Considerations for assessing model averaging of regression coefficients

Predicting the odds of chronic wasting disease with Habitat Risk software

Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in captive cervids in Colorado, United States (US) in 1967, but has since spread into free-ranging white-tailed deer (Odocoileus virginianus) across the US and Canada as well as to Scandinavia and South Korea. In some areas, the disease is considered endemic in wild deer populations, and governmental wildlife agencies have employed epidemiological models to understand long-term environmental risk. However, continued rapid spread of CWD into new regions of the continent has underscored the need for extension of these models into broader tools applicable for wide use by wildlife agencies. Additionally, efforts to semi-automate models will facilitate access of technical scientific methods to broader users. We introduce software (Habitat Risk) designed to link a previously published epidemiological model with spatially referenced environmental and disease testing data to enable agency personnel to make up-to-date, localized, data-driven predictions regarding the odds of CWD detection in surrounding areas after an outbreak is discovered. Habitat Risk requires pre-processing publicly available environmental datasets and standardization of disease testing (surveillance) data, after which an autonomous computational workflow terminates in a user interface that displays an interactive map of disease risk. We demonstrated the use of the Habitat Risk software with surveillance data of white-tailed deer from Tennessee, USA.

Temperate species underfill their tropical thermal potentials on land

Understanding how temperature determines the distribution of life is necessary to assess species' sensitivities to contemporary climate change. Here, we test the importance of temperature in limiting the geographic ranges of ectotherms by comparing the temperatures and areas that species occupy to the temperatures and areas species could potentially occupy on the basis of their physiological thermal tolerances. We find that marine species across all latitudes and terrestrial species from the tropics occupy temperatures that closely match their thermal tolerances. However, terrestrial species from temperate and polar latitudes are absent from warm, thermally tolerable areas that they could potentially occupy beyond their equatorward range limits, indicating that extreme temperature is often not the factor limiting their distributions at lower latitudes. This matches predictions from the hypothesis that adaptation to cold environments that facilitates survival in temperate and polar regions is associated with a performance trade-off that reduces species' abilities to contend in the tropics, possibly due to biotic exclusion. Our findings predict more direct responses to climate warming of marine ranges and cool range edges of terrestrial species.

Insularity determines nestling sex ratio variation in Egyptian vulture populations

Variation in offspring sex ratio, particularly in birds, has been frequently studied over the last century, although seldom using long-term monitoring data. In raptors, the cost of raising males and females is not equal, and several variables have been found to have significant effects on sex ratio, including food availability, parental age, and hatching order. Sex ratio differences between island populations and their mainland counterparts have been poorly documented, despite broad scientific literature on the island syndrome reporting substantial differences in population demography and ecology. Here, we assessed individual and environmental factors potentially affecting the secondary sex ratio of the long-lived Egyptian vulture Neophron percnopterus. We used data collected from Spanish mainland and island populations over a ca. 30-year period (1995-2021) to assess the effects of insularity, parental age, breeding phenology, brood size, hatching order, type of breeding unit (pairs vs. trios), and spatial and temporal variability on offspring sex ratio. No sex bias was found at the population level, but two opposite trends were observed between mainland and island populations consistent with the island syndrome. Offspring sex ratio was nonsignificantly female-biased in mainland Spain (0.47, n = 1112) but significantly male-biased in the Canary Islands (0.55, n = 499), where a male-biased mortality among immatures could be compensating for offspring biases and maintaining a paired adult sex ratio. Temporal and spatial variation in food availability might also have some influence on sex ratio, although the difficulties in quantifying them preclude us from determining the magnitude of such influence. This study shows that insularity influences the offspring sex ratio of the Egyptian vulture through several processes that can affect island and mainland populations differentially. Our research contributes to improving our understanding of sex allocation theory by investigating whether sex ratio deviations from parity are possible as a response to changing environments comprised by multiple and complexly interrelated factors.

Avian influenza antibody prevalence increases with mercury contamination in wild waterfowl

Environmental contamination is widespread and can negatively impact wildlife health. Some contaminants, including heavy metals, have immunosuppressive effects, but prior studies have rarely measured contamination and disease simultaneously, which limits our understanding of how contaminants and pathogens interact to influence wildlife health. Here, we measured mercury concentrations, influenza infection, influenza antibodies and body condition in 749 individuals from 11 species of wild ducks overwintering in California. We found that the odds of prior influenza infection increased more than fivefold across the observed range of blood mercury concentrations, while accounting for species, age, sex and date. Influenza infection prevalence was also higher in species with higher average mercury concentrations. We detected no relationship between influenza infection and body fat content. This positive relationship between influenza prevalence and mercury concentrations in migratory waterfowl suggests that immunotoxic effects of mercury contamination could promote the spread of avian influenza along migratory flyways, especially if influenza has minimal effects on bird health and mobility. More generally, these results show that the effects of environmental contamination could extend beyond the geographical area of contamination itself by altering the prevalence of infectious diseases in highly mobile hosts.

