Defining and Evaluating the Umbrella Species Concept for Conserving and Restoring Landscape Connectivity

Conserving or restoring landscape connectivity between patches of breeding habitat is a common strategy to protect threatened species from habitat fragmentation. By managing connectivity for some species, usually charismatic vertebrates, it is often assumed that these species will serve as conservation umbrellas for other species. We tested this assumption by developing a quantitative method to measure overlap in dispersal habitat of 3 threatened species—a bird (the umbrella), a butterfly, and a frog—inhabiting the same fragmented landscape. Dispersal habitat was determined with Circuitscape, which was parameterized with movement data collected for each species. Despite differences in natural history and breeding habitat, we found substantial overlap in the spatial distributions of areas important for dispersal of this suite of taxa. However, the intuitive umbrella species (the bird) did not have the highest overlap with other species in terms of the areas that supported connectivity. Nevertheless, we contend that when there are no irreconcilable differences between the dispersal habitats of species that cohabitate on the landscape, managing for umbrella species can help conserve or restore connectivity simultaneously for multiple threatened species with different habitat requirements. Definición y Evaluación del Concepto de Especie Paraguas para Conservar y Restaurar la Conectividad de Paisajes     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low‐elevation wetlands or mid‐elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy—herbaceous alpine ecotones—were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. Patrones Espaciales del Éxito Reproductivo de Osos Pardos, Derivados de Modelos Jerárquicos Multi‐Estado     

Estimating abundance without recaptures of marked pallid sturgeon in the Mississippi River

Abundance estimates are essential for assessing the viability of populations and the risks posed by alternative management actions. An effort to estimate abundance via a repeated mark‐recapture experiment may fail to recapture marked individuals. We devised a method for obtaining lower bounds on abundance in the absence of recaptures for both panmictic and spatially structured populations. The method assumes few enough recaptures were expected to be missed by random chance. The upper Bayesian credible limit on expected recaptures allows probabilistic statements about the minimum number of individuals present in the population. We applied this method to data from a 12‐year survey of pallid sturgeon (Scaphirhynchus albus) in the lower and middle Mississippi River (U.S.A.). None of the 241 individuals marked was recaptured in the survey. After accounting for survival and movement, our model‐averaged estimate of the total abundance of pallid sturgeon ≥3 years old in the study area had a 1%, 5%, or 25% chance of being <4,600, 7,000, or 15,000, respectively. When we assumed fish were distributed in proportion to survey catch per unit effort, the farthest downstream reach in the survey hosted at least 4.5–15 fish per river kilometer (rkm), whereas the remainder of the reaches in the lower and middle Mississippi River hosted at least 2.6–8.5 fish/rkm for all model variations examined. The lower Mississippi River had an average density of pallid sturgeon ≥3 years old of at least 3.0–9.8 fish/rkm. The choice of Bayesian prior was the largest source of uncertainty we considered but did not alter the order of magnitude of lower bounds. Nil‐recapture estimates of abundance are highly uncertain and require careful communication but can deliver insights from experiments that might otherwise be considered a failure.     

State of research on the automation of HAZOP studies

For more than 30 years, multiple research groups have worked on the automation of hazard and operability (HAZOP) studies, or more specifically on the hazard identification process. So far, very few of these approaches have been used in the chemical process industry. Automatic hazard identification is a knowledge-intensive process that demands high standards with regard to the way in which knowledge is stored and made available. There are various suitable approaches to the qualitative modeling of processes and plants, which are the foundation for reasoning systems that are used for the identification of hazards. Additionally, there are quantitative methods that are based on process simulations and can be used to identify potential hazards. The investigation of the state of research demonstrates that there are sophisticated technologies for automated systems that include powerful reasoning techniques. The benefits and shortcomings of existing technologies are discussed with regard to their industrial applicability. Often, the quality of the necessary specific and generic knowledge is not sufficient to detect potential hazardous events and operational malfunctions. Computer-aided HAZOP systems should be integrated with computer-aided design- or process simulation software using common data models based on the digital representation of the process plant. In order to be used by HAZOP practitioners automated systems need to be comprehensive, serve as specialized decision support systems, and be tested and evaluated using round robin tests.     

