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?     

The difference conservation makes to extinction risk of the world's ungulates

Previous studies show that conservation actions have prevented extinctions, recovered populations, and reduced declining trends in global biodiversity. However, all studies to date have substantially underestimated the difference conservation action makes because they failed to account fully for what would have happened in the absence thereof. We undertook a scenario‐based thought experiment to better quantify the effect conservation actions have had on the extinction risk of the world's 235 recognized ungulate species. We did so by comparing species’ observed conservation status in 2008 with their estimated status under counterfactual scenarios in which conservation efforts ceased in 1996. We estimated that without conservation at least 148 species would have deteriorated by one International Union for Conservation of Nature (IUCN) Red List category, including 6 species that now would be listed as extinct or extinct in the wild. The overall decline in the conservation status of ungulates would have been nearly 8 times worse than observed. This trend would have been greater still if not for conservation on private lands. While some species have benefited from highly targeted interventions, such as reintroduction, most benefited collaterally from conservation such as habitat protection. We found that the difference conservation action makes to the conservation status of the world's ungulate species is likely to be higher than previously estimated. Increased, and sustained, investment could help achieve further improvements.     

Development and environmental application of a genus-specific quantitative PCR approach for Pseudo-nitzschia species

Quantitative polymerase chain reaction (qPCR) for the identification and quantification of microbes has become a common tool for the study of harmful algal blooms (HABs). We developed a qPCR method for the diatom genus Pseudo-nitzschia. Several species of this genus form toxic blooms through the production of the neurotoxin domoic acid (DA). Outbreaks of toxicity attributed to DA along the US west coast have caused sickness and death of marine mammals and seabirds through food web contamination. The method developed here quantifies Pseudo-nitzschia spp. at low abundances in natural samples, thereby, providing a method to improve our understanding of the environmental conditions leading to blooms of these species. This has been accomplished previously by techniques for identification and quantification that are slow and laborious compared to qPCR. The approach was successfully tested and validated using eight species of Pseudo-nitzschia and 33 non-target organisms and employed to follow local bloom dynamics.     

Alimentary niche partitioning in the Galapagos sea lion, Zalophus wollebaeki

Sea lions are generally considered opportunistic feeders. However, studies from different areas suggest their diet consists mostly of four to five types of prey. Previous studies in Galapagos sea lions have identified at least three feeding strategies for this species, suggesting diversification of their diet. Diet diversification is favored in organisms with relatively high trophic position and subject to high intra-specific and low inter-specific competition. Zalophus wollebaeki meet these criteria as the only pinniped on San Cristobal Island, where three sea lion rookeries are located within 11 km: a distance considerably shorter than their 41 km foraging range. To measure the degree of diet diversification, we used scats and stable isotope analyses. A total of 270 scat samples from lactating females and 142 fur samples from sea lion pups were collected during the breeding season 2006. The scat analysis identified distinct diets among rookeries, with minimal trophic overlap (Cλ = 0.19), a trophic level TL = 4.5 (secondary–tertiary carnivore), and trophic breadth of a specialist predator (B _i  = 0.37). The mean δ¹⁵N and δ¹³C values were 13.07 ± 0.52 and −16.34 ± 0.37, respectively. No significant difference was found in the δ¹⁵N values from the sea lion rookeries, but differences were found inter- and intra-population in δ¹³C values for pups from different groups (ANOVA P < 0.05). Our results indicate that diet diversification is present in the Galapagos sea lion and may play important role to the survival of the species in a habitat where pinniped populations are limited.     

Effects of temperature variation on TSD in turtle (C. picta) populations

We formulate a two-sex model of temperature-dependent sex determination (TSD) for a freshwater turtle (C. picta) population. The aim is to understand how environmental temperature variations and nest heat conduction properties affect the long term dynamics of the population. This is a key to understanding how global temperature changes may affect their survival. With stochastic inputs of ambient temperature and solar radiation, the model uses the heat equation to determine the temperature in the egg layer in the nest; in turn, this determines the sex ratio in the egg clutch using a variable degree-day model. Finally, a nonlinear Leslie type, stage-based, two-sex model, is used to determine the long term male and female populations. A two-sex model is required because of different development rates for males and females. The model is flexible enough to enable other researchers to examine the effects of temperature variation variations on other species with TSD, e.g., crocodilians, reptilians, as well as other turtle species. It can be adapted to study effects of nest location, soil type, rain events, different incubation periods, and density effects, for example, the dependence of the mating function on the ratio of males to females and each’s contribution to the sex of hatchlings. Modifications can be easily made to fit a specific life history traits. The model is a beginning step in understanding the long term, high fitness shown by many reptile species with TSD, and it may suggest to experimentalists what data may be relevant to these issues; it can also be useful to wildlife managers in developing strategies for intervention if needed. Among the principal findings are that temperature variability and detailed nest heat conduction properties may buffer projected negative effects on a population.     

A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters

An understanding of the causal mechanisms and processes that shape macroinvertebrate communities at a local scale has important implications for the management and conservation of freshwater biodiversity. Here we compare the performance of linear and non-linear statistics to explore diversity-environment relationships using data from 76 temporary and fluctuating ponds in two regions of southern England. We focus on aquatic beetle assemblages, which have been shown to be excellent surrogates of wider freshwater macroinvertebrate diversity. Ponds in the region contained a rich coleopteran fauna, totaling 68 species, which provided an excellent model system with which to compare the performance of two non-linear procedures (artificial neural networks—ANNs and generalised additive models—GAMs) and one more traditional linear approach (Multiple linear regression—MLR) to modelling diversity-environment relationships. Of all approaches employed, the best fit was obtained using an ANN model with only four input variables (conductivity, turbidity, magnesium concentration and depth). This model accounted for 82% of the observed variability in Shannon diversity index across ponds. In contrast, the best GAM and MLR models only explained 50% and 14% of this variation, respectively. Contribution profile analysis of conductivity, turbidity, magnesium concentration and depth, obtained from the best fit ANN through a hierarchical cluster analysis, allowed the identification of direct and proxy effects in relation to the environmental variables measured in this study. In each case, distinct clusters of ponds were identified in contribution profile analysis, suggesting that ponds across the two regions fall into a number of discrete groups, whose beetle faunas respond in subtly yet significantly different ways to key environmental variables. Aquatic coleopteran diversity in ponds in the two regions appears to be driven at a local scale by changes in relatively few physicochemical gradients, which are related to diversity in a clearly non-linear manner.