A critical part of any conservation planning process is considering funding sources for the desired conservation action. Studies have revealed that the location of conservation spending is often constrained by the funding place of origin, either through institutional structure or political constraints. However, the current literature leaves out this important real-world limitation. Consequently, a solid understanding of the conservation revenue landscape may be a key tool in planning and prioritizing future projects. We explore the landscape of private donations for conservation and factors that determine its distribution by using a case study of fundraising success by The Nature Conservancy (TNC), the world’s largest conservation organization.
We construct a Generalized Linear Model fitting donation level resolved to the spatial scale of ZIP code to examine the spatial patterns of private fundraising across the continental U.S. In our model, we include demographic factors of the ZIP code from national survey data, geographic factors such as land use from the surrounding region (e.g. current amount of protected areas), as well as fundraising effort in the form of number of communication instances by TNC in that area.
Results/Conclusions
We illustrate a national pattern of conservation philanthropy using data from over 6500 ZIP codes with positive contribution amounts. Philanthropic giving shows patterns of spatial aggregation and tends to be highest in coastal regions and metropolitan areas. Annual gift amounts in our case study, grouped by ZIP code, ranges in size across three orders of magnitude. We explicitly conclude that fundraising effort has a positive and consistent effect on total donations received from an area. We report and compare across best models using AIC that explain fundraising with demographic predictors (average income, average educational attainment level, and household composition) and geographic factors. Our work will help reveal which regions are currently exhibiting fundraising success and how that may skew conservation practice through spatial constraint. By highlighting characteristics of areas that are likely to support conservation work, we hope to direct future conservation efforts.