Dancing to a different tune: changing reproductive seasonality in an introduced chital deer population

Male and female reproductive behaviour is typically synchronised. In species such as those in the family Cervidae, reproductive timing is often cued by photoperiod, although in females, it can be dependent on body condition. When a species is introduced to a novel environment, the environment changes, or responses of the sexes to such cues differ, asynchronous reproductive behaviour between males and females may occur. We investigated the seasonality of reproductive behaviour in introduced chital deer in northern Queensland by examining male antler phase in relation to female conception rates. We then analysed the influence of different variables likely to affect the timing of male and female reproductive physiology. The lowest percentage of chital in hard antler in any 1 month in this study was 35% (Fig. 1), but the average value was closer to 50%, thus there was a seasonal peak in antler phase linked with photoperiod. Females conceived at any time of year, but were strongly influenced by the amount of rainfall 3 months prior to conception. This resulted in varying conception peaks year-to-year that often did not correspond to the male’s peak in hard antler. In this system, a proportion of males and females were physiologically and behaviourally ready to mate at any time of the year. We predict that differences in the timing of the peaks between the males and females will lead to increased reproductive skew (variation in reproductive success among individual males). This pattern may select for different mating strategies or physiological mechanisms to increase reproductive success.Fig. 1

Determinants of Task-Based Exposures to Alpha-Diketones in Coffee Roasting and Packaging Facilities Using a Bayesian Model Averaging Approach

Coffee production workers can be exposed to inhalational hazards including alpha-diketones such as diacetyl and 2,3-pentanedione. Exposure to diacetyl is associated with the development of occupational lung disease, including obliterative bronchiolitis, a rare and irreversible lung disease. We aimed to identify determinants contributing to task-based exposures to diacetyl and 2,3-pentanedione at 17 U.S. coffee production facilities. We collected 606 personal short-term task-based samples including roasting (n = 189), grinding (n = 74), packaging (n = 203), quality control (QC, n = 44), flavoring (n = 15), and miscellaneous production/café tasks (n = 81), and analyzed for diacetyl and 2,3-pentanedione in accordance with the modified OSHA Method 1013/1016. We also collected instantaneous activity-based (n = 296) and source (n = 312) samples using evacuated canisters. Information on sample-level and process-level determinants relating to production scale, sources of alpha-diketones, and engineering controls was collected. Bayesian mixed-effect regression models accounting for censored data were fit for overall data (all tasks) and specific tasks. Notable determinants identified in univariate analyses were used to fit all plausible models in multiple regression analysis which were summarized using a Bayesian model averaging method. Grinding, flavoring, packaging, and production tasks with ground coffee were associated with the highest short-term and instantaneous-activity exposures for both analytes. Highest instantaneous-sources of diacetyl and 2,3-pentanedione included ground coffee, flavored coffee, liquid flavorings, and off-gassing coffee bins or packages. Determinants contributing to higher exposures to both analytes in all task models included sum of all open storage sources and average percent of coffee production as ground coffee. Additionally, flavoring ground coffee and flavoring during survey contributed to notably higher exposures for both analytes in most, but not all task groups. Alternatively, general exhaust ventilation contributed to lower exposures in all but two models. Additionally, among facilities that flavored, local exhaust ventilation during flavoring processes contributed to lower 2,3-pentanedione exposures during grinding and packaging tasks. Coffee production facilities can consider implementing additional exposure controls for processes, sources, and task-based determinants associated with higher exposures to diacetyl and 2,3-pentanedione, such as isolating, enclosing, and directly exhausting grinders, flavoring mixers, and open storage of off-gassing whole bean and ground coffee, to reduce exposures and minimize risks for lung disease among workers.

Oral disease is linked to low nestling condition and brood size in a raptor species living in a highly modified environment

