Ecosphere最新文献

Dynamics of infectious disease in natural populations result from processes across scales, from host characteristics shaping exposure risk and susceptibility, to local environmental conditions driving vector populations, to the structure of metapopulation networks shaping transmission of pathogens across the landscape. However, multiscale datasets of pathogen exposure patterns in natural populations are rare, limiting opportunities to explore the interplay of factors that shape the occurrence of infectious pathogens in space and time. We leveraged serological data from 18 populations of desert bighorn sheep (Ovis canadensis nelsoni) in southern California, collected across 40 years of captures, to investigate within- and between-population drivers of exposure to 10 viral and bacterial pathogens. Across these serological tests, we found high diversity in patterns of temporal dynamics, spatial distribution, and local seroprevalences. For most of the tests evaluated, seroprevalence varied significantly between geographically distinct populations and between metapopulation clusters. We found that population connectivity, environmental suitability for vectors, and proximity to cattle grazing allotments affected pathogen exposure. The relative importance of each of these drivers depended on pathogen biology: exposure to pathogens that may infect both bighorn and domestic cattle was best explained by the presence of cattle grazing allotments, while pathogens specific to wild and domestic sheep were negatively associated with cattle. Importantly, only a subset of serological tests had any positive association with population connectivity, challenging the long-debated assertion that increasing metapopulation connectivity will most often lead to increased risk of exposure. Instead, these data suggest that the benefits, and costs, of population connectivity on managing wildlife disease are dependent on pathogen characteristics.

Long-lived perennial species in drylands tolerate a range of environmental conditions over their lifespan, but young plants are more vulnerable to stressful conditions than mature plants. To understand plant community stability, it is essential to evaluate how variable weather and disturbances influence the growth and establishment of new individuals. Over 760,000 km² of temperate midlatitude drylands of western North America are dominated by big sagebrush (Artemisia tridentata Nutt.) plant communities, a long-lived woody species. Due to historic degradation and loss, the conservation of remaining big sagebrush habitat is a public land management priority. Big sagebrush recruitment is often the most challenging aspect of restoration treatments, yet relatively little is known about the growth and development of juvenile big sagebrush plants under field conditions. We collected 73 juvenile big sagebrush plants (<20 cm height) to investigate how weather, shrub canopy modification, and site conditions affect growth rate. We found no significant effect of mechanical canopy reduction in plant communities on the growth rate. Annual growth in our chronology was positively and significantly correlated with June precipitation, and establishment was influenced by winter, fall, or spring precipitation and summer temperatures. We found that big sagebrush height and stem diameter are significant predictors of age. Our findings demonstrate that morphological characteristics can be used to estimate the age of juvenile plants to assess stand dynamics and growing conditions. Our findings also demonstrate that the growth of juvenile big sagebrush plants is tightly coupled to weather and that growth has a predictable response to variable conditions.

Specific host-tick interactions in temperate forest systems influence variation in density and infection prevalence of nymphal blacklegged tick (Ixodes scapularis). The density of infected nymphs (DIN), which is the product of nymphal infection prevalence (NIP) and density of questing nymphs (DON), influences the risk of human exposure to tick-borne pathogens. Questing nymphs (>2000) collected between 2014 and 2022 were screened for 16 zoonotic pathogens. More than a third (38.8%) of nymphs were infected with at least one pathogen, and Borrelia burgdorferi (the agent of Lyme disease) was detected in all six sampling locations and years. Pathogens included Babesia microti (NIP = 21.4%), Bo. burgdorferi (19.3%), Anaplasma phagocytophilum (5.8%), Bo. miyamotoi (1.5%), Powassan virus (<0.01%), and two regionally emergent Rickettsia (10 nymphs sampled in 2016 and 2021). Rates of Ba. microti infection were high relative to prior work, and coinfection with Bo. burgdorferi increased during the study period. White-footed mouse (Peromyscus leucopus) and eastern chipmunk (Tamias striatus) are important zoonotic hosts in temperate forests. We evaluated how variation in host abundance and the number of larval ticks feeding per animal (larval burden) explained and predicted DIN, as well as DON and NIP independently. While both mouse abundance and mouse larval burden were positive predictors of DON in this study, their influence on NIP and DIN for commonly detected pathogens differed. Both mouse and chipmunk larval burden explained significant variation in Bo. burgdorferi DIN, and larval burden on mice specifically improved prediction when observed Bo. burgdorferi DIN was high. Chipmunk larval burden also predicted variance in Bo. burgdorferi NIP and also explained significant variation in Ba. microti DIN. While observed host-tick contact metrics improved predictive skill, underprediction was most evident when observed DIN or NIP was high. These results emphasize how tick-borne zoonoses depend on a distribution of larval meals across a community of hosts. For Bo. burgdorferi in particular, NIP may be stabilized by tick-feeding on a diverse host community. Thus, while large changes in mouse abundance may predict regional changes in DIN, local NIP in particular may be more responsive to shifts in larval feeding activity across the entire community of hosts.

