Evaluating the effectiveness of conservation and development investments in reducing deforestation and fires in Ankeniheny-Zahemena Corridor, Madagascar.

Forest conservation and REDD+ projects invest millions of dollars each year to reduce local communities' dependence on forests and prevent forest loss and degradation. However, to date, there is limited evidence on whether these investments are effective at delivering conservation outcomes. We explored the relationships between 600+ small-scale conservation and development investments that occurred from 2007 to 2014 and conservation outcomes (deforestation rates and fire detections) within Ankeniheny-Zahamena Corridor in Madagascar using linear fixed effects panel regressions. We derived annual changes in forest cover and fires from satellite remote sensing. We found a statistically significant correlation between presence of any investment and reduced deforestation rates in 2010 and 2011 -years with accelerated deforestation elsewhere in the study area. This result indicated investments abated deforestation rates during times of political instability and lack of governance following a 2009 coup in Madagascar. We also found a statistically significant relationship between presence of any investment and reduced fire detections in the study area, suggesting investments had an impact on reducing burning of forest for agriculture. For both outcomes (i.e., deforestation rates and fire detections), we found that more dollars invested led to greater conservation outcomes (i.e. fewer fires or less deforestation), particularly when funding was sustained for one to two years. Our findings suggest that conservation and development investments can reduce deforestation and fire incidence, but also highlight the many challenges and complexities in assessing relationships between investments and conservation outcomes in a dynamic landscape and a volatile political context.

Ten ways remote sensing can contribute to conservation.

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?

A satellite model of forest flammability.

We describe a model of forest flammability, based on daily satellite observations, for national to regional applications. The model defines forest flammability as the percent moisture content of fuel, in the form of litter of varying sizes on the forest floor. The model uses formulas from the US Forest Service that describe moisture exchange between fuel and the surrounding air and precipitation. The model is driven by estimates of temperature, humidity, and precipitation from the moderate resolution imaging spectrometer and tropical rainfall measuring mission multi-satellite precipitation analysis. We provide model results for the southern Amazon and northern Chaco regions. We evaluate the model in a tropical forest-to-woodland gradient in lowland Bolivia. Results from the model are significantly correlated with those from the same model driven by field climate measurements. This model can be run in a near real-time mode, can be applied to other regions, and can be a cost-effective input to national fire management programs.

Globally downscaled climate projections for assessing the conservation impacts of climate change.

Assessing the potential impacts of 21st-century climate change on species distributions and ecological processes requires climate scenarios with sufficient spatial resolution to represent the varying effects of climate change across heterogeneous physical, biological, and cultural landscapes. Unfortunately, the native resolutions of global climate models (usually approximately 2 degrees x 2 degrees or coarser) are inadequate for modeling future changes in, e.g., biodiversity, species distributions, crop yields, and water resources. Also, 21st-century climate projections must be debiased prior to use, i.e., corrected for systematic offsets between modeled representations and observations of present climates. We have downscaled future temperature and precipitation projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model data set to 10-minute resolution and debiased these simulations using the change-factor approach and observational data from the Climatic Research Unit (CRU). These downscaled data sets are available online and include monthly mean temperatures and precipitation for 2041-2060 and 2081-2100, for 24 climate models and the A1B, A2, and B1 emission scenarios. This paper describes the downscaling method and compares the downscaled and native-resolution simulations. Sharp differences between the original and downscaled data sets are apparent at regional to continental scales, particularly for temperature in mountainous areas and in areas with substantial differences between observed and simulated 20th-century climatologies. Although these data sets in principle could be downscaled further, a key practical limitation is the density of observational networks, particularly for precipitation-related variables in tropical mountainous regions. These downscaled data sets can be used for a variety of climate-impact assessments, including assessments of 21st-century climate-change impacts on biodiversity and species distributions.