Anthropogenic stressors can favor the occurrence of non-infectious disease that can be worsened by the impact of opportunistic pathogens, making the epizootiology of environmental diseases difficult to unravel. The incidence and impact of oral lesions in nestlings of a facultative scavenger species, the black kite Milvus migrans, were examined over seven breeding seasons in the highly degraded environment close to Madrid, Spain. We found an overall prevalence of 31% of nestlings with oral lesions, with no clear spatial pattern in nests with affected and unaffected individuals. The occurrence and number of oral lesions was negatively associated with nestling body condition and brood size. Broods where all siblings had oral lesions were smaller than those where some or all siblings were apparently healthy, suggesting that oral disease could be causing nestling mortality and, consequently, brood size reduction. In turn, nestling body condition was negatively affected by lesion occurrence, brood size and laying date. Although these relationship were bidirectional, piecewise structural equation modeling analyses showed a greater negative effect of body condition on lesion occurrence than vice versa, indicating that nestlings in poorer body condition were more likely to develop oral lesions (which could contribute to aggravate their state of deterioration) than those in better condition. Nestlings from small broods were also more likely to have oral disease (directly or indirectly through their lower body condition) than nestlings from large broods. Nestlings that hatched last in the broods showed greater development stress than those that hatched first. Anthropogenic stressors could trigger poor body condition, and contribute to microbiota dysbiosis-related diseases. Although further research is needed to determine the consequences for the long-term fitness of individuals, actions should be taken to mitigate adverse conditions that may favor the appearance of environmental diseases associated with peri-urban areas, given their rapid expansion over natural areas.

Flight efficiency explains differences in natal dispersal distances in birds

The factors responsible for variation in dispersal distances across species remain poorly understood. Previous comparative studies found differing results and equivocal support for theoretical predictions. Here I re-examine factors that influence natal dispersal distances in British birds while taking into account the cost of transport as estimated from proxies of long-distance flight efficiency. First, I show that flight efficiency, as estimated by the hand-wing index, the aspect ratio, or the lift-to-drag ratio, is a strong predictor of dispersal distances among resident species. Most migratory species showed a similar pattern, but a group of species with relatively low aerodynamic efficiency showed longer-than-expected dispersal distances, making the overall trend independent of flight efficiency. Ecological, behavioral, and life history factors had a small or nil influence on dispersal distances, with most of their influence likely mediated by adaptations for the use of space reflected in flight efficiency. This suggests that dispersal distances in birds are not determined by adaptive strategies for dispersal per se, but are predominantly influenced by the energetic cost of movement.

Quantifying Critical Success Factors (CSFs) in Management of Investment-Construction Projects: Insights from Bayesian Model Averaging

The problem with evaluating investment projects is that there are many factors that determine the degree of their successful conclusion. Consequently, there has been an active debate for years as to which critical success factors (CSFs) contribute most to the performance of construction projects. This is because the practice of empirical research is based on two steps: first, researchers choose a particular model from the space of all possible models, and second, they act as if the chosen model is the only one that fits the data and describes the phenomenon under study. Hence, there are many CSF lists that can be found in the literature, owing to the uncertainty at the model selection stage, which is usually ignored. Alternatively, model averaging accounts for this model uncertainty. In this study, the Bayesian model averaging and data from a survey of Polish construction managers were used to investigate the potential of 28 factors describing a diverse set of characteristics in explaining the performance of construction projects in Poland. Determinants of successful completion of investment projects are categorized by their level of evidential strength, which is derived from posterior inclusion probabilities (PIPs), i.e., providing strong, medium and weak evidence.

Parsimonious model selection using information theory: a modified selection rule

Information-theoretic approaches to model selection, such as Akaike's information criterion (AIC) and cross validation, provide a rigorous framework to select among candidate hypotheses in ecology, yet the persistent concern of overfitting undermines the interpretation of inferred processes. A common misconception is that overfitting is due to the choice of criterion or model score, despite research demonstrating that selection uncertainty associated with score estimation is the predominant influence. Here we introduce a novel selection rule that identifies a parsimonious model by directly accounting for estimation uncertainty, while still retaining an information-theoretic interpretation. The new rule, which is a modification of the existing one-standard-error rule, mitigates overfitting and reduces the likelihood that spurious effects will be included in the selected model, thereby improving its inferential properties. We present the rule and illustrative examples in the context of maximum-likelihood estimation and Kullback-Leibler discrepancy, although the rule is applicable in a more general setting, including Bayesian model selection and other types of discrepancy.

Including tree spatial extension in the evaluation of neighborhood competition effects in Bornean rain forest

