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1.
Proc Natl Acad Sci U S A ; 121(12): e2312252121, 2024 03 19.
Artigo em Inglês | MEDLINE | ID: mdl-38466845

RESUMO

The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family Mustelidae, Order Carnivora) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation.


Assuntos
Carnívoros , Comportamento Social , Animais , Carnívoros/fisiologia
2.
J Anim Ecol ; 93(2): 132-146, 2024 02.
Artigo em Inglês | MEDLINE | ID: mdl-38213300

RESUMO

How animals use the diel period (24-h light-dark cycle) is of fundamental importance to understand their niche. While ecological and evolutionary literature abound with discussion of diel phenotypes (e.g. diurnal, nocturnal, crepuscular, cathemeral), they lack clear and explicit quantitative definitions. As such, inference can be confounded when evaluating hypotheses of animal diel niche switching or plasticity across studies because researchers may be operating under different definitions of diel phenotypes. We propose quantitative definitions of diel phenotypes using four alternative hypothesis sets (maximizing, traditional, general and selection) aimed at achieving different objectives. Each hypothesis set is composed of mutually exclusive hypotheses defined based on the activity probabilities in the three fundamental periods of light availability (twilight, daytime and night-time). We develop a Bayesian modelling framework that compares diel phenotype hypotheses using Bayes factors and estimates model parameters using a multinomial model with linear inequality constraints. Model comparison, parameter estimation and visualizing results can be done in the Diel.Niche R package. A simplified R Shiny web application is also available. We provide extensive simulation results to guide researchers on the power to discriminate among hypotheses for a range of sample sizes (10-1280). We also work through several examples of using data to make inferences on diel activity, and include online vignettes on how to use the Diel.Niche package. We demonstrate how our modelling framework complements other analyses, such as circular kernel density estimators and animal movement modelling. Our aim is to encourage standardization of the language of diel activity and bridge conceptual frameworks and hypotheses in diel research with data and models. Lastly, we hope more research focuses on the ecological and conservation importance of understanding how animals use diel time.


Assuntos
Evolução Biológica , Movimento , Animais , Teorema de Bayes
3.
Proc Natl Acad Sci U S A ; 117(30): 18119-18126, 2020 07 28.
Artigo em Inglês | MEDLINE | ID: mdl-32631981

RESUMO

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.


Assuntos
Mudança Climática , Hibernação , Mamíferos , Estações do Ano , Animais , Demografia , Meio Ambiente , Mortalidade , Dinâmica Populacional
4.
Am Nat ; 200(4): 556-570, 2022 10.
Artigo em Inglês | MEDLINE | ID: mdl-36150193

RESUMO

AbstractCurrent methods to model species habitat use through space and diel time are limited. Development of such models is critical when considering rapidly changing habitats where species are forced to adapt to anthropogenic change, often by shifting their diel activity across space. We use an occupancy modeling framework to specify the multistate diel occupancy model (MSDOM), which can evaluate species diel activity against continuous response variables that may impact diel activity within and across seasons or years. We used two case studies, fosas in Madagascar and coyotes in Chicago, Illinois, to conceptualize the application of this model and to quantify the impacts of human activity on species spatial use in diel time. We found support that both species varied their habitat use by diel states-in and across years and by human disturbance. Our results exemplify the importance of understanding animal diel activity patterns and how human disturbance can lead to temporal habitat loss. The MSDOM will allow more focused attention in ecology and evolution studies on the importance of the short temporal scale of diel time in animal-habitat relationships and lead to improved habitat conservation and management.


