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?     

Strategies for Testing the “Irritation-signaling” Model for Chronic Lung Effects of Fine Acid Particles

The “irritation signaling” model proposed that a long term contribution to chronic bronchitis might result from the repeated delivery of “signals” resulting from temporary localized acidification of the bronchial epithelium by the action of Individual particles. This led to a prediction that the effectiveness of particles in inducing changes in mucus secreting cell numbers/types should depend on the number of particles deposited that contained a particular amount of acid—implying that particles below a certain size cutoff (and therefore lacking a minimum amount of acid) should be ineffective; and that particle potency per unit weight should be greatest at the cutoff and decline strongly above the cutoff.

Since the development of this hypothesis both epidemiologlcal observations and some experimental studies have tended to reinforce the notion that acid particles can make a contribution to relatively long lasting bronchitic-like changes, and enhance the desirability of more direct testing of the model. In this paper we develop a general theoretical framework for the contributions of environmental agents to chronic obstructive lung disease, and a series of alternative hypotheses against which the predictions of the “Irritant signaling” model can be compared. Based on this, we suggest a research program that could be used to further develop and test the model and reasonable alternatives.     

Examining Fragmentation and Loss of Primary Forest in the Southern Bahian Atlantic Forest of Brazil with Radar Imagery

Abstract: The Atlantic rainforest of southern Bahia is one of the last remnants of the lowland forest of eastern Brazil that once covered the entire coastal area from Rio Grande do Norte to Rio Grande do Sul ( lat 8°–28° S) and has been deforested to a small fraction of its original cover (1–12%). All recent vegetation surveys have been based on optical satellite data, which is hampered by cloud cover and by southern Bahia's intricate mix of forest patches with other tree crops, especially cocoa. We describe the application of radar remote-sensing data to distinguish forest patches from cocoa planted in the shade of natural-forest trees. Radar, unlike optical sensors, is not obstructed by cloud cover and can acquire information about forest structure by penetrating into the vegetation canopy. The vegetation map generated from radar data clearly separates forest patches based on the degree of structural disturbance such as the density of shaded trees, the openness of the canopy, and the density of the monodominant Erythyrina shaded trees. The structural classification based on the radar data, and shown on the map, can help researchers assess the degree of fragmentation of the original Atlantic coastal forest and delineate areas of less disturbance with higher potential for conservation of biodiversity. This information can then be applied to conservation planning, especially the design and monitoring of nature reserves and the modeling of biological corridors.