Information Gathering Is Associated with Increased Survival: A Field Experiment in Black-Capped Chickadees (Poecile atricapillus).

AbstractSampling, investing time or energy to learn about the environment, allows organisms to track changes in resource distribution and quality. The use of sampling is predicted to change as a function of energy expenditure, food availability, and starvation risk, all of which can vary both within and among individuals. We studied sampling behavior in a field study with black-capped chickadees (Poecile atricapillus) and show that individuals adjust their use of sampling as a function of ambient temperature (a proxy for energy expenditure), the presence of an alternative food source (yes or no, a proxy for risk of energy shortfall), and their interaction, as predicted by models of optimal sampling. We also observed repeatable differences in sampling. Some individuals consistently sampled more, and individuals that sampled more overall also had a higher annual survival. These results are consistent with among-individual differences in resource acquisition (e.g., food caches or dominance-related differences in priority access to feeders), shaping among-individual differences in both sampling and survival, with greater resource acquisition leading to both higher sampling and higher survival. Although this explanation requires explicit testing, it is in line with several recent studies suggesting that variation in resource acquisition is a key mechanism underlying animal personality.

Adult body mass is heritable, positively genetically correlated and under selection of differing shapes between the sexes in a bird with little apparent sexual dimorphism.

In most animals, body mass varies with ecological conditions and is expected to reflect how much energy can be allocated to reproduction and survival. Because the sexes often differ in their resource acquisition and allocation strategies, variations in adult body mass and their consequences on fitness can differ between the sexes. Assessing the relative contributions of environmental and genetic effects (i.e. heritability)-and whether these effects and their fitness consequences are sex-specific-is essential to gain insights into the evolution of sexual dimorphism and sexual conflicts. We used 20+ years of data to study the sources of variation in adult body mass and associated fitness consequences in a bird with biparental care, the Alpine swift (Tachymarptis melba). Swifts appear monomorphic to human observers, though subtle dimorphisms are present. We first investigated the effects of weather conditions on adult body mass using a sliding window analysis approach. We report a positive effect of temperature and a negative effect of rainfall on adult body mass, as expected for an aerial insectivorous bird. We then quantified the additive genetic variance and heritability of body mass in both sexes and assessed the importance of genetic constraints on mass evolution by estimating the cross-sex genetic correlation. Heritability was different from zero in both sexes at ~0.30. The positive cross-sex genetic correlation and comparable additive genetic variance between the sexes suggest the possibility for evolutionary constraints when it comes to body mass. Finally, we assessed the sex-specific selection on adjusted body mass using multiple fitness components. We report directional positive and negative selection trending towards stabilizing and diversifying selection on females and males respectively in relation to the weighted proportion of surviving fledglings. Overall, these results suggest that while body mass may be able to respond to environmental conditions and evolve, genetic constraints would result in similar changes in both sexes or an overall absence of response to selection. It remains unclear whether the weak (1%) dimorphism in Alpine swift body mass we report is simply a result of the similar fitness peaks between the sexes or of genetic constraints.

Current and lagged climate affects phenology across diverse taxonomic groups.

The timing of life events (phenology) can be influenced by climate. Studies from around the world tell us that climate cues and species' responses can vary greatly. If variation in climate effects on phenology is strong within a single ecosystem, climate change could lead to ecological disruption, but detailed data from diverse taxa within a single ecosystem are rare. We collated first sighting and median activity within a high-elevation environment for plants, insects, birds, mammals and an amphibian across 45 years (1975-2020). We related 10 812 phenological events to climate data to determine the relative importance of climate effects on species' phenologies. We demonstrate significant variation in climate-phenology linkage across taxa in a single ecosystem. Both current and prior climate predicted changes in phenology. Taxa responded to some cues similarly, such as snowmelt date and spring temperatures; other cues affected phenology differently. For example, prior summer precipitation had no effect on most plants, delayed first activity of some insects, but advanced activity of the amphibian, some mammals, and birds. Comparing phenological responses of taxa at a single location, we find that important cues often differ among taxa, suggesting that changes to climate may disrupt synchrony of timing among taxa.

Individual life histories: neither slow nor fast, just diverse.

