FickTrue, IGR Qp estimates correlated best and had the least systematic bias and narrowest 95% limits of agreement (results presented as mean bias ±95% limits of agreement): IGR -0.2 ± 1.1 L/min, r = 0.90; FickLaFarge +0.7 ± 2.2 L/min, r = 0.80; FickLundell +1.6 ± 2.9 L/min, r = 0.83; FickSeckeler +0.8 ± 2.5 L/min, r = 0.83. CONCLUSIONS: IGR estimation of Qp is feasible in mechanically ventilated patients weighing >15 kg, and agreement with FickTrue Qp estimates is better for IGR than for other Fick Qp estimates commonly used in pediatric catheterization. IGR is an attractive option for bedside monitoring of Qp in mechanically ventilated children.

Birds in Anthropogenic Landscapes: The Responses of Ecological Groups to Forest Loss in the Brazilian Atlantic Forest.

Habitat loss is the dominant threat to biodiversity and ecosystem functioning in terrestrial environments. In this study, we used an a priori classification of bird species based on their dependence on native forest habitats (forest-specialist and habitat generalists) and specific food resources (frugivores and insectivores) to evaluate their responses to forest cover reduction in landscapes in the Brazilian Atlantic Forest. From the patch-landscapes approach, we delimited 40 forest sites, and quantified the percentage of native forest within a 2 km radius around the center of each site (from 6 - 85%). At each site, we sampled birds using the point-count method. We used a null model, a generalized linear model and a four-parameter logistic model to evaluate the relationship between richness and abundance of the bird groups and the native forest amount. A piecewise model was then used to determine the threshold value for bird groups that showed nonlinear responses. The richness and abundance of the bird community as a whole were not affected by changes in forest cover in this region. However, a decrease in forest cover had a negative effect on diversity of forest-specialist, frugivorous and insectivorous birds, and a positive effect on generalist birds. The species richness and abundance of all ecological groups were nonlinearly related to forest reduction and showed similar threshold values, i.e., there were abrupt changes in individuals and species numbers when forest amount was less than approximately 50%. Forest sites within landscapes with forest cover that was less than 50% contained a different bird species composition than more extensively forested sites and had fewer forest-specialist species and higher beta-diversity. Our study demonstrated the pervasive effect of forest reduction on bird communities in one of the most important hotspots for bird conservation and shows that many vulnerable species require extensive forest cover to persist.