Classical tree neighborhood models use size variables acting at point distances. In a new approach here, trees were spatially extended as a function of their crown sizes, represented impressionistically as points within crown areas. Extension was accompanied by plasticity in the form of crown removal or relocation under the overlap of taller trees. Root systems were supposedly extended in a similar manner. For the 38 most abundant species in the focal size class (10-<100 cm stem girth) in two 4-ha plots at Danum (Sabah), for periods P1 (1986-1996) and P2 (1996-2007), stem growth rate and tree survival were individually regressed against stem size, and neighborhood conspecific (CON) and heterospecific (HET) basal areas within incremented steps in radius. Model parameters were critically assessed, and statistical robustness in the modeling was set by randomization testing. Classical and extended models differed importantly in their outcomes. Crown extension weakened the relationship of CON effect on growth versus plot species' abundance, showing that models without plasticity overestimated negative density dependence. A significant negative trend of difference in CON effects on growth (P2-P1) versus CON or HET effect on survival in P1 was strongest with crown extension. Model outcomes did not then support an explanation of CON and HET effects being due to (asymmetric) competition for light alone. An alternative hypothesis is that changes in CON effects on small trees, largely incurred by a drought phase (relaxing light limitation) in P2, and following the more shaded (suppressing) conditions in P1, were likely due to species-specific (symmetric) root competition and mycorrhizal processes. The very high variation in neighborhood composition and abundances led to a strong "neighborhood stochasticity" and hence to largely idiosyncratic species' responses. A need to much better understand the roles of rooting structure and processes at the individual tree level was highlighted.

Effects of age, sex, and ENSO phase on foraging and flight performance in Nazca boobies

Age-related changes in survival and reproduction are common in seabirds; however, the underlying causes remain elusive. A lack of experience for young individuals, and a decline in foraging performance for old birds, could underlie age-related variation in reproduction because reproductive success is connected closely to provisioning offspring. For seabirds, flapping flight during foraging trips is physiologically costly; inexperience or senescent decline in performance of this demanding activity might cap delivery of food to the nest, providing a proximate explanation for poor breeding success in young and old age, respectively. We evaluated the hypothesis that young and old Nazca boobies (Sula granti), a Galápagos seabird, demonstrate deficits in foraging outcomes and flight performance. We tagged incubating male and female adults across the life span with both accelerometer and GPS loggers during the incubation periods of two breeding seasons (years), during the 2015 El Niño and the following weak La Niña. We tested the ability of age, sex, and environment to explain variation in foraging outcomes (e.g., mass gained) and flight variables (e.g., wingbeat frequency). Consistent with senescence, old birds gained less mass while foraging than middle-aged individuals, a marginal effect, and achieved a slower airspeed late in a foraging trip. Contrary to expectations, young birds showed no deficit in foraging outcomes or flight performance, except for airspeed (contingent on environment). Young birds flew slower than middle-aged birds in 2015, but faster than middle-aged birds in 2016. Wingbeat frequency, flap-glide ratio, and body displacement (approximating wingbeat strength) failed to predict airspeed and were unaffected by age. Sex influenced nearly all aspects of performance. Environment affected flight performance and foraging outcomes. Boobies' foraging outcomes were better during the extreme 2015 El Niño than during the 2016 weak La Niña, a surprising result given the negative effects tropical seabirds often experience during extreme El Niños.

Toxins from harmful algae in fish from Scottish coastal waters

Harmful algal bloom events are increasing in a number of water bodies around the world with significant economic impacts on the aquaculture, fishing and tourism industries. As well as their potential impacts on human health, toxin exposure from harmful algal blooms (HABs) has resulted in widespread morbidity and mortality in marine life, including top marine predators. There is therefore a need for an improved understanding of the trophic transfer, and persistence of toxins in marine food webs. For the first time, the concentrations of two toxin groups of commercial and environmental importance, domoic acid (DA) and saxitoxin (including Paralytic Shellfish Toxin (PST) analogues), were measured in the viscera of 40 different fish species caught in Scotland between February and November, 2012 to 2019. Overall, fish had higher concentrations of DA compared to PSTs, with a peak in the summer / autumn months. Whole fish concentrations were highest in pelagic species including Atlantic mackerel and herring, key forage fish for marine predators including seals, cetaceans and seabirds. The highest DA concentrations were measured along the east coast of Scotland and in Orkney. PSTs showed highest concentrations in early summer, consistent with phytoplankton bloom timings. The detection of multiple toxins in such a range of demersal, pelagic and benthic fish prey species suggests that both the fish, and by extension, piscivorous marine predators, experience multiple routes of toxin exposure. Risk assessment models to understand the impacts of exposure to HAB toxins on marine predators therefore need to consider how chronic, low-dose exposure to multiple toxins, as well as acute exposure during a bloom, could lead to potential long-term health effects ultimately contributing to mortalities. The potential synergistic, neurotoxic and physiological effects of long-term exposure to multiple toxins require investigation in order to appropriately assess the risks of HAB toxins to fish as well as their predators.

