Landscape Equivalency Analysis: Methodology for Estimating Spatially Explicit Biodiversity Credits

Abstract

We propose a biodiversity credit system for trading endangered species habitat designed to minimize and reverse the negative effects of habitat loss and fragmentation, the leading cause of species endangerment in the United States. Given the increasing demand for land, approaches that explicitly balance economic goals against conservation goals are required. The Endangered Species Act balances these conflicts based on the cost to replace habitat. Conservation banking is a means to manage this balance, and we argue for its use to mitigate the effects of habitat fragmentation. Mitigating the effects of land development on biodiversity requires decisions that recognize regional ecological effects resulting from local economic decisions. We propose Landscape Equivalency Analysis (LEA), a landscape-scale approach similar to HEA, as an accounting system to calculate conservation banking credits so that habitat trades do not exacerbate regional ecological effects of local decisions. Credits purchased by public agencies or NGOs for purposes other than mitigating a take create a net investment in natural capital leading to habitat defragmentation. Credits calculated by LEA use metapopulation genetic theory to estimate sustainability criteria against which all trades are judged. The approach is rooted in well-accepted ecological, evolutionary, and economic theory, which helps compensate for the degree of uncertainty regarding the effects of habitat loss and fragmentation on endangered species. LEA requires application of greater scientific rigor than typically applied to endangered species management on private lands but provides an objective, conceptually sound basis for achieving the often conflicting goals of economic efficiency and long-term ecological sustainability.

Biodiversity offsets in theory and practice

“…in US wetlands), or the provision of services such as carbon sequestration. US conservation banking focuses on species diversity but Bruggeman et al (2005Bruggeman et al ( , 2009) explore how function and genetic diversity could be used as alternatives. The topic of measuring diversity as well as function is the subject of ongoing research (Cadotte et al, 2011) and we recommend that offsets should not target diversity alone.…”

Net Present Biodiversity Value and the Design of Biodiversity Offsets

“…The NPV of a financial transaction is simply the sum over the time period of the transaction of the discounted payments and debits. Time discounting has been used in for the design of biodiversity offsets and compensation (e.g., Dunford et al 2004;Bruggeman et al 2005;Moilanen et al 2008).…”

“…Salzman and Ruhl (2000) and Walker et al (2009) identify interrelated ecological and non-ecological problems with the implementation of offsets, including the complexity of biodiversity and the imbalances of power, interest, and information between developers and biodiversity protection groups, and Walker et al (2009) argue that these problems contribute to the failure of biodiversity offsets to protect biodiversity. Habitat equivalency analysis (Dunford et al 2004) and landscape equivalency analysis (Bruggeman et al 2005) provide methods for assessing equity of trades that include time discounting. Moilanen et al (2009) consider the implications for offset design of uncertainty and spatial autocorrelation in project success and incorporate time discounting.…”

Trading Habitat Patches for the Red Cockaded Woodpecker: Incorporating the Role of Landscape Structure and Uncertainty in Decision Making

“…Levels of genetic variance within and among breeding groups expected to result from the restoration program were used as the baseline levels for calculating LEA credits. This represents an adjustment from the "prior to habitat loss and fragmentation" condition for a baseline described in Bruggeman et al (2005) for trading among private landowners. The baseline trajectory of genetic services expected by the restoration plan represents the improvement in rates of recruitment, migration, and local extinction that result from meeting yearly recovery objectives and are feasible given soil types and existing land use.…”

“…Endangered species management may benefit from incorporating habitat defragmentation into recovery goals. Therefore, LEA adds a "spatially-explicit" recovery objective as the allocation of habitat yielding the spatial apportionment of genetic variance (e.g., as would be determined using neutral genetic markers) observed prior to habitat loss and fragmentation (Meffe 1996;Bruggeman et al 2005). Given existing loss of habitat in most landscapes, this goal will often be unachievable, but it does serve as an objective criterion for defragmenting endangered species habitat to protect evolutionary processes at the landscape scale.…”