Niche tracking and rapid establishment of distributional equilibrium in the house sparrow show potential responsiveness of species to climate change.

The ability of species to respond to novel future climates is determined in part by their physiological capacity to tolerate climate change and the degree to which they have reached and continue to maintain distributional equilibrium with the environment. While broad-scale correlative climatic measurements of a species' niche are often described as estimating the fundamental niche, it is unclear how well these occupied portions actually approximate the fundamental niche per se, versus the fundamental niche that exists in environmental space, and what fitness values bounding the niche are necessary to maintain distributional equilibrium. Here, we investigate these questions by comparing physiological and correlative estimates of the thermal niche in the introduced North American house sparrow (Passer domesticus). Our results indicate that occupied portions of the fundamental niche derived from temperature correlations closely approximate the centroid of the existing fundamental niche calculated on a fitness threshold of 50% population mortality. Using these niche measures, a 75-year time series analysis (1930-2004) further shows that: (i) existing fundamental and occupied niche centroids did not undergo directional change, (ii) interannual changes in the two niche centroids were correlated, (iii) temperatures in North America moved through niche space in a net centripetal fashion, and consequently, (iv) most areas throughout the range of the house sparrow tracked the existing fundamental niche centroid with respect to at least one temperature gradient. Following introduction to a new continent, the house sparrow rapidly tracked its thermal niche and established continent-wide distributional equilibrium with respect to major temperature gradients. These dynamics were mediated in large part by the species' broad thermal physiological tolerances, high dispersal potential, competitive advantage in human-dominated landscapes, and climatically induced changes to the realized environmental space. Such insights may be used to conceptualize mechanistic climatic niche models in birds and other taxa

Lazarus ecology: Recovering the distribution and migratory patterns of the extinct Carolina parakeet.

The study of the ecology and natural history of species has traditionally ceased when a species goes extinct, despite the benefit to current and future generations of potential findings. We used the extinct Carolina parakeet as a case study to develop a framework investigating the distributional limits, subspecific variation, and migratory habits of this species as a means to recover important information about recently extinct species. We united historical accounts with museum collections to develop an exhaustive, comprehensive database of every known occurrence of this once iconic species. With these data, we combined species distribution models and ordinal niche comparisons to confront multiple conjectured hypotheses about the parakeet's ecology with empirical data on where and when this species occurred. Our results demonstrate that the Carolina parakeet's range was likely much smaller than previously believed, that the eastern and western subspecies occupied different climatic niches with broad geographical separation, and that the western subspecies was likely a seasonal migrant while the eastern subspecies was not. This study highlights the novelty and importance of collecting occurrence data from published observations on extinct species, providing a starting point for future investigations of the factors that drove the Carolina parakeet to extinction. Moreover, the recovery of lost autecological knowledge could benefit the conservation of other parrot species currently in decline and would be crucial to the success of potential de-extinction efforts for the Carolina parakeet

Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset.

Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1-10 cameras), and (2) by total season length (1-365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40-128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify target species for which inference will be made, and then design camera trapping studies around the most difficult to detect of those species

Co-occurrence of invasive and native carnivorans affects occupancy patterns across environmental gradients

Understanding species interactions and their effects on distributions is crucial for assessing the impacts of global change, particularly for invasive species. Co-occurrence models can help investigate these effects when interactions are likely given shared traits. For such an assemblage of invasive and native carnivorans, we examined how patterns of co-occurrence change across space and environmental gradients using a static multispecies occupancy model that accounts for imperfect detectability and models co-occurrence as a function of environmental variables, and also extended it to be temporally dynamic. We focused on invasive raccoons, which pose threats to humans and wildlife globally. In Japan, raccoons prey on many native taxa, but little is known about interactions with sympatric carnivorans. We searched for signals of competitive exclusion of native raccoon dogs (tanuki) and invasive masked palm civets by applying the model to detection data from a broad-scale trapping effort over 6 years. Forest cover was the strongest predictor of occupancy for individual species and raccoon co-occurrences, and raccoon occupancy probability increased with forest cover conditionally depending on the co-occurring carnivoran: only tanuki absence or civet presence had positive responses. However, tanuki occupancy probability increased with forest cover despite any co-occurrence. Thus, we found no evidence of competitive exclusion by raccoons, contrary to our expectations. As parts of the world with invasive raccoons can also have invasive tanuki, our findings may have broad management implications. The model we present should be useful for inferring signals of biotic interactions between species with low detectability over multi-year time frames