Extrapolating Parametric Survival Models in Health Technology Assessment Using Model Averaging: A Simulation Study

Previous work examined the suitability of relying on routine methods of model selection when extrapolating survival data in a health technology appraisal setting. Here we explore solutions to improve reliability of restricted mean survival time (RMST) estimates from trial data by assessing model plausibility and implementing model averaging. We compare our previous methods of selecting a model for extrapolation using the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Our methods of model averaging include using equal weighting across models falling within established threshold ranges for AIC and BIC and using BIC-based weighted averages. We apply our plausibility assessment and implement model averaging to the output of our previous simulations, where 10,000 runs of 12 trial-based scenarios were examined. We demonstrate that removing implausible models from consideration reduces the mean squared error associated with the restricted mean survival time (RMST) estimate from each selection method and increases the percentage of RMST estimates that were within 10% of the RMST from the parameters of the sampling distribution. The methods of averaging were superior to selecting a single optimal extrapolation, aside from some of the exponential scenarios where BIC already selected the exponential model. The averaging methods with wide criterion-based thresholds outperformed BIC-weighted averaging in the majority of scenarios. We conclude that model averaging approaches should feature more widely in the appraisal of health technologies where extrapolation is influential and considerable uncertainty is present. Where data demonstrate complicated underlying hazard rates, funders should account for the additional uncertainty associated with these extrapolations in their decision making. Extended follow-up from trials should be encouraged and used to review prices of therapies to ensure a fair price is paid.

Declining reproductive success in the Gulf of St. Lawrence's humpback whales (Megaptera novaeangliae) reflects ecosystem shifts on their feeding grounds

Climate change has resulted in physical and biological changes in the world's oceans. How the effects of these changes are buffered by top predator populations, and therefore how much plasticity lies at the highest trophic levels, are largely unknown. Here endocrine profiling, longitudinal observations of known individuals over 15 years between 2004 and 2018, and environmental data are combined to examine how the reproductive success of a top marine predator is being affected by ecosystem change. The Gulf of St. Lawrence, Canada, is a major summer feeding ground for humpback whales (Megaptera novaeangliae) in the North Atlantic. Blubber biopsy samples (n = 185) of female humpback whales were used to investigate variation in pregnancy rates through the quantification of progesterone. Annual pregnancy rates showed considerable variability, with no overall change detected over the study. However, a total of 457 photo-identified adult female sightings records with/without calves were collated, and showed that annual calving rates declined significantly. The probability of observing cow-calf pairs was related to favourable environmental conditions in the previous year; measured by herring spawning stock biomass, Calanus spp. abundance, overall copepod abundance and phytoplankton bloom magnitude. Approximately 39% of identified pregnancies were unsuccessful over the 15 years, and the average annual pregnancy rate was higher than the average annual calving rate at ~37% and ~23% respectively. Together, these data suggest that the declines in reproductive success could be, at least in part, the result of females being unable to accumulate the energy reserves necessary to maintain pregnancy and/or meet the energetic demands of lactation in years of poorer prey availability rather than solely an inability to become pregnant. The decline in calving rates over a period of major environmental variability may suggest that this population has limited resilience to such ecosystem change.

Does genetic diversity protect host populations from parasites? A meta-analysis across natural and agricultural systems

If parasites transmit more readily between closely related hosts, then parasite burdens should decrease with increased genetic diversity of host populations. This important hypothesis is often accepted at face value—notorious epidemics of crop monocultures testify to the vulnerability of host populations that have been purged of diversity. Yet the relationship between genetic diversity and parasitism likely varies across contexts, differing between crop and noncrop hosts and between experimental and natural host populations. Here, we used a meta‐analytic approach to ask if host diversity confers protection against parasites over the range of contexts in which it has been tested. We synthesized the results of 102 studies, comprising 2004 effect sizes representing a diversity of approaches and host‐parasite systems. Our results validate a protective effect of genetic diversity, while revealing significant variation in its strength across biological and empirical contexts. In experimental host populations, genetic diversity reduces parasitism by ∼20% for noncrop hosts and by ∼50% for crop hosts. In contrast, observational studies of natural host populations show no consistent relationship between genetic diversity and parasitism, with both strong negative and positive correlations reported. This result supports the idea that, if parasites preferentially attack close relatives, the correlation of genetic diversity with parasitism could be positive or negative depending upon the potential for host populations to evolve in response to parasite selection. Taken together, these results reinforce genetic diversity as a priority for both conservation and agriculture and emphasize the challenges inherent to drawing comparisons between controlled experimental populations and dynamic natural populations.

Do traits of plant species predict the efficacy of species distribution models for finding new occurrences?

