Allocating resources for land protection using continuous optimization: biodiversity conservation in the United States

Abstract

Spatial optimization approaches that were originally developed to help conservation organizations determine protection decisions over small spatial scales are now used to inform global or continental scale priority setting. However, the different decision contexts involved in large‐scale resource allocation need to be considered. We present a continuous optimization approach in which a decision‐maker allocates funding to regional offices. Local decision‐makers then use these funds to implement habitat protection efforts with varying effectiveness when evaluated in terms of the funder's goals. We illustrate this continuous formulation by examining the relative priority that should be given to different counties in the coterminous United States when acquiring land to establish new protected areas. If weighting all species equally, counties in the southwest United States, where large areas can be bought cheaply, are priorities for protection. If focusing only on species of conservation concern, priorities shift to locations rich in such species, particularly near expanding exurban areas facing high rates of future habitat conversion (e.g., south‐central Texas). Priorities for protection are sensitive to what is assumed about local ecological and decision‐making processes. For example, decision‐makers who doubt the efficacy of local land protection efforts should focus on a few key areas, while optimistic decision‐makers should disperse funding more widely. Efforts to inform large‐scale conservation priorities should reflect better the types of choice that decision‐makers actually face when working over these scales. They also need to report the sensitivity of recommended priorities to what are often unstated assumptions about local processes affecting conservation outcomes.

High-resolution land value maps reveal underestimation of conservation costs in the United States

“…• The National Agricultural Statistics Services (NASS) of the US Department of Agriculture (USDA) publishes county-level estimates of the average market value of agricultural land for all US counties, based on farmers' responses to the Census of Agriculture (21). USDA-NASS land value estimates have been used by several US-wide conservation planning analyses as cost proxies (10,17); however, a recent study casts doubt on the utility of these estimates as proxies for conservation cost (44). Human Footprint (GHF) raster layer (23), using the following formula:…”

“…Because such large-scale data have long been inaccessible to the public, many conservation planning studies have paid only limited attention to the costs that conservation organizations actually face (14). Nationwide prioritizations either ignore cost (15,16) or rely on untested proxies, such as estimated returns from extractive uses (9,11), farmer-reported agricultural land values (10,17), county-level models trained on observed acquisition costs (13), and remotely sensed human footprints (12), among others. Studies developing high-resolution, parcel-level estimates of land value are constrained to small spatial extents (18,19), limiting their utility for land use prioritization at large scales.…”

Optimizing the location of watercraft inspection stations to slow the spread of aquatic invasive species

“…Our formulation applies to a single, local governance unit (i.e., the county). In practice, the governance of AIS interventions and other conservation practices involves collaborative decision making at both the regional and local levels (Armsworth et al 2020). For example, the State of Minnesota allocates funds to counties for boat inspection and boater education to slow the spread of AIS within the state.…”

Consequences of underexplored variation in biodiversity indices used for land‐use prioritization

“…Although previous spatial studies have shown a lack of congruence among different taxonomic groups and different species richness metrics (Orme et al 2005, Ceballos and Ehrlich 2006, Grenyer et al 2006, Roll et al 2017, and others have identified differences in areas to be prioritized for conservation based on these biological factors (Veach et al 2017, Armsworth et al 2020, Sacre et al 2020), here we undertake a more systematic analysis of those differences and look at a broader range of criteria and decisions that go into biodiversity ranking systems. Using ensemble averaging methods to isolate the consequences of different categories of decisions, we compare recently published composite indices and explore the consequences of basic methodological variation stemming from different methods for combining layers and different input spatial resolutions, alongside biological variation.…”

“…2017, Armsworth et al. 2020, Sacre et al. 2020), here we undertake a more systematic analysis of those differences and look at a broader range of criteria and decisions that go into biodiversity ranking systems.…”