Assuntos
Ecologia , Ecossistema , Animais , Atividades Humanas , Humanos , Estações do Ano
5.
Ecol Appl ; 32(7): e2639, 2022 10.
Artigo em Inglês | MEDLINE | ID: mdl-35443093

RESUMO

Reduced food availability is implicated in declines in avian aerial insectivores, but the effect of nutritional stress on mammalian aerial insectivores is unclear. Unlike birds, insectivorous bats provision their young through lactation, which might protect nursing juveniles when prey availability is low but could increase the energetic burden on lactating females. We analyzed a 15-year capture-mark-recapture data set from 5312 individual little brown myotis (Myotis lucifugus) captured at 11 maternity colonies in northwestern Canada, to test the hypothesis that nutritional stress is impacting these mammalian aerial insectivores. We used long-bone (forearm [FA]) length as a proxy for relative access to nutrition during development, and body mass as a proxy for access to nutrition prior to capture. Average FA length and body mass both decreased significantly over the study period in adult females and juveniles, suggesting decreased access to nutrition. Effect sizes were very small, similar to those reported for declining body size in avian aerial insectivores. Declines in juvenile body mass were only observed in individuals captured in late summer when they were foraging independently, supporting our hypothesis that lactation provides some protection to nursing young during periods of nutritional stress. Potential drivers of the decline in bat size include one or both of (1) declining insect (prey) abundance, and (2) declining prey availability. Echolocating insectivorous bats cannot forage effectively during rainfall, which is increasing in our study area. The body mass of captured adult females and juveniles in our study was lower, on average, after periods of high rainfall, and higher after warmer-than-average periods. Finally, survival models revealed a positive association between FA length and survival, suggesting a fitness consequence to declines in body size. Our study area has not yet been impacted by bat white-nose syndrome (WNS), but research elsewhere has suggested that fatter bats are more likely to survive infection. We found evidence for WNS-independent shifts in the body size of little brown myotis, which can inform studies investigating population responses to WNS. More broadly, the cumulative effects of multiple stressors (e.g., disease, nutritional stress, climate change, and other pressures) on mammalian aerial insectivores require urgent attention.


Assuntos
Quirópteros , Animais , Tamanho Corporal , Canadá , Quirópteros/fisiologia , Feminino , Humanos , Lactação , Gravidez , Estações do Ano
6.
Ecol Appl ; 32(1): e02470, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34626518

RESUMO

Habitat selection is a fundamental animal behavior that shapes a wide range of ecological processes, including animal movement, nutrient transfer, trophic dynamics and population distribution. Although habitat selection has been a focus of ecological studies for decades, technological, conceptual and methodological advances over the last 20 yr have led to a surge in studies addressing this process. Despite the substantial literature focused on quantifying the habitat-selection patterns of animals, there is a marked lack of guidance on best analytical practices. The conceptual foundations of the most commonly applied modeling frameworks can be confusing even to those well versed in their application. Furthermore, there has yet to be a synthesis of the advances made over the last 20 yr. Therefore, there is a need for both synthesis of the current state of knowledge on habitat selection, and guidance for those seeking to study this process. Here, we provide an approachable overview and synthesis of the literature on habitat-selection analyses (HSAs) conducted using selection functions, which are by far the most applied modeling framework for understanding the habitat-selection process. This review is purposefully non-technical and focused on understanding without heavy mathematical and statistical notation, which can confuse many practitioners. We offer an overview and history of HSAs, describing the tortuous conceptual path to our current understanding. Through this overview, we also aim to address the areas of greatest confusion in the literature. We synthesize the literature outlining the most exciting conceptual advances in the field of habitat-selection modeling, discussing the substantial ecological and evolutionary inference that can be made using contemporary techniques. We aim for this paper to provide clarity for those navigating the complex literature on HSAs while acting as a reference and best practices guide for practitioners.


Assuntos
Comportamento Animal , Ecossistema , Animais , Coleta de Dados , Ecologia/métodos , Movimento
7.
Folia Primatol (Basel) ; 92(1): 12-34, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33171471