Species distribution models (SDMs) are used to test ecological theory and to direct targeted surveys for species of conservation concern. Several studies have tested for an influence of species traits on the predictive accuracy of SDMs. However, most used the same set of environmental predictors for all species and/or did not use truly independent data to test SDM accuracy. We built eight SDMs for each of 24 plant species of conservation concern, varying the environmental predictors included in each SDM version. We then measured the accuracy of each SDM using independent presence and absence data to calculate area under the receiver operating characteristic curve (AUC) and true positive rate (TPR). We used generalized linear mixed models to test for a relationship between species traits and SDM accuracy, while accounting for variation in SDM performance that might be introduced by different predictor sets. All traits affected one or both SDM accuracy measures. Species with lighter seeds, animal-dispersed seeds, and a higher density of occurrences had higher AUC and TPR than other species, all else being equal. Long-lived woody species had higher AUC than herbaceous species, but lower TPR. These results support the hypothesis that the strength of species-environment correlations is affected by characteristics of species or their geographic distributions. However, because each species has multiple traits, and because AUC and TPR can be affected differently, there is no straightforward way to determine a priori which species will yield useful SDMs based on their traits. Most species yielded at least one useful SDM. Therefore, it is worthwhile to build and test SDMs for the purpose of finding new populations of plant species of conservation concern, regardless of these species' traits.

Scientist's guide to developing explanatory statistical models using causal analysis principles

Recent discussions of model selection and multimodel inference highlight a general challenge for researchers: how to convey the explanatory content of a hypothesized model or set of competing models clearly. The advice from statisticians for scientists employing multimodel inference is to develop a well-thought-out set of candidate models for comparison, though precise instructions for how to do that are typically not given. A coherent body of knowledge, which falls under the general term causal analysis, now exists for examining the explanatory scientific content of candidate models. Much of the literature on causal analysis has been recently developed, and we suspect may not be familiar to many ecologists. This body of knowledge comprises a set of graphical tools and axiomatic principles to support scientists in their endeavors to create "well-formed hypotheses," as statisticians are asking them to do. Causal analysis is complementary to methods such as structural equation modeling, which provides the means for evaluation of proposed hypotheses against data. In this paper, we summarize and illustrate a set of principles that can guide scientists in their quest to develop explanatory hypotheses for evaluation. The principles presented in this paper have the capacity to close the communication gap between statisticians, who urge scientists to develop well-thought-out coherent models, and scientists, who would like some practical advice for exactly how to do that.

Differential effects of habitat loss on occupancy patterns of the eastern green lizard Lacerta viridis at the core and periphery of its distribution range

The effects of habitat loss on the distribution of populations are often linked with species specialization degree. Specialist species can be more affected by changes in landscape structure and local patch characteristics compared to generalist species. Moreover, the spatial scale at which different land covers (eg. habitat, cropland, urban areas) affect specialist species can be smaller. Specialization is usually assumed as a constant trait along the distribution range of species. However, for several taxa, there is evidence of higher specialization degree in peripheral populations compared with populations in the core. Hence, peripheral populations should have a higher sensitivity to habitat loss, and strongest effects should be found at a smaller spatial scale. To test these expectations, we implemented a patch-landscape approach at different spatial scales, and compared effects of landscape structure and patch characteristics on occupancy probability among northern peripheral, more specialized populations (Czech Republic) and core populations (Bulgaria) of the eastern green lizard Lacerta viridis. We found that landscape structure and patch characteristics affect differently the occupancy probability of Lacerta viridis in each region. Strongest effects of habitat loss were found at a spatial scale of 150m around patches in the periphery, but at a scale of 500m in the core. In the periphery occupancy probability of populations was principally affected by landscape composition, and the effect of habitat quality was stronger compared to core populations. In the core, persistence of populations was mainly explained by characteristics of the spatial configuration of habitat patches. We discuss possible ecological mechanisms behind the relationship between sensitivity to habitat loss, populations' specialization degree and position in the distribution range, and suggest conservation measures for L. viridis.

External temperature and distance from nearest entrance influence microclimates of cave and culvert-roosting tri-colored bats (Perimyotis subflavus)

Many North American bat species hibernate in both natural and artificial roosts. Although hibernacula can have high internal climate stability, they still retain spatial variability in their thermal regimes, resulting in various "microclimates" throughout the roost that differ in their characteristics (e.g., temperature and air moisture). These microclimate components can be influenced by factors such as the number of entrances, the depth of the roost, and distance to the nearest entrance of the roost. Tri-colored bats are commonly found roosting in caves in winter, but they can also be found roosting in large numbers in culverts, providing the unique opportunity to investigate factors influencing microclimates of bats in both natural and artificial roost sites. As tri-colored bats are currently under consideration for federal listing, information of this type could be useful in aiding in the conservation and management of this species through a better understanding of what factors affect the microclimate near roosting bats. We collected data on microclimate temperature and microclimate actual water vapor pressure (AWVP) from a total of 760 overwintering tri-colored bats at 18 caves and 44 culverts. Using linear mixed models analysis, we found that variation in bat microclimate temperatures was best explained by external temperature and distance from nearest entrance in both caves and culverts. External temperature had a greater influence on microclimate temperatures in culverts than caves. We found that variation in microclimate AWVP was best explained by external temperature, distance from nearest entrance, and proportion from entrance (proportion of the total length of the roost from the nearest entrance) in culvert-roosting bats. Variation in microclimate AWVP was best explained by external temperature and proportion from entrance in cave-roosting bats. Our results suggest that bat microclimate temperature and AWVP are influenced by similar factors in both artificial and natural roosts, although the relative contribution of these factors differs between roost types.

