Goldilocks scenario how to#

However, researchers now have access to multiple data sources at very high resolutions.

When access to spatial data was limited, this was the only assumption possible. In only a few instances have researchers examined conservation impacts at multiple scales, suggesting that for the most part, analysts implicitly assume that choices about scale will not affect estimates of treatment effects for conservation programs. Until now, the scale and structure of spatial data has been taken as given and estimates of conservation programs have used units of analyses that range from small pixels to 5x5 km grids ( Table 1). In this paper, we examine how the choice of scale influences estimates of program impact when evaluating conservation programs. These high quality data provide researchers with new opportunities to monitor and quantify the impact of conservation programs such as protected areas, payment for environmental services (PES) programs or forest management practices. We have witnessed vast improvements in the quality of remote sensed imagery in the last decade, and it is now common to analyze spatial data obtained at resolutions of less than 1 m per pixel. Spatial data on land use or forest cover is a key ingredient for studies seeking to measure the impact of conservation programs. So, she tasted the last bowl of porridge. So, she tasted the porridge from the second bowl. 'This porridge is too hot!' exclaimed Goldilocks. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Д¬ompeting interests: The authors have declared that no competing interests exist. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Дata Availability: All relevant data are within the paper and its Supporting Information files.ДЇunding: This work was supported by University of Illinois Urbana Champaign (UIUC)-Universidad Nacional Autonoma de MГ©xico (UNAM) Joint Research Program. Received: OctoAccepted: NovemPublished: December 22, 2016Д¬opyright: В© 2016 Avelino et al. PLoS ONE 11(12):Д®ditor: Ben Bond-Lamberty, Pacific Northwest National Laboratory, UNITED STATES We conclude with suggestions on how researchers might navigate their choice of scale and aerial unit when evaluating conservation policies.Д¬itation: Avelino AFT, Baylis K, Honey-RosГ©s J (2016) Goldilocks and the Raster Grid: Selecting Scale when Evaluating Conservation Programs. While we do not find a solution to these issues, even though treatment effects are generally underestimated. Aggregation may reduce this bias for continuous variables, but aggregation exacerbates bias when using a discrete measure of treatment. This problem may be pronounced at small scales of analysis.

In our context, the MAUP may reflect an errors in variables problem, where imprecise measures of the independent variables will bias the coefficient estimates toward zero. Under more realistic conditions, we find biased estimates associated with scale choices that are both too large or too small relative to the data generating process or decision unit. We find that estimates of treatment effects and variable coefficients are only accurate under restrictive circumstances. We then develop a Monte Carlo experiment that simulates a conservation intervention. To illustrate the consequences of the MAUP, we begin by examining the effect of scale selection when evaluating a protected area in Mexico using real data. We introduce this dilemma to the literature on impact evaluation and then explore the tradeoffs made when choosing different areal units.

The bias associated with scale and unit selection is a part of a well-known dilemma called the modifiable areal unit problem (MAUP).

These choices affect the estimate of program impact. Studies that evaluate the impact of conservation programs have used multiple scales and areal units: from 5x5 km grids to 30m pixels to irregular units based on land uses or political boundaries.

Goldilocks scenario how to#

Access to high quality spatial data raises fundamental questions about how to select the appropriate scale and unit of analysis.