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US President Barack Obama's presidential memorandum on mitigation emphasized the private sector role in delivering a net benefit to the environment at a landscape level. But achieving landscape-scale benefits for species means more than increasing total habitat area, says ecological economist Douglas J. Bruggeman. Here, he discusses ways in which the memo may alter species markets.
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11 January 2016 | On November 3rd President Barack Obama issued a memorandum calling for environmental markets to develop large-scale solutions that lead to a net benefit for the environment. Environmental markets pay landowners to provide ecosystem services such as water purification and retention, species habitat, or carbon sequestration to name the most common. For example, if we restore forested floodplains to reduce nutrient runoff into streams, then we can forego building or expanding a water treatment plant - the New York City watershed is the classic example here. Alternatively, if real estate development destroys wetlands or endangered species habitat then the Clean Water Act and Endangered Species Act, respectively, require replacing wetlands or species habitat at another location to achieve no net loss. So, if the cost of paying someone to provide ecosystem services at a another location is much less than you expect to make by developing a piece of land then a market is created due to the existence of environmental regulation.
President Obama's memorandum encouraged the application of innovative solutions from the private sector to achieve net environmental benefits at a landscape-scale. Net environmental benefits across a landscape are more easily achieved when markets use ecosystems to replace water treatment plants, than when markets permit real estate development while preventing harm to a threatened and endangered species. These species are often affected by differences in the quality of habitat patches across the landscape, land use (e.g., roads or agricultural fields) that prevent or slow their dispersal, and time lags that make it difficult to understand if they are reproducing fast enough to persist in habitat patches even though we can see them now.
I have been developing ways to estimate how equal, or equivalent, habitat trades are for threatened and endangered species when applying a landscape-scale perspective as the President has recently recommended. Species markets have provided a critical tool to allow economic development to occur while adhering to the Endangered Species Act. When individual development projects unavoidably harm habitat, land owners can purchase credits, most often valued based on acreage of habitat, from a conservation credit provider. The provider of conservation credits is often someone with a large piece of land who wants to sell credits to many different landowners.
Providing a landscape perspective to species' markets require that we recognize how the value of a trade is affected by dispersal of critters among patches of habitat often scattered across the landscape. In other words, habitat patches can be of equal habitat area but may not be able to provide the same number of critters that can successfully disperse across the landscape to find a new home. Therefore, simply increasing total habitat area without considering a landscape perspective may not lead to net environmental benefits.
I would argue then, President Obama is calling for a disruptive change for species' markets. This is an important memorandum.
If You Build it, They will ComeThis iconic phrase from "The Field of Dreams" highlights the challenge of applying a landscape perspective to species markets. In our case "they" are the threatened or endangered species, which are often as mysterious as the ghosts from the 1919 Black Sox team, and rather than a baseball diamond we are providing habitat. When working to manage these species there is often no or little data describing how the animals disperse, but data regarding what constitutes good habitat for survival and reproduction is assembled more quickly. From this perspective, trading based on habitat area and ignoring a landscape perspective makes sense.
Also, maybe it doesn't matter "if they come", because credit providers often use large tracts of land and assume that dispersal into their land does not increase the number of credits they can sell. This then leads to the assumption that the locations where habitats are lost also do not contribute any dispersal value to the landscape. The result can be an increase in extinction risk or increased rates of inbreeding across the landscape due to the loss of critters dispersing from habitats removed. Thus, in this case trades are undervalued because a landscape-perspective was not applied. This is a lose-lose outcome for the species and some landowners - the exception being those landowners who might be glad that their neighbor's purchase of a mitigation credit caused extinction on their land. More detail from a scientific paper can be found here.
Sustainable Market Outcomes by Embracing UncertaintyI get the impression that a landscape perspective has been avoided out of fear that applying more detailed scientific analysis will prevent or slow decision making. Importantly, the Endangered Species Act only requires the best available science, so if uncertainties about dispersal, for example, have not been characterized prior to a trade they could be ignored. But what if embracing uncertainty could lead to a win for the species and the landowners involved? Then, we could begin leveraging private investment to apply a landscape perspective within species' markets (e.g., include the role of dispersal).
My publication in PLOS ONE this week highlights how embracing uncertainty and applying a landscape perspective leads to a win-win for species and landowners. The publication highlights how applying simulation models of species can provide a common currency for trading habitat, while including a landscape perspective. The approach can be applied to any species and incorporates uncertainty regarding how species disperse across a landscape. The publication assumes that we want to use these environmental markets to learn about how nature works as we change land use over time.
The computer simulation model was built to estimate and reduce uncertainty about dispersal by comparing model predictions to field data. Think of it as a scientific "school of hard knocks" - as markets change where habitats are located, a simulation model can be used to see if the population responds as predicted based on different dispersal models. I hope "learning" within these markets is included within the updated policies the President's memorandum is requesting.
The President's memorandum did recognize the need for large-scale plans and analysis. Importantly, the type of analysis we employ can greatly affect our ability to learn within these markets. Landscape simulation models can be classified as "tactical models" that do well predicting where critters are and how many are still there after a hard winter or after a neighbor removes habitat, which requires an Incidental Take permit. To get a better idea of a tactical model, imagine coding a Marty Stouffer PBS special ("Wild America"), which describes how critters find mates, rear young, and how the young survive to adulthood, into a computer.
The PLOS ONE article highlights how uncertainty about dispersal within a tactical model can prevent finding the most cost-effective trade across a landscape. The publication focuses on the Red-cockaded Woodpecker, one of the most heavily studied endangered species in the U.S., and yet we are still uncertain how they disperse across the landscape. Results indicated that we often understand dispersal well enough to find the most cost-effective trade in spite of uncertainty. One exception occurred when including loss of dispersal habitat over time. In this case, the approach allows us to estimate how much money we should investment in further data collection and/or modeling to reduce uncertainty, which ranged from $467K to $987K depending on which trades were made. These values reflect the amount of money lost when trades are made without a better understanding of dispersal. Under the Endangered Species Act, the trade could still be made without taking the time to learn, my analysis just highlights the financial benefit of learning.
Though we lack regulatory support for delaying decisions regarding habitat loss, delaying decisions is probably a wiser financial choice than we realize. In other words, science is often cost-effective, especially for sustainable investing.
I have built landscape simulation models for more poorly understood species as well. That model indicated that the most cost-effective trade could not be identified. However, this should not be seen as a problem - trades could still be made and the model provides a great opportunity for compiling data to learn about the species over time. Also, such models would help identify what financial assurances could compensate for scientific uncertainty. More simple models that ignore landscape uncertainty will unlikely be able to identify the most cost-effective trade and are less likely to provide durable conservation outcomes.
Landscape simulation models can likely be built for new species for less than 10% of the total market value, and the cost will drop considerably after applying to each new market. Tactical simulation models of species could also be used to support listing/delisting decisions, designation of critical habitat, and recovery planning.
The President called for clear, durable, and transferable processes to manage landscape-scale markets across federal agencies. Tactical landscape simulation models designed to manage uncertainty could facilitate achieving this goal, though conservation practitioners will view the technology as a disruptive change. The alternative of continuing to rely on administrative processes that lead to programmatic rules may become difficult when applying a landscape-perspective, and critical uncertainties, across federal agencies.
Douglas J. Bruggeman is an ecological economist, consultant and writer based in Asheville, North Carolina.