RESUMO

Ranging behavior is one important strategy by which nonhuman primates obtain access to resources critical to their biological maintenance and reproductive success. As most primates live in permanent social groups, their members must balance the benefits of group living with the costs of intragroup competition for resources. However, some taxa live in more spatiotemporally flexible social groups, whose members modify patterns of association and range use as a method to mitigate these costs. Here, we describe the range use of one such taxon, the black-and-white ruffed lemur (Varecia variegata), at an undisturbed primary rain forest site in Ranomafana National Park, Madagascar, and characterize sex differences in annual home range area, overlap, and daily distances traveled. Moreover, we characterize seasonal variability in range use and ask whether ranging behaviors can be explained by either climatic or reproductive seasonality. We found that females used significantly larger home ranges than males, though sexes shared equal and moderate levels of home range overlap. Overall, range use did not vary across seasons, although within sexes, male range use varied significantly with climate. Moreover, daily path length was best predicted by day length, female reproductive state, and sex, but was unrelated to climate variables. While the patterns of range use and spatial association presented here share some similarities with "bisexually bonded" community models described for chimpanzees, we argue that ruffed lemurs best conform to a "nuclear neighborhood" community model wherein nuclear (core) groups share the highest levels of home range overlap, and where these groups cluster spatially into adjacent "neighborhoods" within the larger, communally defended territory.


Assuntos
Comportamento de Retorno ao Território Vital , Lemuridae/fisiologia , Caracteres Sexuais , Animais , Feminino , Madagáscar , Masculino , Reprodução/fisiologia , Estações do Ano , Comportamento Social , Tempo (Meteorologia)
8.
Ecol Appl ; 28(5): 1325-1341, 2018 07.
Artigo em Inglês | MEDLINE | ID: mdl-29696712

RESUMO

Conservation and management decision making in natural resources is challenging due to numerous uncertainties and unknowns, especially relating to understanding system dynamics. Adaptive resource management (ARM) is a formal process to making logical and transparent recurrent decisions when there are uncertainties about system dynamics. Despite wide recognition and calls for implementing adaptive natural resource management, applications remain limited. More common is a reactive approach to decision making, which ignores future system dynamics. This contrasts with ARM, which anticipates future dynamics of ecological process and management actions using a model-based framework. Practitioners may be reluctant to adopt ARM because of the dearth of comparative evaluations between ARM and more common approaches to making decisions. We compared the probability of meeting management objectives when managing a population under both types of decision frameworks, specifically in relation to typical uncertainties and unknowns. We use a population of Sandhill Cranes as our case study. We evaluate each decision process under varying levels of monitoring and ecological uncertainty, where the true underlying population dynamics followed a stochastic age-structured population model with environmentally driven vital rate density dependence. We found that the ARM framework outperformed the currently employed reactive decision framework to manage Sandhill Cranes in meeting the population objective across an array of scenarios. This was even the case when the candidate set of population models contained only naïve representations of the true population process. Under the reactive decision framework, we found little improvement in meeting the population objective even if monitoring uncertainty was eliminated. In contrast, if the population was monitored without error within the ARM framework, the population objective was always maintained, regardless of the population models considered. Contrary to expectation, we found that age-specific optimal harvest decisions are not always necessary to meet a population objective when population dynamics are age structured. Population managers can decrease risks and gain transparency and flexibility in management by adopting an ARM framework. If population monitoring data has high sampling variation and/or limited empirical knowledge is available for constructing mechanistic population models, ARM model sets should consider a range of mechanistic, descriptive, and predictive model types.


Assuntos
Aves , Conservação dos Recursos Naturais , Tomada de Decisões , Incerteza , Animais , Modelos Biológicos , Noroeste dos Estados Unidos , Dinâmica Populacional , Sudoeste dos Estados Unidos
9.
Ecol Appl ; 25(3): 695-705, 2015 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-26214915