The slow-fast continuum is a commonly used framework to describe variation in life-history strategies across species. Individual life histories have also been assumed to follow a similar pattern, especially in the pace-of-life syndrome literature. However, whether a slow-fast continuum commonly explains life-history variation among individuals within a population remains unclear. Here, we formally tested for the presence of a slow-fast continuum of life histories both within populations and across species using detailed long-term individual-based demographic data for 17 bird and mammal species with markedly different life histories. We estimated adult lifespan, age at first reproduction, annual breeding frequency, and annual fecundity, and identified the main axes of life-history variation using principal component analyses. Across species, we retrieved the slow-fast continuum as the main axis of life-history variation. However, within populations, the patterns of individual life-history variation did not align with a slow-fast continuum in any species. Thus, a continuum ranking individuals from slow to fast living is unlikely to shape individual differences in life histories within populations. Rather, individual life-history variation is likely idiosyncratic across species, potentially because of processes such as stochasticity, density dependence, and individual differences in resource acquisition that affect species differently and generate non-generalizable patterns across species.

Older mothers produce more successful daughters.

Annual reproductive success and senescence patterns vary substantially among individuals in the wild. However, it is still seldom considered that senescence may not only affect an individual but also affect age-specific reproductive success in its offspring, generating transgenerational reproductive senescence. We used long-term data from wild yellow-bellied marmots (Marmota flaviventer) living in two different elevational environments to quantify age-specific reproductive success of daughters born to mothers differing in age. Contrary to prediction, daughters born to older mothers had greater annual reproductive success on average than daughters born to younger mothers, and this translated into greater lifetime reproductive success. However, in the favorable lower elevation environment, daughters born to older mothers also had greater age-specific decreases in annual reproductive success. In the harsher higher elevation environment on the other hand, daughters born to older mothers tended to die before reaching ages at which such senescent decreases could be observed. Our study highlights the importance of incorporating environment-specific transgenerational parent age effects on adult offspring age-specific life-history traits to fully understand the substantial variation observed in senescence patterns in wild populations.

Contrasting effects of climate change on seasonal survival of a hibernating mammal.

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics.

Rapid prototyping for quantifying belief weights of competing hypotheses about emergent diseases.

Emerging diseases can have devastating consequences for wildlife and require a rapid response. A critical first step towards developing appropriate management is identifying the etiology of the disease, which can be difficult to determine, particularly early in emergence. Gathering and synthesizing existing information about potential disease causes, by leveraging expert knowledge or relevant existing studies, provides a principled approach to quickly inform decision-making and management efforts. Additionally, updating the current state of knowledge as more information becomes available over time can reduce scientific uncertainty and lead to substantial improvement in the decision-making process and the application of management actions that incorporate and adapt to newly acquired scientific understanding. Here we present a rapid prototyping method for quantifying belief weights for competing hypotheses about the etiology of disease using a combination of formal expert elicitation and Bayesian hierarchical modeling. We illustrate the application of this approach for investigating the etiology of stony coral tissue loss disease (SCTLD) and discuss the opportunities and challenges of this approach for addressing emergent diseases. Lastly, we detail how our work may apply to other pressing management or conservation problems that require quick responses. We found the rapid prototyping methods to be an efficient and rapid means to narrow down the number of potential hypotheses, synthesize current understanding, and help prioritize future studies and experiments. This approach is rapid by providing a snapshot assessment of the current state of knowledge. It can also be updated periodically (e.g., annually) to assess changes in belief weights over time as scientific understanding increases. Synthesis and applications: The rapid prototyping approaches demonstrated here can be used to combine knowledge from multiple experts and/or studies to help with fast decision-making needed for urgent conservation issues including emerging diseases and other management problems that require rapid responses. These approaches can also be used to adjust belief weights over time as studies and expert knowledge accumulate and can be a helpful tool for adapting management decisions.

An invasive prey provides long-lasting silver spoon effects for an endangered predator.