Opportunities and challenges for big data ornithology

Recent advancements in information technology and data acquisition have created both new research opportunities and new challenges for using big data in ornithology. We provide an overview of the past, present, and future of big data in ornithology, and explore the rewards and risks associated with their application. Structured data resources (e.g., North American Breeding Bird Survey) continue to play an important role in advancing our understanding of bird population ecology, and the recent advent of semistructured (e.g., eBird) and unstructured (e.g., weather surveillance radar) big data resources has promoted the development of new empirical perspectives that are generating novel insights. For example, big data have been used to study and model bird diversity and distributions across space and time, explore the patterns and determinants of broad-scale migration strategies, and examine the dynamics and mechanisms associated with geographic and phenological responses to global change. The application of big data also holds a number of challenges wherein high data volume and dimensionality can result in noise accumulation, spurious correlations, and incidental endogeneity. In total, big data resources continue to add empirical breadth and detail to ornithology, often at very broad spatial extents, but how the challenges underlying this approach can best be mitigated to maximize inferential quality and rigor needs to be carefully considered. Los avances recientes en la tecnolog´ıa de la informaci ´on y la adquisici ´on de datos han creado tanto nuevas oportunidades de investigaci ´on como desaf´ıos para el uso de datos masivos (big data) en ornitolog´ıa. Brindamos una visi ´on general del pasado, presente y futuro de los datos masivos en ornitolog´ıa y exploramos las recompensas y desaf´ıos asociados a su aplicaci ´ on. Los recursos de datos estructurados (e.g., Muestreo de Aves Reproductivas de Am´erica del Norte) siguen jugando un rol importante en el avance de nuestro entendimiento de la ecolog´ıa de poblaciones de las aves, y el advenimiento reciente de datos masivos semi-estructurados (e.g., eBird) y desestructurados (e.g., radar de vigilancia clima´tica) han promovido el desarrollo de nuevas perspectivas emp´ıricas que esta´n generando miradas novedosas. Por ejemplo, los datos masivos han sido usados para estudiar y modelar la diversidad y distribuci ´on de las aves a trav´es del tiempo y del espacio, explorar los patrones y los determinantes de las estrategias de migraci ´on a gran escala, y examinar las dina´micas y los mecanismos asociados con las respuestas geogra´ficas y fenol ´ ogicas al cambio global. La aplicaci ´on de datos masivos tambi´en contiene una serie de desaf´ıos donde el gran volumen de datos y la dimensionalidad pueden generar una acumulaci ´on de ruido, correlaciones espurias y endogeneidad incidental. En total, los recursos de datos masivos contin ´uan agregando amplitud y detalle emp´ırico a la ornitolog´ıa, usualmente a escalas espaciales muy amplias, pero necesita considerarse cuidadosamente c ´omo los desaf´ıos que subyacen este enfoque pueden ser mitigados del mejor modo para maximizar su calidad inferencial y rigor

Addressing data integration challenges to link ecological processes across scales

Data integration is a statistical modeling approach that incorporates multiple data sources within a unified analytical framework. Macrosystems ecology – the study of ecological phenomena at broad scales, including interactions across scales – increasingly employs data integration techniques to expand the spatiotemporal scope of research and inferences, increase the precision of parameter estimates, and account for multiple sources of uncertainty in estimates of multiscale processes. We highlight four common analytical challenges to data integration in macrosystems ecology research: data scale mismatches, unbalanced data, sampling biases, and model development and assessment. We explain each problem, discuss current approaches to address the issue, and describe potential areas of research to overcome these hurdles. Use of data integration techniques has increased rapidly in recent years, and given the inferential value of such approaches, we expect continued development and wider application across ecological disciplines, especially in macrosystems ecology

Differential response of three large mammal species to human recreation in the Rocky Mountains of Colorado, USA

Outdoor recreation benefits local economies, environmental education, and public health and wellbeing, but it can also adversely affect local ecosystems. Human presence in natural areas alters feeding and reproductive behaviors, physiology, and population structure in many wildlife species, often resulting in cascading effects through entire ecological communities. As outdoor recreation gains popularity, existing trails are becoming overcrowded and new trails are being built to accommodate increasing use. Many recreation impact studies have investigated effects of the presence or absence of humans while few have investigated recreation effects on wildlife using a gradient of disturbance intensity. We used camera traps to quantify trail use by humans and mid- to large-sized mammals in an area of intense outdoor recreation–the Upper East River Valley, Colorado, USA. We selected five trails with different types and intensities of human use and deployed six cameras on each trail for five weeks during a COVID-enhanced 2020 summer tourism season. We used occupancy models to estimate detectability and habitat use of the three most common mammal species in the study area and determined which human activities affect the habitat use patterns of each species. Human activities affected each species differently. Mule deer (Odocoileus hemionus) tended to use areas with more vehicles, more predators, and greater distances from the trailhead, and they were more likely to be detected where there were more bikers. Coyotes (Canis latrans) and red foxes (Vulpes vulpes) were most likely to use areas where their prey species occurred, and foxes were more likely to be detected where the vegetation was shorter. Humans and their recreational activities differentially influence different species. More generally, these results reinforce that it is unlikely that a single management policy is suitable for all species and management should thus be tailored for each target species