RESUMO

Abundance and density of wild animals are important ecological metrics. However, estimating either is fraught with challenges; spatial capture-recapture (SCR) models are a relatively new class of models that attempt to ameliorate common challenges, providing a statistically coherent framework to estimate abundance and density. SCR models are increasingly being used in ecological and conservation studies of mammals worldwide, but have received little testing with empirical field data. We use data collected via a web and grid sampling design to evaluate the basic SCR model where small-mammal abundance (N) and density (D) are known (via exhaustive sampling). We fit the basic SCR model with and without a behavioral effect to 11 small-mammal populations for each sampling design using a Bayesian and likelihood SCR modeling approach. We compare SCR and ad hoc density estimators using frequentist performance measures. We found Bayesian and likelihood SCR estimates of density (D) and abundance (N) to be similar. We also found SCR models to have moderately poor frequentist coverage of D and N (45-73%), high deviation from truth (i.e., accuracy; D, 17-29%; N, 16-29%), and consistent negative bias across inferential paradigms, sampling designs, and models. With the trapping grid data, the basic SCR model generally performed more poorly than the best ad hoc estimator (behavior CR super-population estimate divided by the full mean maximum distance moved estimate of the effective trapping area), whereas with the trapping web data, the best-performing SCR model (null) was comparable to the best distance model. Relatively poor frequentist SCR coverage resulted from higher precision (SCR coefficients of variation [CVs] < ad hoc CVs); however D and D were fairly well correlated (r2 range of 0.77-0.96). SCR's negative relative bias (i.e., average underestimation of the true density) suggests additional heterogeneity in detection and/or that small mammals maintained asymmetric home ranges. We suggest caution in the use of the basic SCR model when trapping animals in a sampling grid and more generally when small sample sizes necessitate the spatial scale parameter (σ) apply to all individuals. When possible, researchers should consider variation in detection and incorporate individual biological and/or ecological variation at the trap level when modeling σ.


Assuntos
Modelos Biológicos , Roedores/fisiologia , Animais , Teorema de Bayes , Tamanho Corporal , Modelos Estatísticos , Densidade Demográfica
10.
J Anim Ecol ; 84(5): 1299-310, 2015 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-25808951

RESUMO

1. Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. 2. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. 3. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring-summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. 4. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. 5. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.


Assuntos
Aves/fisiologia , Clima , Ecossistema , Animais , Teorema de Bayes , Mudança Climática , Colorado , Modelos Biológicos , Dinâmica Populacional , Análise de Regressão , Estações do Ano
11.
Ecol Evol ; 13(11): e10684, 2023 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-37928195

RESUMO

Anthropogenic developments alter the environment and resources available to wildlife communities. In response to these real or perceived threats from this development, species may adjust their spatial occurrence. Additionally, wildlife species may adjust when in diel time (24-h light-dark cycle) they occupy sites on the landscape to adapt to changing conditions. However, many wildlife studies only focus on where a species does and does not occur, ignoring how species may shift their diel activity at sites to mitigate threats. We used a multi-state diel occupancy modeling framework to investigate how a community of mammals (mesocarnivores, urban-adapted omnivores, and herbivore/small mammals) respond to differing levels of anthropogenic development and forest cover across two climatic seasons. We collected camera trap data at 240 survey locations across the summer and winter of 2021-2022. We modeled multi-state diel occupancy for 14 mammal species with extent of development/forest and season hypothesized to influence diel occupancy and season hypothesized to influence the probability of detection. We found that all species displayed heterogeneity in both diel occupancy and detection either by extent of development/forest and or season. Within the mesocarnivore species group, coyote and red fox were less sensitive to development and had higher occupancy probability at these sites in general but used them more during the night, while more sensitive mesocarnivores including fisher and bobcat occupied the day state only when there was increasing forest cover. Our results highlight the importance of incorporating diel activity in habitat modeling to better understand the relationship between a species and its landscape, particularly in a region that is vulnerable to increased anthropogenic pressure.