The natal environment can have long-term fitness consequences for individuals, particularly via 'silver spoon' or 'environmental matching' effects. Invasive species could alter natal effects on native species by changing species interactions, but this potential remains unknown. Using 17 years of data on 2588 individuals across the entire US breeding range of the endangered snail kite (Rostrhamus sociabilis), a wetland raptor that feeds entirely on Pomacea snails, we tested for silver spoon and environmental matching effects on survival and movement and whether the invasion of a non-native snail may alter outcomes. We found support for silver spoon effects, not environmental matching, on survival that operated through body condition at fledging, explained by hydrology in the natal wetland. When non-native snails were present at the natal site, kites were in better condition, individual condition was less sensitive to hydrology, and kites fledged across a wider range of hydrologic conditions, leading to higher survival that persisted for at least 10 years. Movement between wetlands was driven by the current (adult) environment, and birds born in both invaded and uninvaded wetlands preferred to occupy invaded wetlands post-fledging. These results illustrate that species invasions may profoundly impact the role of natal environments on native species.

End-tidal Carbon Dioxide for Diagnosing Anaphylaxis in Patients with Severe Postinduction Hypotension.

BACKGROUND: Perioperative hypersensitivity reactions may be difficult to diagnose during general anesthesia. Postinduction hypotension is the most common sign but is not specific. It was recently suggested that low end-tidal carbon dioxide (ETco2) might be a marker of anaphylaxis (Ring and Messmer grades III to IV immediate hypersensitivity reactions) in hypotensive patients under mechanical ventilation. To test this hypothesis, the authors compared ETco2 in patients with a diagnosis of anaphylaxis and in patients with severe hypotension from any other cause after the induction of anesthesia. METHODS: This was a retrospective single-center case-control study in which two groups were formed from an anesthesia data warehouse. The anaphylaxis group was formed on the basis of tryptase/histamine assay data and allergy workup data recorded over the period 2010 to 2018. The control (hypotension) group consisted of all patients having experienced severe hypotension (mean arterial pressure less than 50 mmHg for 5 min or longer) with a cause other than anaphylaxis after anesthesia induction in 2017. RESULTS: The anaphylaxis and hypotension groups comprised 49 patients (grade III: n = 38; grade IV: n = 11) and 555 patients, respectively. The minimum ETco2 value was significantly lower in the anaphylaxis group (median [interquartile range]: 17 [12 to 23] mmHg) than in the hypotension group (32 [29 to 34] mmHg; P < 0.001). The area under the receiver operating characteristic curve (95% CI) for ETco2 was 0.95 (0.91 to 0.99). The sensitivity and specificity (95% CI) for the optimal cutoff value were 0.92 (0.82 to 0.98) and 0.94 (0.92 to 0.99), respectively. In multivariable analysis, minimum ETco2 was associated with anaphylaxis after adjusting for confounders and competing predictors, including arterial pressure, heart rate, and peak airway pressure (odds ratio [95% CI] for ETco2: 0.51 [0.38 to 0.68]; P < 0.001). CONCLUSIONS: In case of severe hypotension after anesthesia induction, a low ETco2 contributes to the diagnosis of anaphylaxis, in addition to the classical signs of perioperative immediate hypersensitivity.

Distinguishing within- from between-individual effects: How to use the within-individual centring method for quadratic patterns.

Any average pattern observed at the population level (cross-sectional analysis) may confound two different types of processes: some processes that occur among individuals and others that occur within individuals. Separating within- from among-individual processes is critical for our understanding of ecological and evolutionary dynamics. The within-individual centring method allows distinguishing within- from among-individual processes and this method has been widely used in ecology to investigate both linear and quadratic patterns. Here we show that two alternative equations could be used for the investigation of quadratic within-individual patterns. We explain the different assumptions and constraints of both equations. Reviewing the literature, we found that mainly one of these two equations has been used in studies investigating quadratic patterns. Yet this equation might not be the most appropriate in all circumstances leading to bias and imprecision. We show that these two alternative equations make different assumptions about the shape of the within-individual pattern. One equation assumes that the within-individual effect is related to an absolute process whereas the other assumes the effect arises from an individual relative process. The choice of using one equation instead of the other should depend upon the biological process investigated. Using simulations, we showed that a mismatch between the assumptions made by the equation used to analyse the data and the biological process investigated might led to flawed inference affecting output of model selection and accuracy of estimates. We stress that the equation used should be chosen carefully. We provide step by step guidelines for choosing an equation when studying quadratic pattern with the within-individual centring approach. We encourage the use of the within-individual centring method, promoting its relevant application for nonlinear relationships.

Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty.

Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle (Glyptemys insculpta) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λmean = 0.952, 95% CI: 0.87-1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.

MiR-100 overexpression attenuates high fat diet induced weight gain, liver steatosis, hypertriglyceridemia and development of metabolic syndrome in mice.

BACKGROUND: Diet-induced obesity can result in the development of a diverse spectrum of cardiovascular and metabolic diseases, including type 2 diabetes, dyslipidemia, non-alcoholic liver steatosis and atherosclerotic disease. MicroRNAs have been described to be important regulators of metabolism and disease development. METHODS: In the current study, we investigated the effects of ubiquitous miR-100 overexpression on weight gain and the metabolic phenotype in a newly generated transgenic mouse strain under normal chow and high fat diet and used microarray expression analysis to identify new potential target genes of miR-100. RESULTS: While transgenic overexpression of miR-100 did not significantly affect weight and metabolism under a normal diet, miR-100 overexpressing mice showed a reduced weight gain under a high fat diet compared to wildtype mice, despite an equal calorie intake. This was accompanied by less visceral and subcutaneous fat development and lover serum LDL cholesterol. In addition, transgenic miR-100 mice were more glucose tolerant and insulin sensitive and demonstrated increased energy expenditure under high fat diet feeding. A comprehensive gene expression profiling revealed the differential expression of several genes involved in lipid storage- and metabolism, among them CD36 and Cyp4A14. Our data showed a direct regulation of CD36 by miR-100, leading to a reduced fatty acid uptake in primary hepatocytes overexpressing miR-100 and the downregulation of several downstream mediators of lipid metabolism such as ACC1, FABP4, FAS and PPARγ in the liver. CONCLUSIONS: Our findings demonstrate a protective role of miR-100 in high fat diet induced metabolic syndrome and liver steatosis, partially mediated by the direct repression of CD36 and attenuation of hepatic lipid storage, implicating miR-100 as a possible therapeutic target in liver steatosis.

Albatrosses respond adaptively to climate variability by changing variance in a foraging trait.

The ability of individuals and populations to adapt to a changing climate is a key determinant of population dynamics. While changes in mean behaviour are well studied, changes in trait variance have been largely ignored, despite being assumed to be crucial for adapting to a changing environment. As the ability to acquire resources is essential to both reproduction and survival, changes in behaviours that maximize resource acquisition should be under selection. Here, using foraging trip duration data collected over 7 years on black-browed albatrosses (Thalassarche melanophris) on the Kerguelen Islands in the southern Indian Ocean, we examined the importance of changes in the mean and variance in foraging behaviour, and the associated effects on fitness, in response to the El Niño Southern Oscillation (ENSO). Using double hierarchical models, we found no evidence that individuals change their mean foraging trip duration in response to a changing environment, but found strong evidence of changes in variance. Younger birds showed greater variability in foraging trip duration in poor conditions as did birds with higher fitness. However, during brooding, birds showed greater variability in foraging behaviour under good conditions, suggesting that optimal conditions allow the alteration between chick provisioning and self-maintenance trips. We found weak correlations between sea surface temperature and the ENSO, but stronger links with sea-level pressure. We suggest that variability in behavioural traits affecting resource acquisition is under selection and offers a mechanism by which individuals can adapt to a changing climate. Studies which look only at effects on mean behaviour may underestimate the effects of climate change and fail to consider variance in traits as a key evolutionary force.

Optimal allocation of law enforcement patrol effort to mitigate poaching activities.

