Dataset Information

The Value of Learning about Natural History in Biodiversity Markets.

ABSTRACT: Markets for biodiversity have generated much controversy because of the often unstated and untested assumptions included in transactions rules. Simple trading rules are favored to reduce transaction costs, but others have argued that this leads to markets that favor development and erode biodiversity. Here, I describe how embracing complexity and uncertainty within a tradable credit system for the Red-cockaded Woodpecker (Picoides borealis) creates opportunities to achieve financial and conservation goals simultaneously. Reversing the effects of habitat fragmentation is one of the main reasons for developing markets. I include uncertainty in habitat fragmentation effects by evaluating market transactions using five alternative dispersal models that were able to approximate observed patterns of occupancy and movement. Further, because dispersal habitat is often not included in market transactions, I contrast how changes in breeding versus dispersal habitat affect credit values. I use an individually-based, spatially-explicit population model for the Red-cockaded Woodpecker (Picoides borealis) to predict spatial- and temporal- influences of landscape change on species occurrence and genetic diversity. Results indicated that the probability of no net loss of abundance and genetic diversity responded differently to the transient dynamics in breeding and dispersal habitat. Trades that do not violate the abundance cap may simultaneously violate the cap for the erosion of genetic diversity. To highlight how economic incentives may help reduce uncertainty, I demonstrate tradeoffs between the value of tradable credits and the value of information needed to predict the influence of habitat trades on population viability. For the trade with the greatest uncertainty regarding the change in habitat fragmentation, I estimate that the value of using 13-years of data to reduce uncertainty in dispersal behaviors is $6.2 million. Future guidance for biodiversity markets should at least encourage the use of spatially- and temporally-explicit techniques that include population genetic estimates and the influence of uncertainty.

SUBMITTER: Bruggeman DJ

PROVIDER: S-EPMC4684417 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The Value of Learning about Natural History in Biodiversity Markets.

Bruggeman Douglas J DJ

PloS one 20151216 12

Markets for biodiversity have generated much controversy because of the often unstated and untested assumptions included in transactions rules. Simple trading rules are favored to reduce transaction costs, but others have argued that this leads to markets that favor development and erode biodiversity. Here, I describe how embracing complexity and uncertainty within a tradable credit system for the Red-cockaded Woodpecker (Picoides borealis) creates opportunities to achieve financial and conserva ...[more]

PMID: 26675488

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Project description:BackgroundWith the increase in human population, and the growing realisation of the importance of urban biodiversity for human wellbeing, the ability to predict biodiversity loss or gain as a result of land use change within urban settings is important. Most models that link biodiversity and land use are at too coarse a scale for informing decisions, especially those related to planning applications. Using the grounds of the Natural History Museum, London, we show how methods used in global models can be applied to smaller spatial scales to inform urban planning.MethodsData were extracted from relevant primary literature where species richness had been recorded in more than one habitat type within an urban setting. As within-sample species richness will increase with habitat area, species richness estimates were also converted to species density using theory based on the species-area relationship. Mixed-effects models were used to model the impact on species richness and species density of different habitat types, and to estimate these metrics in the current grounds and under proposed plans for redevelopment. We compared effects of three assumptions on how within-sample diversity scales with habitat area as a sensitivity analysis. A pre-existing database recording plants within the grounds was also used to estimate changes in species composition across different habitats.ResultsAnalysis estimated that the proposed plans would result in an increase of average biodiversity of between 11.2% (when species density was modelled) and 14.1% (when within-sample species richness was modelled). Plant community composition was relatively similar between the habitats currently within the grounds.DiscussionThe proposed plans for change in the NHM grounds are estimated to result in a net gain in average biodiversity, through increased number and extent of high-diversity habitats. In future, our method could be improved by incorporating purposefully collected ecological survey data (if resources permit) and by expanding the data sufficiently to allow modelling of the temporal dynamics of biodiversity change after habitat disturbance and creation. Even in its current form, the method produces transparent quantitative estimates, grounded in ecological data and theory, which can be used to inform relatively small scale planning decisions.

Dataset Information

The Value of Learning about Natural History in Biodiversity Markets.

Publications

The Value of Learning about Natural History in Biodiversity Markets.

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