12.
Vaccine ; 40(17): 2478-2483, 2022 04 14.
Artigo em Inglês | MEDLINE | ID: mdl-34865873

RESUMO

BACKGROUND: In December 2019, we ran Pacific Eclipse, a pandemic tabletop exercise using smallpox originating in Fiji as a case study. Pacific Eclipse brought together international stakeholders from health, defence, law enforcement, emergency management and a range of other organisations. AIM: To review potential gaps in preparedness and identify modifiable factors which could prevent a pandemic or mitigate the impact of a pandemic. METHODS: Pacific Eclipse was held on December 9-10 in Washington DC, Phoenix and Honolulu simultaneously. The scenario began in Fiji and becomes a pandemic. Mathematical modelling of smallpox transmission was used to simulate the epidemic under different conditions and to test the effect of interventions. Live polling, using Poll Everywhere software that participants downloaded onto their smart phones, was used to gather participant decisions as the scenario unfolded. Stakeholders from state and federal government and non-government organisations from The United States, The United Kingdom, Australia, New Zealand, Canada, as well as industry and non-government organisations attended. RESULTS: The scenario progressed in three phases and participants were able to make decisions during each phase using live polling. The polling showed very diverse and sometimes conflicting decision making. Factors influential to pandemic severity were identified and categorised as modifiable or unmodifiable. A series of recommendations were made on the modifiable determinants of pandemic severity and how these can be incorporated into pandemic planning. These included preventing an attack through intelligence, law enforcement and legislation, improved speed of diagnosis, speed and completeness of case finding and case isolation, speed and security of vaccination response (including stockpiling), speed and completeness of contact tracing, protecting critical infrastructure and business continuity, non-pharmaceutical interventions (social distancing, PPE, border control) and protecting first responders. DISCUSSION: Pacific Eclipse illustrated the impact of a pandemic of smallpox under different response scenarios, which were validated to some extent by the COVID-19 pandemic. The framework developed from the scenario draws out modifiable determinants of pandemic severity which can inform pandemic planning for the ongoing COVID-19 pandemic and for future pandemics.


Assuntos
COVID-19 , Varíola , Vírus da Varíola , COVID-19/epidemiologia , COVID-19/prevenção & controle , Busca de Comunicante , Humanos , Pandemias/prevenção & controle , Varíola/epidemiologia , Varíola/prevenção & controle , Estados Unidos
13.
Nat Ecol Evol ; 6(6): 709-719, 2022 06.
Artigo em Inglês | MEDLINE | ID: mdl-35484222

RESUMO

In many regions of the world, forest management has reduced old forest and simplified forest structure and composition. We hypothesized that such forest degradation has resulted in long-term habitat loss for forest-associated bird species of eastern Canada (130,017 km2) which, in turn, has caused bird-population declines. Despite little change in overall forest cover, we found substantial reductions in old forest as a result of frequent clear-cutting and a broad-scale transformation to intensified forestry. Back-cast species distribution models revealed that breeding habitat loss occurred for 66% of the 54 most common species from 1985 to 2020 and was strongly associated with reduction in old age classes. Using a long-term, independent dataset, we found that habitat amount predicted population size for 94% of species, and habitat loss was associated with population declines for old-forest species. Forest degradation may therefore be a primary cause of biodiversity decline in managed forest landscapes.


Assuntos
Ecossistema , Florestas , Animais , Biodiversidade , Aves , Agricultura Florestal
14.
Elife ; 112022 03 31.
Artigo em Inglês | MEDLINE | ID: mdl-35357308

RESUMO

Time is a fundamental component of ecological processes. How animal behavior changes over time has been explored through well-known ecological theories like niche partitioning and predator-prey dynamics. Yet, changes in animal behavior within the shorter 24-hr light-dark cycle have largely gone unstudied. Understanding if an animal can adjust their temporal activity to mitigate or adapt to environmental change has become a recent topic of discussion and is important for effective wildlife management and conservation. While spatial habitat is a fundamental consideration in wildlife management and conservation, temporal habitat is often ignored. We formulated a temporal resource selection model to quantify the diel behavior of 8 mammal species across 10 US cities. We found high variability in diel activity patterns within and among species and species-specific correlations between diel activity and human population density, impervious land cover, available greenspace, vegetation cover, and mean daily temperature. We also found that some species may modulate temporal behaviors to manage both natural and anthropogenic risks. Our results highlight the complexity with which temporal activity patterns interact with local environmental characteristics, and suggest that urban mammals may use time along the 24-hr cycle to reduce risk, adapt, and therefore persist, and in some cases thrive, in human-dominated ecosystems.


