Quantitative Developments

Quantitative Developments - ARMI Papers & Reports

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Authors: DiRenzo GV, Grant EHC | Outlet: Biological Conservation
One of the leading causes of global amphibian decline is emerging infectious disease. We summarize the disease ecology of four major emerging amphibian infectious agents: chytrids, ranaviruses, trematodes, and Perkinsea. We focus on recently developed quantitative advances that build on well-established ecological theories and aid in studying epizootic and enzootic disease dynamics. For example, we identify ecological and evolutionary selective forces that determine disease outcomes and transmission pathways by borrowing ideas from population and community ecology theory. We outline three topics of general interest in disease ecology: (i) the relationship between biodiversity and disease risk, (ii) individual, species, or environmental transmission heterogeneity, and (iii) pathogen coinfections. Finally, we identify specific knowledge gaps impeding the success of conservation-related decisions for disease mitigation and the future of amphibian conservation success.
Papers & Reports A three-pipe problem: dealing with complexity to halt amphibian declines
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Authors: Converse S, Grant EHC | Outlet: Biological Conservation
Natural resource managers are increasingly faced with threats to managed ecosystems that are largely outside of their control. Examples include land development, climate change, invasive species, and emerging infectious diseases. All of these are characterized by large uncertainties in timing, magnitude, and effects on species. In many cases, the conservation of species will only be possible through concerted action on the limited elements of the system that managers can control. However, before an action is taken, a manager must decide how to act, which is ? if done well ? not easy. In addition to dealing with uncertainty, managers must balance multiple potentially competing objectives, often in cases when the management actions available to them are limited. Guidance in making these types of challenging decisions can be found in the practice known as decision analysis. We demonstrate how using a decision-analytic approach to frame decisions can help identify and address impediments to improved conservation decision making. We demonstrate the application of decision analysis to two high-elevation amphibian species. An inadequate focus on the decision-making process, and an assumption that scientific information is adequate to solve conservation problems, must be overcome to advance the conservation of amphibians and other highly threatened taxa.
Papers & Reports Using Full and Partial Unmixing Algorithms to Estimate the Inundation Extent of Small, Isolated Stock Ponds in an Arid Landscape
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Authors: Jarchow CJ, Sigafus BH, Muths E, Hossack BR | Date: 2019-08 | Outlet: Wetlands
Many natural wetlands around the world have disappeared or been replaced, resulting in the dependence of many wildlife species on small, artificial earthen stock ponds. These ponds provide critical wildlife habitat, such that the accurate detection of water and assessment of inundation extent is required. We applied a full (linear spectral mixture analysis; LSMA) and partial (matched filtering; MF) spectral unmixing algorithm to a 2007 Landsat 5 and a 2014 Landsat 8 satellite image to determine the ability of a time-intensive (i.e., more spectral input; LSMA) vs. a more efficient (less spectral input; MF) spectral unmixing approach to detect and estimate surface water area of stock ponds in southern Arizona, USA and northern Sonora, Mexico. Spearman rank correlations (rs) between modeled and actual inundation areas less than a single Landsat pixel (< 900 m2) were low for both techniques (rs range = 0.22 to 0.62), but improved for inundation areas > 900 m2 (rs range = 0.34 to 0.70). Our results demonstrate that the MF approach can model ranked inundation extent of known pond locations with results comparable to or better than LSMA, but further refinement is required for estimating absolute inundation areas and mapping wetlands < 1 Landsat pixel.
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