Population viability and harvest sustainability for Madagascar lemurs

Subsistence hunting presents a conservation challenge by which biodiversity preservation must be balanced with safeguarding of human livelihoods. Globally, subsistence hunting threatens primate populations, including Madagascar's endemic lemurs. We used population viability analysis to assess the sustainability of lemur hunting in Makira Natural Park, Madagascar. We identified trends in seasonal hunting of 11 Makira lemur species from household interview data, estimated local lemur densities in populations adjacent to focal villages via transect surveys, and quantified extinction vulnerability for these populations based on species-specific demographic parameters and empirically derived hunting rates. We compared stage-based Lefkovitch with periodic Leslie matrices to evaluate the impact of regional dispersal on persistence trajectories and explored the consequences of perturbations to the timing of peak hunting relative to the lemur birth pulse, under assumptions of density-dependent reproductive compensation. Lemur hunting peaked during the fruit-abundant wet season (March–June). Estimated local lemur densities were roughly inverse to body size across our study area. Life-history modeling indicated that hunting most severely threatened the species with the largest bodies (i.e., Hapalemur occidentalis, Avahi laniger, Daubentonia madagascariensis, and Indri indi), characterized by late-age reproductive onsets and long interbirth intervals. In model simulations, lemur dispersal within a regional metapopulation buffered extinction threats when a majority of local sites supported growth rates above the replacement level but drove regional extirpations when most local sites were overharvested. Hunt simulations were most detrimental when timed to overlap lemur births (a reality for D. madagascariensis and I. indri). In sum, Makira lemurs were overharvested. Regional extirpations, which may contribute to broad-scale extinctions, will be likely if current hunting rates persist. Cessation of anthropogenic lemur harvest is a conservation priority, and development programs are needed to help communities switch from wildlife consumption to domestic protein alternatives.     

Freshwater fish diversity hotspots for conservation priorities in the Amazon Basin

Conserving freshwater habitats and their biodiversity in the Amazon Basin is a growing challenge in the face of rapid anthropogenic changes. We used the most comprehensive fish-occurrence database available (2355 valid species; 21,248 sampling points) and 3 ecological criteria (irreplaceability, representativeness, and vulnerability) to identify biodiversity hotspots based on 6 conservation templates (3 proactive, 1 reactive, 1 representative, and 1 balanced) to provide a set of alternative planning solutions for freshwater fish protection in the Amazon Basin. We identified empirically for each template the 17% of sub-basins that should be conserved and performed a prioritization analysis by identifying current and future (2050) threats (i.e., degree of deforestation and habitat fragmentation by dams). Two of our 3 proactive templates had around 65% of their surface covered by protected areas; high levels of irreplaceability (60% of endemics) and representativeness (71% of the Amazonian fish fauna); and low current and future vulnerability. These 2 templates, then, seemed more robust for conservation prioritization. The future of the selected sub-basins in these 2 proactive templates is not immediately threatened by human activities, and these sub-basins host the largest part of Amazonian biodiversity. They could easily be conserved if no additional threats occur between now and 2050.     

Cost‐effectiveness of conservation payment schemes for species with different range sizes

Payments to compensate landowners for carrying out costly land‐use measures that benefit endangered biodiversity have become an important policy instrument. When designing such payments, it is important to take into account that spatially connected habitats are more valuable for many species than isolated ones. One way to incentivize provision of connected habitats is to offer landowners an agglomeration bonus, that is, a bonus on top of payments they are receiving to conserve land if the land is spatially connected. Researchers have compared the cost‐effectiveness of the agglomeration bonus with 2 alternatives: an all‐or‐nothing, agglomeration payment, where landowners receive a payment only if the conserved land parcels have a certain level of spatial connectivity, and a spatially homogeneous payment, where landowners receive a payment for conserved land parcels irrespective of their location. Their results show the agglomeration bonus is rarely the most cost‐effective option, and when it is, it is only slightly better than one of the alternatives. This suggests that the agglomeration bonus should not be given priority as a policy design option. However, this finding is based on consideration of only 1 species. We examined whether the same applied to 2 species, one for which the homogeneous payment is best and the other for which the agglomeration payment is most cost‐effective. We modified a published conceptual model so that we were able to assess the cost‐effectiveness of payment schemes for 2 species and applied it to a grassland bird and a grassland butterfly in Germany that require the same habitat but have different spatial‐connectivity needs. When conserving both species, the agglomeration bonus was more cost‐effective than the agglomeration and the homogeneous payment; thus, we showed that as a policy the agglomeration bonus is a useful conservation‐payment option.     

平原河网地区非点源污染风险差异化分区防控研究

土地利用优化和空间防控策略对非点源污染风险控制及水环境质量的改善具有重要意义。本文以太湖流域典型平原河网地区-上海市青浦区为研究对象,将灰色线性规划模型与最小累积阻力模型相结合,以控制非点源污染风险和增加经济效益、生态效益为目标,进行土地利用结构优化与空间分区防控研究,在空间上划设了水资源保育区、水资源重点防护区、非点源污染一般阻控区、非点源污染中等阻控区及非点源污染重点阻控区,并针对不同分区提出具有针对性的防控措施。与2012年相比,预测2020年优化防控方案下,可减少总氮、总磷的输出10.96%和41.33%。由此表明,优化土地利用结构和构建空间差异化防控机制是有效调控非点源污染风险,实现区域可持续土地利用,促进经济发展和保证生态环境安全的有效途径。