Assuntos
Ecossistema , Urbanização , Animais , Cidades , Mamíferos , Densidade Demográfica
15.
Ecology ; 103(6): e3687, 2022 06.
Artigo em Inglês | MEDLINE | ID: mdl-35315058

RESUMO

Madagascar is a threatened global biodiversity hotspot and conservation priority, yet we lack broad-scale surveys to assess biodiversity across space and time. To fill this gap, we collated camera trap surveys, capturing species occurrences within Madagascar into a single standardized database. This data set includes nine distinct protected areas of Madagascar and encompasses 13 subprojects, 38 camera arrays, and 1156 sampling units (independent camera site per survey) within two important biodiversity eco-regions: western dry deciduous forest and eastern humid rainforest. Camera surveys were conducted from June 2007 to January 2021. The final data set includes 17 unique families of mammals (Bovidae, Canidae, Cheirogaleidae, Daubentoniidae, Equidae, Eupleridae, Felidae, Hominidae, Indriidae, Lemuridae, Lepilemuridae, Muridae, Nesomyidae, Pteropodidae, Soricidae, Suidae, Tenrecidae) comprising 45 species and 27 unique families of birds (Accipitridae, Acrocephalidae, Alcedinidae, Bernieridae, Brachypteraciidae, Caprimulgidae, Cisticolidae, Columbidae, Coraciidae, Corvidae, Cuculidae, Dicruridae, Mesitornithidae, Monarchidae, Motacillidae, Muscicapidae, Numididae, Phasianidae, Rallidae, Sarothruridae, Strigidae, Sturnidae, Sulidae, Threskiornithidae, Upupidae, Vangidae, Zosteropidae) comprising 58 species. Images were processed and verified by individual project data set creators and camera operation and species tables were then collated. The final product represents the first broad-scale freely available standardized formal faunal database for Madagascar. Data are available through this publication and at DOI: 10.5281/zenodo.5801806. These data will be useful for examining species-level and community-level trends in occurrence across space or time within Madagascar and globally, evaluating native and invasive species dynamics, and will aid in determining species conservation status and planning for at-risk species. There are no copyright restrictions; please cite this paper when using the data for publication.


Assuntos
Biodiversidade , Florestas , Animais , Aves , Humanos , Madagáscar/epidemiologia , Mamíferos , Suínos
16.
Int J Infect Dis ; 106: 199-207, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33771668

RESUMO

OBJECTIVES: To determine patterns of mask wearing and other infection prevention behaviours, over two time periods of the COVID-19 pandemic, in cities where mask wearing was not a cultural norm. METHODS: A cross-sectional survey of masks and other preventive behaviours in adults aged ≥18 years was conducted in five cities: Sydney and Melbourne, Australia; London, UK; and Phoenix and New York, USA. Data were analysed according to the epidemiology of COVID-19, mask mandates and a range of predictors of mask wearing. RESULTS: The most common measures used were avoiding public areas (80.4%), hand hygiene (76.4%), wearing masks (71.8%) and distancing (67.6%). Over 40% of people avoided medical facilities. These measures decreased from March-July 2020. Pandemic fatigue was associated with younger age, low perceived severity of COVID-19 and declining COVID-19 prevalence. Predictors of mask wearing were location (US, UK), mandates, age <50 years, education, having symptoms and knowing someone with COVID-19. Negative experiences with mask wearing and low perceived severity of COVID-19 reduced mask wearing. Most respondents (98%) believed that hand washing and distancing were necessary, and 80% reported no change or stricter adherence to these measures when wearing masks. CONCLUSION: Pandemic mitigation measures were widely reported across all cities, but decreased between March and July 2020. Pandemic fatigue was more common in younger people. Cities with mandates had higher rates of mask wearing. Promotion of mask use for older people may be useful. Masks did not result in a reduction of other hygiene measures.


