Predicting the conservation status of data‐deficient species

There is little appreciation of the level of extinction risk faced by one‐sixth of the over 65,000 species assessed by the International Union for Conservation of Nature. Determining the status of these data‐deficient (DD) species is essential to developing an accurate picture of global biodiversity and identifying potentially threatened DD species. To address this knowledge gap, we used predictive models incorporating species’ life history, geography, and threat information to predict the conservation status of DD terrestrial mammals. We constructed the models with 7 machine learning (ML) tools trained on species of known status. The resultant models showed very high species classification accuracy (up to 92%) and ability to correctly identify centers of threatened species richness. Applying the best model to DD species, we predicted 313 of 493 DD species (64%) to be at risk of extinction, which increases the estimated proportion of threatened terrestrial mammals from 22% to 27%. Regions predicted to contain large numbers of threatened DD species are already conservation priorities, but species in these areas show considerably higher levels of risk than previously recognized. We conclude that unless directly targeted for monitoring, species classified as DD are likely to go extinct without notice. Taking into account information on DD species may therefore help alleviate data gaps in biodiversity indicators and conserve poorly known biodiversity. Predección del Estado de Conservación de Especies con Deficiencia de Datos     

Identifying impediments to long‐distance mammal migrations

In much of the world, the persistence of long‐distance migrations by mammals is threatened by development. Even where human population density is relatively low, there are roads, fencing, and energy development that present barriers to animal movement. If we are to conserve species that rely on long‐distance migration, then it is critical that we identify existing migration impediments. To delineate stopover sites associated with anthropogenic development, we applied Brownian bridge movement models to high‐frequency locations of pronghorn (Antilocapra americana) in the Greater Yellowstone Ecosystem. We then used resource utilization functions to assess the threats to long‐distance migration of pronghorn that were due to fences and highways. Migrating pronghorn avoided dense developments of natural gas fields. Highways with relatively high volumes of traffic and woven‐wire sheep fence acted as complete barriers. At crossings with known migration bottlenecks, use of high?quality forage and shrub habitat by pronghorn as they approached the highway was lower than expected based on availability of those resources. In contrast, pronghorn consistently utilized high?quality forage close to the highway at crossings with no known migration bottlenecks. Our findings demonstrate the importance of minimizing development in migration corridors in the future and of mitigating existing pressure on migratory animals by removing barriers, reducing the development footprint, or installing crossing structures. Identificación de los Impedimentos para las Migraciones de Larga Distancia de Mamíferos     

A framework for evaluating the impact of the IUCN Red List of threatened species

The International Union for Conservation of Nature (IUCN) Red List of Threatened Species, a species extinction risk assessment tool, has been guiding conservation efforts for over 5 decades. It is widely assumed to have been instrumental in preventing species from moving closer to extinction and driving recoveries. However, the impact of the IUCN Red List in guiding conservation has not been evaluated. We conducted, transcribed, and coded interviews with experts who use the IUCN Red List across a range of sectors to understand how the list is used in conservation. We developed a theory of change to illustrate how and why change is expected to occur along causal pathways contributing to the long-term goal of the IUCN Red List and an evaluation framework with indicators for measuring the impact of the IUCN Red List in generating scientific knowledge, raising awareness among stakeholders, designating priority conservation sites, allocating funding and resources, influencing development of legislation and policy, and guiding targeted conservation action (key themes). Red-list assessments were the primary input leading to outputs (scientific knowledge, raised awareness), outcomes (better informed priority setting, access to funding and resource availability, improved legislation and policy), and impact (implemented conservation action leading to positive change) that have resulted in achievement of IUCN Red List goals. To explore feasibility of attributing the difference made by the IUCN Red List across themes, we studied increased scientific knowledge, raised awareness, access to funding and resource allocation, and increased conservation activity. The feasibility exploration showed increased scientific knowledge over time identified through positive trends in publications referring to the IUCN Red List in the literature; raised awareness of the list following high IUCN activity identified by peaks in online search activity; an increased proportion of conservation funding bodies requesting IUCN Red List status in the application process; and, based on interviews with Amphibian Specialist Group members, red-list assessments were essential in connecting relevant stakeholders and ensuring conservation action. Although we identified the IUCN Red List as a vital tool in global conservation efforts, it was challenging to measure specific impacts because of its ubiquitous nature. We are the first to identify the influence of the IUCN Red List on conservation.     

