Anthropogenic pressures have altered fire regimes across the western United States. These altered fire regimes, and the megafires they often produce, threaten ecologically and economically critical ecosystems and biodiversity across this region. Oak woodland savannas may be particularly sensitive to altered fire regimes, but there remains a significant gap in our understanding of how different characteristics of wildfire impact these ecosystems and the wildlife species that reside within them. In this study, we used an occupancy modeling framework to investigate how fire severity and pyrodiversity, the diversity of severity patches, impact the distributions of bird and bat species assemblages following a major wildfire in northern California. We used acoustic monitors deployed across the Hopland Research and Extension Center following the 2018 Mendocino Complex Fire and compared how patterns of fire severity and pyrodiversity influence habitat preferences across a diverse community of woodland bird and bat species. We found that fire enhances habitat use and increased occupancy for several species and species-groups across both taxonomic groups. Specifically, low to moderate severity fire increased occupancy for several species and species-groups. Pyrodiversity had smaller, negligible effects on species distributions relative to fire severity. Fires that reproduce the natural heterogeneity of oak woodland landscapes are likely key in sustaining high biodiversity across oak woodland ecosystems.

Despite growing evidence of widespread impacts of humans on animal behavior, our understanding of how humans reshape species interactions remains limited. Here, we present a framework that draws on key concepts from behavioral and community ecology to outline four primary pathways by which humans can alter predator-prey spatiotemporal overlap. We suggest that predator-prey dyads can exhibit similar or opposite responses to human activity with distinct outcomes for predator diet, predation rates, population demography, and trophic cascades. We demonstrate how to assess these behavioral response pathways with hypothesis testing, using temporal activity data for 178 predator-prey dyads from published camera trap studies on terrestrial mammals. We found evidence for each of the proposed pathways, revealing multiple patterns of human influence on predator-prey activity and overlap. Our framework and case study highlight current challenges, gaps, and advances in linking human activity to animal behavior change and predator-prey dynamics. By using a hypothesis-driven approach to estimate the potential for altered species interactions, we can anticipate the ecological consequences of human activities on whole communities.

<b>Abstract</b><br/><p>Despite growing evidence of widespread impacts of humans on animal behavior, our understanding of how humans reshape species interactions remains limited. Here, we present a framework that draws on key concepts from behavioral and community ecology to outline four primary pathways by which humans can alter predator-prey spatiotemporal overlap. We suggest that predator-prey dyads can exhibit similar or opposite responses to human activity with distinct outcomes for predator diet, predation rates, population demography, and trophic cascades. We demonstrate how to assess these behavioral response pathways with hypothesis testing, using temporal activity data for 178 predator-prey dyads from published camera trap studies on terrestrial mammals. We found evidence for each of the proposed pathways, revealing multiple patterns of human influence on predator-prey activity and overlap. Our framework and case study highlight current challenges, gaps, and advances in linking human activity to animal behavior change and predator-prey dynamics. By using a hypothesis-driven approach to estimate the potential for altered species interactions, we can anticipate the ecological consequences of human activities on whole communities.</p>

1. Multi-year precipitation ‘legacies’ can have stronger effects on plant community composition than rainfall in the current growing season, but variation in the magnitude of these effects is not fully understood. Direct interactions between plants and animals, such as herbivory, and indirect interactions, such as ecosystem engineering (via changes in the physical environment), may influence precipitation legacies by altering mechanisms of lagged effects. However, the role of direct and indirect plant-animal interactions in determining the strength of precipitation legacies remains largely unexplored. 2. Here, we investigated effects of current growing season rainfall and precipitation legacies on grassland composition, and the influence of herbivory and ecosystem engineering interactions on these temporal dynamics. From 2009 to 2014, a period spanning high and low rainfall, we recorded plant cover in kangaroo rat exclosures and paired control plots that included both burrow and inter-burrow areas. We used linear mixed effects modeling and analysis of community dissimilarities to evaluate plant composition responses to current and previous growing season rainfall and kangaroo rat herbivory (presence of seed foraging) and ecosystem engineering (burrowing). 3. We found that community composition was more strongly affected by precipitation legacies than by current growing season rainfall. Greater precipitation in the previous growing season enhanced grass cover and reduced forb and legume cover. Kangaroo rat trophic and engineering interactions had counteracting effects on these legacies. While burrowing increased grass cover and thereby amplified the effects of previous growing season rainfall on community composition, legacies were suppressed by the presence of kangaroo rat foraging, which decreased grass cover. Further analysis revealed that kangaroo rat foraging and burrowing had conflicting effects on residual plant biomass prior to the growing season, suggesting that precipitation legacies were influenced by altered litter dynamics. 4. Synthesis. Our study demonstrates that animals can impact the strength of precipitation legacies through direct and indirect interactions with the plant species that drive lag effects. The influence of multiple types of plant-animal interactions on precipitation legacies may be important to consider for ecosystem management and when generating predictions of community composition and productivity in future ecosystems.