Variability in resource use within populations of free-ranging animals can influence demographic and evolutionary processes. Yet in many ecological systems, the extent of intra-population variation in the resources that animals consume and the environmental factors that contribute to this variance remain poorly understood. For example, dietary studies commonly group conspecific individuals and jointly classify entire study populations along the generalist to specialist continuum, even though the diets of subpopulations and individuals can deviate significantly from the population average, particularly in heterogeneous habitats—where structural and biotic characteristics of the sampled habitat are diverse. To evaluate the degree of intraspecific diet variation in a population of wild birds and to test potential linkages between observed variation and environmental gradients in relative resource abundance, we used hierarchical Bayesian stable isotope mixing models to estimate (1) assimilated diets of juvenile lesser scaup (Aythya affinis; hereafter scaup) and (2) diet variation within and across lakes that harbor distinct assemblages of aquatic macroinvertebrates. We found that lake-level variation in diet accounted for most of the variation across the study population, with little variation attributed to differences among individuals within a given lake. Although we did not detect an effect of macroinvertebrate abundance on the diets of pre-fledging scaup, our findings indicated that ducklings have greater dietary flexibility than previously considered. By identifying variation in resource use within a population of a generalist consumer occupying diverse habitats, our results facilitate improved predictions of which species might be best adapted to respond to changing environmental conditions.

The understanding of ectomycorrhizal (ECM) fungi's role in shaping bacterial groups and regulating heavy metals in soils was limited in the past. A mesocosm experiment with inoculation treatments (Pezicula ericae K2 and Pisolithus tinctorius) was applied to Pinus taiwanensis. The study aimed to explore the impact of ECM fungi, specifically, P. ericae K2 and P. tinctorius, on bacterial communities within the rhizosphere and endorhiza (root tips) of P. taiwanensis seedlings. Additionally, it sought to evaluate the interaction between environmental factors, including heavy metals and bacteria associated with ECM fungi. Furthermore, the study aimed to elucidate the influence of ECM fungi on host plant biomass, environmental conditions, and heavy metal concentrations. Next-generation sequencing analyzed rhizosphere soils and root tip bacterial communities. Results confirmed P. ericae K2 as an ECM fungi; dominant phyla in rhizosphere soils were Acidobacteria and Proteobacteria, while in mycorrhizal root tips were Actinobacteria and Proteobacteria; rhizosphere soils had a more robust influence of environmental factors and heavy metals; the most dominant Actinomycetales and Burkholderiales were associated with rhizosphere soils and root tips, respectively; diversity indices escalated for seedlings with ECM fungi; most negative correlations of bacterial rhizosphere soils signified their resistance to heavy metals; nitrogen fixers displayed intricate positive correlations in the root tips; ECM fungi increased plant biomass, soil cations, pH, and cation exchange capacity while reducing soil nitrogen and heavy metal concentrations. The study highlighted that ECM fungi's ecological contributions were crucial for regulating metal-laden soils, benefiting plant health and tolerance, and sustaining ecosystems.

Understanding distinct vital rates (birth, death, immigration, and emigration) is a common goal in studies of ecological populations because separately estimating these rates and their drivers allows better prediction of population growth in unsurveyed areas and in the future. Integrated population models provide a means of isolating vital rates, but may require an abundance of relatively costly mark–recapture data to do so. For migratory animals, moreover, the utility of population models that do not consider multiple seasons in the full annual cycle may be limited. We describe a full-annual-cycle, integrated population model (FAC-IPM) framework that addresses these issues for migratory animals, and relies primarily on monitoring data (i.e., counts) in two of the four seasons of the annual cycle, breeding and non-breeding. This Bayesian FAC-IPM is composed of two parallel, linked dynamic N-mixture (Dail–Madsen) models, one for the breeding season and the other for non-breeding, that share information with one another across the seasonal divide to better resolve annual survival and recruitment. This information sharing also allows separate estimation of movement (immigration and emigration) in both seasons. We show through simulations that the FAC-IPM can recover population vital rates when sufficient auxiliary information regarding a subset of these rates is available, for example, in the form of mark–recapture data such as those from telemetry and productivity studies. We then present a case study of a migratory grassland bird of conservation concern, Baird's sparrow (Centronyx bairdii), in which we demonstrate that the FAC-IPM provides useful results in realistic sampling situations: longer time series and broader spatial coverage for count than for mark–recapture data, and many missing years in particular sites' monitoring histories. We show the model's ability to estimate annual values for survival, reproduction, and movement in the breeding grounds, non-breeding survival and movement, and, by deduction, survival during the two migratory seasons. We also estimate covariate relationships on rates in both breeding and non-breeding seasons, valuable information in support of effective conservation planning to improve overall population growth.