Fire and biodiversity in the Anthropocene

The workshop leading to this paper was funded by the Centre Tecnològic Forestal de Catalunya and the ARC Centre of Excellence for Environmental Decisions. L.T.K. was supported by a Victorian Postdoctoral Research Fellowship (Victorian Government), a Centenary Fellowship (University of Melbourne), and an Australian Research Council Linkage Project Grant (LP150100765). A.R. was supported by the Xunta de Galicia (Postdoctoral Fellowship ED481B2016/084-0) and the Foundation for Science and Technology under the FirESmart project (PCIF/MOG/0083/2017). A.L.S. was supported by a Marie Skłodowska-Curie Individual Fellowship (746191) under the European Union Horizon 2020 Programme for Research and Innovation. L.R. was supported by the Australian Government’s National Environmental Science Program through the Threatened Species Recovery Hub. L.B. was partially supported by the Spanish Government through the INMODES (CGL2014-59742-C2-2-R) and the ERANET-SUMFORESTS project FutureBioEcon (PCIN-2017-052). This research was supported in part by the U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station.BACKGROUND Fire has shaped the diversity of life on Earth for millions of years. Variation in fire regimes continues to be a source of biodiversity across the globe, and many plants, animals, and ecosystems depend on particular temporal and spatial patterns of fire. Although people have been using fire to modify environments for millennia, the combined effects of human activities are now changing patterns of fire at a global scale—to the detriment of human society, biodiversity, and ecosystems. These changes pose a global challenge for understanding how to sustain biodiversity in a new era of fire. We synthesize how changes in fire activity are threatening species with extinction across the globe, highlight forward-looking methods for predicting the combined effects of human drivers and fire on biodiversity, and foreshadow emerging actions and strategies that could revolutionize how society manages fire for biodiversity in the Anthropocene. ADVANCES Our synthesis shows that interactions with anthropogenic drivers such as global climate change, land use, and biotic invasions are transforming fire activity and its impacts on biodiversity. More than 4400 terrestrial and freshwater species from a wide range of taxa and habitats face threats associated with modified fire regimes. Many species are threatened by an increase in fire frequency or intensity, but exclusion of fire in ecosystems that need it can also be harmful. The prominent role of human activity in shaping global ecosystems is the hallmark of the Anthropocene and sets the context in which models and actions must be developed. Advances in predictive modeling deliver new opportunities to couple fire and biodiversity data and to link them with forecasts of multiple drivers including drought, invasive plants, and urban growth. Making these connections also provides an opportunity for new actions that could revolutionize how society manages fire. Emerging actions include reintroduction of mammals that reduce fuels, green fire breaks comprising low-flammability plants, strategically letting wildfires burn under the right conditions, managed evolution of populations aided by new genomics tools, and deployment of rapid response teams to protect biodiversity assets. Indigenous fire stewardship and reinstatement of cultural burning in a modern context will enhance biodiversity and human well-being in many regions of the world. At the same time, international efforts to reduce greenhouse gas emissions are crucial to reduce the risk of extreme fire events that contribute to declines in biodiversity. OUTLOOK Conservation of Earth’s biological diversity will be achieved only by recognition of and response to the critical role of fire in shaping ecosystems. Global changes in fire regimes will continue to amplify interactions between anthropogenic drivers and create difficult trade-offs between environmental and social objectives. Scientific input will be crucial for navigating major decisions about novel and changing ecosystems. Strategic collection of data on fire, biodiversity, and socioeconomic variables will be essential for developing models to capture the feedbacks, tipping points, and regime shifts characteristic of the Anthropocene. New partnerships are also needed to meet the challenges ahead. At the local and regional scale, getting more of the “right” type of fire in landscapes that need it requires new alliances and networks to build and apply knowledge. At the national and global scale, biodiversity conservation will benefit from greater integration of fire into national biodiversity strategies and action plans and in the implementation of international agreements and initiatives such as the UN Convention on Biological Diversity. Placing the increasingly important role of people at the forefront of efforts to understand and adapt to changes in fire regimes is central to these endeavors.PostprintPeer reviewe

A Survey of Experimental Research on Contests, All-Pay Auctions and Tournaments

Many economic, political and social environments can be described as contests in which agents exert costly efforts while competing over the distribution of a scarce resource. These environments have been studied using Tullock contests, all-pay auctions and rankorder tournaments. This survey provides a review of experimental research on these three canonical contests. First, we review studies investigating the basic structure of contests, including the contest success function, number of players and prizes, spillovers and externalities, heterogeneity, and incomplete information. Second, we discuss dynamic contests and multi-battle contests. Then we review research on sabotage, feedback, bias, collusion, alliances, and contests between groups, as well as real-effort and field experiments. Finally, we discuss applications of contests to the study of legal systems, political competition, war, conflict avoidance, sales, and charities, and suggest directions for future research. (author's abstract