Application of multiple-population viability analysis to evaluate species recovery alternatives

Population viability analysis (PVA) is a powerful conservation tool, but it remains impractical for many species, particularly species with multiple, broadly distributed populations for which collecting suitable data can be challenging. A recently developed method of multiple-population viability analysis (MPVA), however, addresses many limitations of traditional PVA. We built on previous development of MPVA for Lahontan cutthroat trout (LCT) (Oncorhynchus clarkii henshawi), a species listed under the U.S. Endangered Species Act, that is distributed broadly across habitat fragments in the Great Basin (U.S.A.). We simulated potential management scenarios and assessed their effects on population sizes and extinction risks in 211 streams, where LCT exist or may be reintroduced. Conservation populations (those managed for recovery) tended to have lower extinction risks than nonconservation populations (mean = 19.8% vs. 52.7%), but not always. Active management or reprioritization may be warranted in some cases. Eliminating non-native trout had a strong positive effect on overall carrying capacities for LCT populations but often did not translate into lower extinction risks unless simulations also reduced associated stochasticity (to the mean for populations without non-native trout). Sixty fish or 5–10 fish/km was the minimum reintroduction number and density, respectively, that provided near-maximum reintroduction success. This modeling framework provided crucial insights and empirical justification for conservation planning and specific adaptive management actions for this threatened species. More broadly, MPVA is applicable to a wide range of species exhibiting geographic rarity and limited availability of abundance data and greatly extends the potential use of empirical PVA for conservation assessment and planning.     

Using average autonomy to test whether behavioral syndromes constrain evolution

Genetic correlations between behaviors underlying a behavioral syndrome may constrain the capacity of a population to respond to selection on these behaviors. Average autonomy quantifies the extent in which estimated genetic (co)variances constrain the rate of evolutionary change of behavioral traits forming a syndrome when these traits are under selections in all possible directions of multivariate trait-space. However, it is not clear whether a calculated average autonomy value of an observed syndrome constitutes a significant evolutionary constraint or not. I here outline an approach for testing evolutionary constraint in a syndrome, which is based on comparing the observed genetic (co)variance structure to the one where the genetic covariances are assumed to be zero and taking onboard the uncertainty in the (co)variances between behaviors into the calculations of average autonomy. The approach can be implemented in the context of parametric bootstrap or Bayesian statistics, and I provide a worked example of the latter. I further highlight that when genetic (co)variances are unattainable, the between-individual (co)variances act as an interesting proxy, which is within reach for many behavioral studies. I provide R code for all calculations.     

Quantifying the importance of patch-specific changes in habitat to metapopulation viability of an endangered songbird

A growing number of programs seek to facilitate species conservation using incentive-based mechanisms. Recently, a market-based incentive program for the federally endangered Golden-cheeked Warbler (Dendroica chrysoparia) was implemented on a trial basis at Fort Hood, an Army training post in Texas, USA. Under this program, recovery credits accumulated by Fort Hood through contracts with private landowners are used to offset unintentional loss of breeding habitat of Golden-cheeked Warblers within the installation. Critical to successful implementation of such programs is the ability to value, in terms of changes to overall species viability, both habitat loss and habitat restoration or protection. In this study, we sought to answer two fundamental questions: Given the same amount of change in breeding habitat, does the change in some patches have a greater effect on metapopulation persistence than others? And if so, can characteristics of a patch (e.g., size or spatial location) be used to predict how the metapopulation will respond to these changes? To answer these questions, we describe an approach for using sensitivity analysis of a metapopulation projection model to predict how changes to specific habitat patches would affect species viability. We used a stochastic, discrete-time projection model based on stage-specific estimates of survival and fecundity, as well as various assumptions about dispersal among populations. To assess a particular patch's leverage, we quantified how much metapopulation viability was expected to change in response to changing the size of that patch. We then related original patch size and distance from the largest patch to each patch's leverage to determine if general patch characteristics could be used to develop guidelines for valuing changes to patches within a metapopulation. We found that both the characteristic that best predicted patch leverage and the magnitude of the relationship changed under different model scenarios. Thus, we were unable to find a consistent set of relationships, and therefore we emphasize the dangers in relying on general guidelines to assess patch value. Instead, we provide an approach that can be used to quantitatively evaluate patch value and identify critical needs for future research.     