Why are monarch butterflies declining in the West? Understanding the importance of multiple correlated drivers

Understanding the factors associated with declines of at-risk species is an important first step in setting management and recovery targets. This step can be challenging when multiple aspects of climate and land use are changing simultaneously, and any or all could be contributing to population declines. We analyzed population trends of monarch butterflies in western North America in relation to likely environmental drivers. Unlike the larger eastern monarch population, past analyses of western monarchs have only evaluated the importance of climate (i.e., not land use) factors as drivers of abundance. We used partial least squares regression (PLSR) to evaluate the potential importance of changes in land use and climate variables. Trends in western monarch abundance were more strongly associated with land use variables than climate variables. Conclusions about importance of climate and land use variables were robust to changes in PLSR model structure. However, individual variables were too collinear to unambiguously separate their effects. We compared these conclusions to the more widely used technique of multiple regression, followed by multi-model inference (MRMI). Naïve interpretation of MRMI results could be misleading, if collinearity were not taken into account. MRMI was also highly sensitive to variation in model construction. Our results suggest a two-pronged approach to monarch conservation, specifically, starting efforts now to restore habitat, while also using experiments to more clearly delineate separate effects of climate and land use factors. They also demonstrate the utility of PLSR, a technique that is growing in use but is still relatively under-appreciated in conservation biology.

Ant diversity in Neotropical savannas: Hierarchical processes acting at multiple spatial scales

Understanding what creates and maintains macroscale biodiversity gradients is a central focus of ecological and evolutionary research. Spatial patterns in diversity are driven by a hierarchy of factors operating at multiple scales. Historical and climatic factors drive large-scale patterns of diversity by affecting the size of regional species pools, while habitat heterogeneity or microhabitat characteristics further influence species coexistence at small scales. We tested the degree to which the species-energy, historical factors, habitat heterogeneity and local environment hypotheses explain observed patterns of ant diversity across hierarchical spatial scales. We sampled ground-dwelling ants at 29 sites within a Neotropical savanna region, the Brazilian Cerrado. We measured species density - an abundance-dependent diversity metric - and rarefied species richness - an abundance-independent metric - at spatial scales with varying grain sizes. For each hypothesis, two correlates were used to predict ant diversity patterns: (a) species-energy: rainfall and productivity; (b) historical factors: historical variation in rainfall and refugial areas; (c) habitat heterogeneity: heterogeneity in greenness and diversity of land cover; and (d) local factors: contents of sand and coarse fragments in the soil. Ant diversity patterns correlated to net primary productivity and to the proportion of coarse fragments in the soil, corroborating the species-energy and local environment hypotheses, respectively. Soil negatively influenced species density, but not rarefied species richness, which was positively influenced by productivity. We found scale dependencies in the effects of soil/productivity on species density; productivity best predicted species density patterns at large scales, since sampling completeness offset the abundance-driven effects of soil. Considering abundance differences may help to discern the mechanisms underlying the relationship between macroscale diversity patterns and its ecological drivers. Plant productivity affected ant diversity independently of abundance, possibly by limiting the size of regional species pools. On the other hand, soil properties had an abundance-dependent effect on ant diversity, indicating a sampling mechanism. Our findings are consistent with predictions of the hierarchical theory of diversity. Large-scale patterns of productivity limit regional diversity, an effect that cascades down to finer spatial scales, where soil properties influence the number of coexisting species.