Assuntos
COVID-19/prevenção & controle , COVID-19/psicologia , Controle de Doenças Transmissíveis/métodos , Máscaras/estatística & dados numéricos , Adulto , Austrália/epidemiologia , Cidades/epidemiologia , Estudos Transversais , Feminino , Humanos , Masculino , Programas Obrigatórios , Máscaras/virologia , Pessoa de Meia-Idade , SARS-CoV-2 , Reino Unido/epidemiologia , Estados Unidos/epidemiologia , Adulto Jovem
17.
Ecology ; 101(3): e02953, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31840242

RESUMO

Resource selection is often studied by ecologists interested in the environmental drivers of animal space use and movement. These studies commonly produce spatial predictions, which are of considerable utility to resource managers making habitat and population management decisions. It is thus paramount that predictions from resource selection studies are accurate. We evaluated model building and fitting strategies for optimizing resource selection function predictions in a use-availability framework. We did so by simulating low- and high-intensity spatial sampling data that respectively predicted study area and movement-based resource selection. We compared one of the most commonly used forms of statistical regularization, Akaike's Information Criterion (AIC), with the lesser used least absolute shrinkage and selection operator (LASSO). LASSO predictions were less variable and more accurate than AIC and were often best when considering additive and interacting variables. We explicitly demonstrate the predictive equivalence using the logistic and Poisson likelihoods and how it is lost when the available sample is too small. Regardless of modeling approach, interpreting the sign of coefficients as a measure of selection can be misleading when optimizing for prediction.


Assuntos
Ecossistema , Modelos Biológicos , Animais , Tomada de Decisões , Movimento
18.
PLoS One ; 14(2): e0212346, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30735552

RESUMO

[This corrects the article DOI: 10.1371/journal.pone.0192819.].

19.
PLoS One ; 13(2): e0192819, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29481554

RESUMO

Understanding patterns of species occurrence and the processes underlying these patterns is fundamental to the study of ecology. One of the more commonly used approaches to investigate species occurrence patterns is occupancy modeling, which can account for imperfect detection of a species during surveys. In recent years, there has been a proliferation of Bayesian modeling in ecology, which includes fitting Bayesian occupancy models. The Bayesian framework is appealing to ecologists for many reasons, including the ability to incorporate prior information through the specification of prior distributions on parameters. While ecologists almost exclusively intend to choose priors so that they are "uninformative" or "vague", such priors can easily be unintentionally highly informative. Here we report on how the specification of a "vague" normally distributed (i.e., Gaussian) prior on coefficients in Bayesian occupancy models can unintentionally influence parameter estimation. Using both simulated data and empirical examples, we illustrate how this issue likely compromises inference about species-habitat relationships. While the extent to which these informative priors influence inference depends on the data set, researchers fitting Bayesian occupancy models should conduct sensitivity analyses to ensure intended inference, or employ less commonly used priors that are less informative (e.g., logistic or t prior distributions). We provide suggestions for addressing this issue in occupancy studies, and an online tool for exploring this issue under different contexts.


Assuntos
Teorema de Bayes , Ecologia/métodos , Modelos Biológicos , Animais , Aves , Simulação por Computador , Funções Verossimilhança , Modelos Logísticos , Dinâmica Populacional
20.
Mov Ecol ; 6: 14, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30062012

RESUMO

BACKGROUND: Characterizing animal space use is critical for understanding ecological relationships. Animal telemetry technology has revolutionized the fields of ecology and conservation biology by providing high quality spatial data on animal movement. Radio-telemetry with very high frequency (VHF) radio signals continues to be a useful technology because of its low cost, miniaturization, and low battery requirements. Despite a number of statistical developments synthetically integrating animal location estimation and uncertainty with spatial process models using satellite telemetry data, we are unaware of similar developments for azimuthal telemetry data. As such, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models.We developed a hierarchical modeling framework to provide robust animal location estimates from one or more intersecting or non-intersecting azimuths. We used our azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into spatial ecological models. We evaluate the ATM with commonly used estimators (Lenth (1981) maximum likelihood and M-Estimators) using simulation. We also provide illustrative empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We further use simulation to better understand the relationship among location uncertainty, spatial covariate autocorrelation, and resource selection inference. RESULTS: We found the ATM to have good performance in estimating locations and the only model that has appropriate measures of coverage. Ignoring animal location uncertainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. Home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Furthermore, our simulation study clarified that incorporating location uncertainty helps reduce bias in resource selection coefficients across all levels of covariate spatial autocorrelation. CONCLUSION: The ATM can accommodate one or more azimuths when estimating animal locations, regardless of how they intersect; this ensures that all data collected are used for ecological inference. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies.

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