Effect of fluid concentration in titanium machining with an atomization-based cutting fluid (ACF) spray system

The aim of this work is to investigate the effect of metal-working fluid (MWF) concentration on the machining responses including tool life and wear, cutting force, friction coefficient, chip morphology, and surface roughness during the machining of titanium with the use of the ACF spray system. Five different concentrations from 5 to 15% of a water-soluble metalworking fluid (MWF) were applied during turning of a titanium alloy, Ti–6Al–4V. The thermo-physical properties such as viscosity, surface tension and thermal conductivity of these concentrations were also measured. The test results demonstrate that the tool life first extends with the increase in MWF concentration and then drops with further increase. At low concentration (e.g., 5%), a lack of the lubrication effect causes to increase in a higher friction at the tool–chip interface resulting in severe chipping and tool nose/flank wear within a short machining time. On the other hand, at high concentration, the cooling effect is less. This increases cutting temperature and a faster thermal softening/chipping/notching of the tool material and higher friction at the tool–chip–workpiece interaction zones resulting in early tool failure. A good balance between the cooling and the lubrication effects seems to be found at the 10% MWF concentration as it offers the best machining performance. However, machining with flood coolant is observed to perform the best in the range of 5–7%.     

Comparing Contaminant Removal Costs for Aquifer Recharge with Wastewater with Water Supply Benefits

The use of waters of impaired quality has been suggested as a means to expand available water resources supply for water‐limited communities. An ongoing concern is the safety of supplies that use wastewater because of the potential for introduction of emerging contaminants such as pharmaceuticals into drinking water supplies. Prior research into contaminants of emerging concerns (CECs) have included a variety of methods, but the only consistent removal is with reverse osmosis (RO) membranes, ultraviolet light (UV), and advanced oxidation processes (AOP). However, few of these prior studies have measurable quantities of these contaminants in the influent wastewater, so determining actual removal percentages is difficult. This project was designed to evaluate the removal of CECs to verify that a 3‐log removal of common constituents was realized. Spike testing was used to compare to prior research and to evaluate whether the project costs were competitive with other forms of reuse or other water supplies. The combination of RO/UV/AOP was effective at obtaining a 3‐log removal of CECs, but the RO and UV/AOP processes alone were not capable of removing all substances. However, despite the extensive treatment, the proposed process was both competitive cost‐wise and met the water quality goals.     

The Relationship Between Shift Work Schedules and Spillover in a Sample of Nurses

The aim of the present study was to estimate spillover effects between the work and the family sphere in a sample of nurses (N = 2058). Hierarchical regression analyses investigated whether shift work schedules were associated with negative or positive spillover, both from family to work and vice versa, controlling for demographic factors, job demands and decision latitude. With daytime work as a reference group, all types of shift work (day and evening shift, night shift only and rotating 3 shift) were associated with higher negative work-to-family spillover. Night work was associated with significantly less negative family-to-work spillover. None of the different shift work schedules were related to any type of positive spillover. The results indicate that working outside of daytime hours is less compatible with workers’ family lives, compared to working ordinary day shifts. On the other hand, working night shifts only was associated with reduced negative family-to-work spillover.