Climate change is transforming precipitation regimes world-wide. Changes in precipitation regimes are known to have powerful effects on plant productivity, but the consequences of these shifts for the dynamics of ecological communities are poorly understood. This knowledge gap hinders our ability to anticipate and mitigate the impacts of climate change on biodiversity. Precipitation may affect fauna through direct effects on physiology, behaviour or demography, through plant-mediated indirect effects, or by modifying interactions among species. In this paper, we examined the response of a semi-arid ecological community to a fivefold change in precipitation over 7 years. We examined the effects of precipitation on the dynamics of a grassland ecosystem in central California from 2007 to 2013. We conducted vegetation surveys, pitfall trapping of invertebrates, visual surveys of lizards and capture–mark–recapture surveys of rodents on 30 plots each year. We used structural equation modelling to evaluate the direct, indirect and modifying effects of precipitation on plants, ants, beetles, orthopterans, kangaroo rats, ground squirrels and lizards. We found pervasive effects of precipitation on the ecological community. Although precipitation increased plant biomass, direct effects on fauna were often stronger than plant-mediated effects. In addition, precipitation altered the sign or strength of consumer-resource and facilitative interactions among the faunal community such that negative or neutral interactions became positive or vice versa with increasing precipitation. These findings indicate that precipitation influences ecological communities in multiple ways beyond its recognized effects on primary productivity. Stochastic variation in precipitation may weaken the average strength of biotic interactions over time, thereby increasing ecosystem stability and resilience to climate change.

Evaluating landscape connectivity and identifying and protecting corridors for animal movement have become central challenges in applied ecology and conservation. Currently, resource selection analyses are widely used to focus corridor planning where animal movement is predicted to occur. An animal's behavioural state (e.g. foraging, dispersing) is a significant determinant of resource selection patterns, yet has largely been ignored in connectivity assessments. We review 16 years of connectivity studies employing resource selection analysis to evaluate how researchers have incorporated animal behaviour into corridor planning, and highlight promising new approaches for identifying wildlife corridors. To illustrate the importance of behavioural information in such analyses, we present an empirical case study to test behaviour-specific predictions of connectivity with long-distance dispersal movements of African wild dogs Lycaon pictus. We conclude by recommending strategies for developing more realistic connectivity models for future conservation efforts. Our review indicates that most connectivity studies conflate resource selection with connectivity requirements, which may result in misleading estimates of landscape resistance, and lack validation of proposed connectivity models with movement data. Our case study shows that including only directed movement behaviour when measuring resource selection reveals markedly different, and more accurate, connectivity estimates than a model measuring resource selection independent of behavioural state. Synthesis and applications. Our results, using African wild dogs as a case study, suggest that resource selection analyses that fail to consider an animal's behavioural state may be insufficient in targeting movement pathways and corridors for protection. This failure may result in misidentification of wildlife corridors and misallocation of limited conservation resources. Our findings underscore the need for considering patterns of animal movement in appropriate behavioural contexts to ensure the effective application of resource selection analyses for corridor planning.

1. The high cost of directly measuring habitat quality has led ecologists to test alternate methods for estimating and predicting this critically important ecological variable. In particular, it is frequently assumed but rarely tested that models of habitat suitability (“species distribution models”, SDMs) may provide useful indices of habitat quality, either from an individual animal or manager’s perspective. Critically, SDMs are increasingly used to estimate species’ ranges, with an implicit assumption that areas of high suitability will result in higher probability of persistence. This assumption underlies efforts to use SDMs to design protected areas, assess the status of cryptic species, or manage responses to climate change. Recent tests of this relationship have provided mixed results, suggesting SDMs may predict abundance but not other measures of high quality habitat (e.g., survival, persistence). 2. In this study, we created a suite of SDMs for the endangered giant kangaroo rat Dipodomys ingens at three distinct scales using the machine-learning method Maxent. We compared these models with three measures of habitat quality: survival, abundance, and body condition. 3. SDMs were not correlated with survival, while models at all scales were positively correlated with abundance. Finer-scale models were more closely correlated with abundance than the largest scale. Body condition was not correlated with habitat suitability at any scale. The inability of models to predict survival may be due to a lack of information in environmental covariates; unmeasured community processes or stochastic events; or the inadequacy of using models that predict species presence to also predict demography. Synthesis and applications: SDMs, especially fine scale ones, may be useful for longer-term management goals, such as identifying high quality habitat for protection. However, short-term management decisions should be based only on models that use covariates appropriate for the necessary temporal and spatial scales. Assumptions about the relationship between habitat suitability and habitat quality must be made explicit. Even then, care should be taken in inferring multiple types of habitat quality from SDMs.

There is widespread concern about impacts of land-use change on connectivity among animal and plant populations, but those impacts are difficult to quantify. Moreover, lack of knowledge regarding ecosystems before fragmentation may obscure appropriate conservation targets. We use occurrence and population genetic data to contrast connectivity for a long-lived mega-herbivore over historical and contemporary time frames. We test whether (i) historical gene flow is predicted by persistent landscape features rather than human settlement, (ii) contemporary connectivity is most affected by human settlement and (iii) recent gene flow estimates show the effects of both factors. We used 16 microsatellite loci to estimate historical and recent gene flow among African elephant (Loxodonta africana) populations in seven protected areas in Tanzania, East Africa. We used historical gene flow (FST and G'ST) to test and optimize models of historical landscape resistance to movement. We inferred contemporary landscape resistance from elephant resource selection, assessed via walking surveys across ~15 400 km2 of protected and unprotected lands. We used assignment-based recent gene flow estimates to optimize and test the contemporary resistance model, and to test a combined historical and contemporary model. We detected striking changes in connectivity. Historical connectivity among elephant populations was strongly influenced by slope but not human settlement, whereas contemporary connectivity was influenced most by human settlement. Recent gene flow was strongly influenced by slope but was also correlated with contemporary resistance. Inferences across multiple timescales can better inform conservation efforts on large and complex landscapes, while mitigating the fundamental problem of shifting baselines in conservation.