The Effect of Carbon Credits on Savanna Land Management and Priorities for Biodiversity Conservation

September 26, 2011 Leave a Comment

Douglass, L. L., H. P. Possingham, J. Carwardine, C. J. Klein, S. H. Roxburgh, J. Russell-Smith, and K. A. Wilson. 2011. The Effect of Carbon Credits on Savanna Land Management and Priorities for Biodiversity Conservation. PLoS ONE 6:e23843. doi:10.1371/journal.pone.0023843

Abstract

Carbon finance offers the potential to change land management and conservation planning priorities. We develop a novel approach to planning for improved land management to conserve biodiversity while utilizing potential revenue from carbon biosequestration. We apply our approach in northern Australia’s tropical savanna, a region of global significance for biodiversity and carbon storage, both of which are threatened by current fire and grazing regimes. Our approach aims to identify priority locations for protecting species and vegetation communities by retaining existing vegetation and managing fire and grazing regimes at a minimum cost. We explore the impact of accounting for potential carbon revenue (using a carbon price of US$14 per tonne of carbon dioxide equivalent) on priority areas for conservation and the impact of explicitly protecting carbon stocks in addition to biodiversity. Our results show that improved management can potentially raise approximately US$5 per hectare per year in carbon revenue and prevent the release of 1–2 billion tonnes of carbon dioxide equivalent over approximately 90 years. This revenue could be used to reduce the costs of improved land management by three quarters or double the number of biodiversity targets achieved and meet carbon storage targets for the same cost. These results are based on generalised cost and carbon data; more comprehensive applications will rely on fine scale, site-specific data and a supportive policy environment. Our research illustrates that the duel objective of conserving biodiversity and reducing the release of greenhouse gases offers important opportunities for cost-effective land management investments.

A comparison of the difference in selection frequency, a measure of investment priority, between scenarios 1 and 2.

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Engage the hodgepodge: management factors are essential when prioritizing areas for restoration and conservation action

September 26, 2011 Leave a Comment

Knight, A. T., S. Sarkar, R. J. Smith, N. Strange, and K. A. Wilson. 2011. Engage the hodgepodge: management factors are essential when prioritizing areas for restoration and conservation action. Diversity and Distributions.  DOI: 10.1111/j.1472-4642.2011.00789.x (online early view)

Abstract

Restoration and conservation initiatives, such as the eradication of invasive alien plants, should be guided by scientific evidence. Typically, ecological data alone is used to inform the decision-making of these initiatives. Recent advances in the mapping of conservation opportunity include a diverse range of scientifically-identified factors that determine the feasibility and likely effectiveness of conservation initiatives, and include, for example, data on the willingness and capacity of land managers to be effectively involved. Social research techniques such as interview surveys, phenomenology, and social network analysis are important approaches for securing useful human and social data. These approaches are yet to be widely adopted in restoration initiatives, but could be usefully applied to improve the effective implementation of these initiatives. Restoration and conservation planners will deliver spatial prioritisations which provide more effective and cost-efficient decision-making if they include not simply ecological data, but also data on economic, human, management, social and vulnerability factors that determine implementation effectiveness.

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Prioritizing conservation investments for mammal species globally

August 17, 2011 Leave a Comment

Kerrie A. Wilson, Megan C. Evans, Moreno Di Marco, David C. Green, Luigi Boitani, Hugh P. Possingham, Federica Chiozza and Carlo Rondinini

Prioritizing conservation investments for mammal species globally. Philosophical Transactions of the Royal Society B: Biological Sciences 366:2670-2680. doi:10.1098/rstb.2011.0108

Abstract

We need to set priorities for conservation because we cannot do everything, everywhere, at the same time. We determined priority areas for investment in threat abatement actions, in both a cost-effective and spatially and temporally explicit way, for the threatened mammals of the world. Our analysis presents the first fine-resolution prioritization analysis for mammals at a global scale that accounts for the risk of habitat loss, the actions required to abate this risk, the costs of these actions and the likelihood of investment success. We evaluated the likelihood of success of investments using information on the past frequency and duration of legislative effectiveness at a country scale. The establishment of new protected areas was the action receiving the greatest investment, while restoration was never chosen. The resolution of the analysis and the incorporation of likelihood of success made little difference to this result, but affected the spatial location of these investments.

Figure 1. Spatial distribution of conservation funds through time at (a) 5, (b) 10, (c) 15 and (d) 20 years for all conservation actions, and (e) the average change in land use through time. Restoration received no investment after 20 years. Black solid line, protected areas; grey line, reduced impact logging; black dashed line, forestry; black dotted line, unallocated; grey dashed-dotted line, agriculture.

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Managing for change: wetland transitions under sea-level rise and outcomes for threatened species

July 19, 2011 Leave a Comment

Lochran W. Traill, Karin Perhans, Catherine E. Lovelock, Ana Prohaska, Steve McFallan, Jonathan R. Rhodes, Kerrie A. Wilson

Managing for change: wetland transitions under sea-level rise and outcomes for threatened species.  Diversity and Distributions. DOI: 10.1111/j.1472-4642.2011.00807.x

Abstract

Aim  Global sea-level rise (SLR) could be as much as 1.8 metres by 2100, which will impact coastal wetland communities and threatened species. We evaluated the likely outcomes of SLR for wetland communities using a process-based simulation model and coupled this with a metapopulation model for a threatened native rodent (Xeromys myoides). Furthermore, we tested the amplified impacts of SLR, urban growth and introduced predators on X. myoides persistence.

Location  South-east Queensland, Australia.

Methods  We adapted the Sea Level Affects Marshes Model to subtropical Australia. We used LiDAR elevation data, field data to parameterize surface accretion and shallow subsidence, and local knowledge to configure wetland transitions. SLR was simulated based on the IPCC B1 and A1FI scenarios, as well as the maximal limit of 1.8 m by 2100. Further, we coupled our demographic model to projected shifts in wetland habitat, and estimates of future wetland loss to urban expansion and feral cat (Felis catus) predation.

Results  Our models project a general decline in wetland communities under SLR, with a noted exception of mangroves. Under the A1FI scenario, SLR allows mangroves to migrate inland, with urban development acting as an obstruction in some areas. Mangrove expansion provides an unexpected benefit for dependent X. myoides populations, although the inclusion of predation and habitat loss due to urban development still suggests extirpation in c. 50 years.

Main conclusions  Through this case study, we illustrate the usefulness of process-based SLR models in understanding outcomes for wetland communities and dependent species. Our models will underscore decision-making in a dynamic system, with global applications for urban planning, conservation prioritization and wildlife management.

Figure 1.  Outline of study area, South-east Queensland (SEQ) Australia, indicated with black box inset. Broad figure shows SEQ for context, indicating elevation, main urban areas (white) and major river systems (grey). Study restricted to the insert area due to memory limitations imposed by the size of the LiDAR elevation data.

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