Snap happy: camera traps are an effective sampling tool when compared with alternative methods

Camera traps have become a ubiquitous tool in ecology and conservation. They are routinely deployed in wildlife survey and monitoring work, and are being advocated as a tool for planetary-scale biodiversity monitoring. The camera trap's widespread adoption is predicated on the assumption of its effectiveness, but the evidence base for this is lacking. Using 104 past studies, we recorded the qualitative overall recommendations made by study authors (for or against camera traps, or ambiguous), together with quantitative data on the effectiveness of camera traps (e.g. number of species detected or detection probabilities) relative to 22 other methods. Most studies recommended the use of camera traps overall and they were 39% more effective based on the quantitative data. They were significantly more effective compared with live traps (88%) and were otherwise comparable in effectiveness to other methods. Camera traps were significantly more effective than other methods at detecting a large number of species (31% more) and for generating detections of species (91% more). This makes camera traps particularly suitable for broad-spectrum biodiversity surveys. Film camera traps were found to be far less effective than digital models, which has led to an increase in camera trap effectiveness over time. There was also evidence from the authors that the use of attractants with camera traps reduced their effectiveness (counter to their intended effect), while the quantitative data indicated that camera traps were more effective in closed than open habitats. Camera traps are a highly effective wildlife survey tool and their performance will only improve with future technological advances. The images they produce also have a range of other benefits, for example as digital voucher specimens and as visual aids for outreach. The evidence-base supports the increasing use of camera traps and underlines their suitability for meeting the challenges of global-scale biodiversity monitoring.

Acute drivers influence recent inshore Great Barrier Reef dynamics

Understanding the dynamics of habitat-forming organisms is fundamental to managing natural ecosystems. Most studies of coral reef dynamics have focused on clear-water systems though corals inhabit many turbid regions. Here, we illustrate the key drivers of an inshore coral reef ecosystem using 10 years of biological, environmental, and disturbance data. Tropical cyclones, crown-of-thorns starfish, and coral bleaching are recognized as the major drivers of coral loss at mid- and offshore reefs along the Great Barrier Reef (GBR). In comparison, little is known about what drives temporal trends at inshore reefs closer to major anthropogenic stress. We assessed coral cover dynamics using state-space models within six major inshore GBR catchments. An overall decline was detected in nearly half (46%) of the 15 reefs at two depths (30 sites), while the rest exhibited fluctuating (23%), static (17%), or positive (13%) trends. Inshore reefs responded similarly to their offshore counterparts, where contemporary trends were predominantly influenced by acute disturbance events. Storms emerged as the major driver affecting the inshore GBR, with the effects of other drivers such as disease, juvenile coral density, and macroalgal and turf per cent cover varying from one catchment to another. Flooding was also associated with negative trends in live coral cover in two southern catchments, but the mechanism remains unclear as it is not reflected in available metrics of water quality and may act through indirect pathways.

Brown bear damage: patterns and hotspots in Croatia

Human–bear conflicts resulting from livestock depredation and crop use are a common threat to the brown bear Ursus arctos throughout its range. Understanding these conflicts requires the recording and categorization of incidents, assessment of their geographical distribution and frequency, and documentation of the financial costs and the presence of any preventative measures. Damage compensation schemes can help mitigate conflicts and, in some cases, improve acceptance of bears. This study aims to elucidate the major factors determining the patterns of damage caused by bears, examine the effectiveness of preventative measures in reducing such damage, and identify bear damage hotspots in Croatia. Our analysis is based on damage reports provided by hunting organizations to the Croatian Ministry of Agriculture during 2004–2014. The highest number of claims were made for damage to field crops and orchards. Damage to livestock, agricultural crops and beehives resulted in the highest total cost to farmers. Damage to beehives and to automatic corn feeders for game species incurred the highest cost per damage event. We identified a hotspot for bear damage claims in Croatia, located near Risnjak National Park and the border with Slovenia. Damage appears higher in areas that have more villages closer to protected areas and a greater per cent of forest cover, indicating a synergistic effect of protected environments that facilitate bear movements and the presence of human activities that provide easily accessible food for bears.

Superpredator proximity and landscape characteristics alters nest site selection and breeding success of a subordinate predator

Selecting nesting habitat that minimizes predation risk but maximizes foraging success is one of the most important decisions in avian life history. This takes on added complexity when a predator is faced with the challenge of avoiding fellow predators. We assessed the importance of local and landscape vegetation, food abundance, and predation risk on nest site selection and nest survival in a subordinate raptor (Mississippi Kite; Ictinia mississippiensis) nesting in proximity to two superpredators, Red-tailed hawk (Buteo jamaicensis) and Great horned owl (Bubo virginianus). All three species nested in trees in a grassland landscape. In this landscape, kites favored upland trees and shrubs, avoiding their more typical riparian forest association elsewhere in the species' range. Compared to random conditions, kites selected nest sites with high tree density and more closed canopy in the surrounding area. Mississippi Kite selection was not related to food abundance but could be explained by the presence of superpredators (i.e., hawks and owls) selecting riparian woodland for their nests. Nest survival declined with proximity to superpredator nesting sites. Overall, our study demonstrates how landscape structure and superior predators shapes predation risk for subordinate predators. Our results emphasize the importance of spatial heterogeneity in presenting opportunities for subordinate predators to coexist in a landscape with important superpredators.