Poaching is a global problem causing the decline of species worldwide. Optimizing the efficiency of ranger patrols to deter poaching activity at the lowest possible cost is crucial for protecting species with limited resources. We applied decision analysis and spatial optimization algorithms to allocate efforts of ranger patrols throughout a national park. Our objective was to mitigate poaching activity at or below management risk targets for the lowest monetary cost. We examined this trade-off by constructing a Pareto efficiency frontier using integer linear programming. We used data from a ranger-based monitoring program in Nyungwe National Park, Rwanda. Our measure of poaching risk is based on dynamic occupancy models that account for imperfect detection of poaching activities. We found that in order to achieve a 5% reduction in poaching risk, 622 ranger patrol events (each corresponding to patrolling 1-km2 sites) were needed within a year at a cost of US$49,760. In order to attain a 60% reduction in poaching risk, 15,560 patrol events were needed at a cost of US$1,244,800. We evaluated the trade-off between patrol cost and poaching risk based on our model by constructing a Pareto efficiency frontier and park managers found the solution for a 50% risk reduction to be a practical trade-off based on funding constraints (comparable to recent years) and the diminishing returns between risk mitigation and cost. This expected reduction in risk required 8,558 patrol events per year at a cost of US$684,640. Our results suggest that optimal solutions could increase efficiency compared to the actual effort allocations from 2006 to 2016 in Nyungwe National Park (e.g., risk reductions of ~30% under recent budgets compared to ~50% reduction in risk under the optimal strategy). The modeling framework in this study took into account imperfect detection of poaching risk as well as the directional and conditional nature of ranger patrol events given the spatial adjacency relationships of neighboring sites and access points. Our analyses can help to improve the efficiency of ranger patrols, and the modeling framework can be broadly applied to other spatial conservation planning problems with conditional, multilevel, site selection.

Assessing seasonal demographic covariation to understand environmental-change impacts on a hibernating mammal.

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development and reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneously, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.

Genetic variance for behavioural 'predictability' of stress response.

Genetic factors underpinning phenotypic variation are required if natural selection is to result in adaptive evolution. However, evolutionary and behavioural ecologists typically focus on variation among individuals in their average trait values and seek to characterize genetic contributions to this. As a result, less attention has been paid to if and how genes could contribute towards within-individual variance or trait 'predictability'. In fact, phenotypic 'predictability' can vary among individuals, and emerging evidence from livestock genetics suggests this can be due to genetic factors. Here, we test this empirically using repeated measures of a behavioural stress response trait in a pedigreed population of wild-type guppies. We ask (a) whether individuals differ in behavioural predictability and (b) whether this variation is heritable and so evolvable under selection. Using statistical methodology from the field of quantitative genetics, we find support for both hypotheses and also show evidence of a genetic correlation structure between the behavioural trait mean and individual predictability. We show that investigating sources of variability in trait predictability is statistically tractable and can yield useful biological interpretation. We conclude that, if widespread, genetic variance for 'predictability' will have major implications for the evolutionary causes and consequences of phenotypic variation.

MicroRNA-100 Suppresses Chronic Vascular Inflammation by Stimulation of Endothelial Autophagy.

RATIONALE: The interaction of circulating cells within the vascular wall is a critical event in chronic inflammatory processes, such as atherosclerosis, but the control of the vascular inflammatory state is still largely unclear. OBJECTIVE: This study was undertaken to characterize the function of the endothelial-enriched microRNA miR-100 during vascular inflammation and atherogenesis. METHODS AND RESULTS: Based on a transcriptome analysis of endothelial cells after miR-100 overexpression, we identified miR-100 as a potent suppressor of endothelial adhesion molecule expression, resulting in attenuated leukocyte-endothelial interaction in vitro and in vivo as shown by flow cytometry and intravital imaging. Mechanistically, miR-100 directly repressed several components of mammalian target of rapamycin complex 1-signaling, including mammalian target of rapamycin and raptor, which resulted in a stimulation of endothelial autophagy and attenuated nuclear factor κB signaling in vitro and in vivo. In a low-density lipoprotein receptor-deficient atherosclerotic mouse model, pharmacological inhibition of miR-100 resulted in enhanced plaque lesion formation and a higher macrophage content of the plaque, whereas a systemic miR-100 replacement therapy had protective effects and attenuated atherogenesis, resulting in a decrease of plaque area by 45%. Finally, analysis of miR-100 expression in >70 samples obtained during carotid endarterectomy revealed that local miR-100 expression was inversely correlated with inflammatory cell content in patients. CONCLUSIONS: In summary, we describe an anti-inflammatory function of miR-100 in the vascular response to injury and inflammation and identify an important novel modulator of mammalian target of rapamycin signaling and autophagy in the vascular system. Our findings of miR-100 as a potential protective anti-athero-miR suggest that the therapeutic replacement of this microRNA could be a potential strategy for the treatment of chronic inflammatory diseases, such as atherosclerosis, in the future.

Collision between biological process and statistical analysis revealed by mean centring.

Animal ecologists often collect hierarchically structured data and analyse these with linear mixed-effects models. Specific complications arise when the effect sizes of covariates vary on multiple levels (e.g. within vs. among subjects). Mean centring of covariates within subjects offers a useful approach in such situations, but is not without problems. A statistical model represents a hypothesis about the underlying biological process. Mean centring within clusters assumes that the lower level responses (e.g. within subjects) depend on the deviation from the subject mean (relative) rather than on the absolute scale of the covariate. This may or may not be biologically realistic. We show that mismatch between the nature of the generating (i.e. biological) process and the form of the statistical analysis produce major conceptual and operational challenges for empiricists. We explored the consequences of mismatches by simulating data with three response-generating processes differing in the source of correlation between a covariate and the response. These data were then analysed by three different analysis equations. We asked how robustly different analysis equations estimate key parameters of interest and under which circumstances biases arise. Mismatches between generating and analytical equations created several intractable problems for estimating key parameters. The most widely misestimated parameter was the among-subject variance in response. We found that no single analysis equation was robust in estimating all parameters generated by all equations. Importantly, even when response-generating and analysis equations matched mathematically, bias in some parameters arose when sampling across the range of the covariate was limited. Our results have general implications for how we collect and analyse data. They also remind us more generally that conclusions from statistical analysis of data are conditional on a hypothesis, sometimes implicit, for the process(es) that generated the attributes we measure. We discuss strategies for real data analysis in face of uncertainty about the underlying biological process.

Consistent within-individual plasticity is sufficient to explain temperature responses in red deer reproductive traits.

Warming global temperatures are affecting a range of aspects of wild populations, but the exact mechanisms driving associations between temperature and phenotypic traits may be difficult to identify. Here, we use a 36-year data set on a wild population of red deer to investigate the causes of associations between temperature and two important components of female reproduction: timing of breeding and offspring size. By separating within- versus between-individual associations with temperature for each trait, we show that within-individual phenotypic plasticity (changes within a female's lifetime) was entirely sufficient to generate the observed population-level association with temperature at key times of year. However, despite apparently adequate statistical power, we found no evidence of any variation between females in their responses (i.e. no "IxE" interactions). Our results suggest that female deer show plasticity in reproductive traits in response to temperatures in the year leading up to calving and that this response is consistent across individuals, implying no potential for either selection or heritability of plasticity. We estimate that the plastic response to rising temperatures explained 24% of the observed advance in mean calving date over the study period. We highlight the need for comparable analyses of other systems to determine the contribution of within-individual plasticity to population-level responses to climate change.

Spatial conservation planning under uncertainty: adapting to climate change risks using modern portfolio theory.

Climate change and urban growth impact habitats, species, and ecosystem services. To buffer against global change, an established adaptation strategy is designing protected areas to increase representation and complementarity of biodiversity features. Uncertainty regarding the scale and magnitude of landscape change complicates reserve planning and exposes decision makers to the risk of failing to meet conservation goals. Conservation planning tends to treat risk as an absolute measure, ignoring the context of the management problem and risk preferences of stakeholders. Application of risk management theory to conservation emphasizes the diversification of a portfolio of assets, with the goal of reducing the impact of system volatility on investment return. We use principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in climate-driven reserve design. We extend MPT to specify a framework that evaluates multiple conservation objectives, allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. We apply an efficient search algorithm that optimizes portfolio design for large conservation problems and a game theoretic approach to evaluate portfolio trade-offs that satisfy decision makers with divergent benefit and risk tolerances, or when a single decision maker cannot resolve their own preferences. Evaluating several risk profiles for a case study in South Carolina, our results suggest that a reserve design may be somewhat robust to differences in risk attitude but that budgets will likely be important determinants of conservation planning strategies, particularly when divestment is considered a viable alternative. We identify a possible fiscal threshold where adequate resources allow protecting a sufficiently diverse portfolio of habitats such that the risk of failing to achieve conservation objectives is considerably lower. For a range of sea-level rise projections, conversion of habitat to open water (14-180%) and wetland loss (1-7%) are unable to be compensated under the current protected network. In contrast, optimal reserve design outcomes are predicted to ameliorate expected losses relative to current and future habitat protected under the existing conservation estate.