The frequency and intensity of extreme climatic events such as heatwaves are predicted to increase under continued climate change and rising atmospheric CO₂. Degraded and fragmented ecosystems are at particular risk of being greatly impacted by such extreme events. The longleaf pine (LLP) savanna ecosystem, once the dominant ecosystem throughout the Southeast Coastal Plains of the United States, has been reduced to a small percentage of its pre-colonization range. While the effect of heatwaves on grassland systems has been well explored, less focus has been given to the legacy effects of previous climatic events. Through a greenhouse experiment using Schizachyrium scoparium (little bluestem), a dominant understory grass species in LLP savanna ecosystems, we aimed to study the legacy effects of heatwaves (i.e., higher temperatures and lower precipitation and humidity) across multiple plant performance metrics and stress responses. S. scoparium had a negative response to an early heatwave, showing increased mortality, smaller maximum leaf length, fewer leaves, decreased specific leaf area (SLA), decreased leaf thickness, and reduced belowground net primary productivity (NPP) when compared to plants that did not experience a heatwave. S. scoparium individuals exposed to a late heatwave had fewer leaves, reduced SLA, and thinner leaves when compared to plants that did not experience a heatwave. While plants exposed to both an early and late heatwave experienced an increase in some stress responses as observed by increased catalase activity and plant mortality, they exhibited no change in other stress responses studied (e.g., maximum leaf length, relative growth rate, productivity, leaf thickness, peroxidase levels, or fuel load). Overall, our study revealed that S. scoparium may show neutral-to-positive legacy effects in response to multiple heatwaves. This indicates that LLP savanna ecosystems dominated by S. scoparium may display resistance to the predicted increased frequency of heatwaves in the southeastern United States, an important outcome for the heavily degraded and endangered ecosystem.

The feeding ecology of apex carnivores is affected by multiple intrinsic (e.g., sex and age) and extrinsic (e.g., prey density, habitat availability, presence of dominant competitors) factors, yet little research has explored how these factors affect the temporal use of resources. We placed video camera traps at puma (Puma concolor) kill sites and used a series of comparative analyses to understand if pumas varied in their diel activity at kill sites. We found that the diel activity of male pumas at kill sites peaked around midnight, but the diel activity of females and family groups peaked just after sunset, supporting our hypothesis that other sex/age classes would shift diel activity to avoid the potential risk posed by male pumas. We also observed changes in diel activity according to whether pumas fed during the visit to a kill site or not, their visit duration, and the number of days since the kill was made—suggesting that pumas adjusted the diel aspect of feeding to minimize competition risk while maximizing energy/nutrient intake as carcass quality degraded. Finally, contrary to our predictions, human activity had a greater impact on puma diel activity at kill sites than the human footprint, suggesting that pumas are more sensitive to short-term anthropogenic disturbances near their kills than proximity to permanent structures. Our study highlights how both intrinsic and extrinsic factors lead to diel variation in kill sites by pumas. Better understanding the dynamics of the feeding ecology of apex carnivores—including how they balance the competing forces of feeding efficiency, safety, and competition—will facilitate developing more effective conservation strategies to minimize costly disturbances while feeding for apex carnivores.

Top predators influence ecological communities in part through the prey they consume. Prey preferences often shift throughout the year, reflecting both seasonal and geographic patterns of habitat use and the relative abundance of preferred prey species. Killer whales (Orcinus orca) are top predators in the marine ecosystem, and understanding their diet is critical to assess their ecological impacts and role. In this study, we examine the diet of the southern Alaska resident killer whale population across three major foraging hotspots. We leverage two complementary sampling methods—morphological ID and genetic metabarcoding—to reveal strong spatiotemporal patterns in diet from May through September. Chinook, chum, and coho salmon were each important prey resources in different locations and times, with consistent dietary contributions from Pacific halibut, arrowtooth flounder, and sablefish. Our results reveal a diverse, location-specific, and strongly seasonal foraging strategy in this top predator and highlight the increased resolution provided by using ensemble techniques to characterize foraging behavior. Effective conservation and management of this population will depend on broad spatiotemporal sampling to accurately characterize foraging ecology.

Emerging infectious diseases can cause rapid, widespread host mortality, and the lack of demographic data before and after pathogen emergence complicates understanding mechanisms of host persistence. This challenge is further compounded by environmental conditions that influence host behavior, while driving pathogen growth and virulence. These interactions create complex disease outcomes that hinder predictions of when and how hosts endure pathogen outbreaks. Here, we analyzed 10 years of capture-mark-recapture data (2000–2014) spanning wet and dry seasons for male Espadarana prosoblepon in El Copé, Panama, encompassing a period before (2000–2004) and after (2010–2014) a Batrachochytrium dendrobatidis (Bd) outbreak using Jolly-Seber models. We found that post-Bd male E. prosoblepon population size (range in mean population size among primary periods = 136–225 individuals) was similar to pre-Bd population size (range in mean population size among primary periods = 201–242 individuals). Pre-Bd, average monthly survival probability in the wet season was 0.93 (95% credible interval [CI] = 0.90–0.96). Post-Bd, uninfected individuals had survival probability higher in the wet season (mean = 0.97; [95% CI = 0.95–0.98]) than the dry season (mean = 0.90 [95% CI = 0.84–0.94]), while survival probability for infected individuals decreased as a function of Bd infection intensity. Pre-Bd, mean monthly per-capita entry probability was 0.07 (95% CI = 0.05–0.10), and post-Bd, mean monthly per-capita entry probability was 0.06 (95% CI = 0.00–0.10). Lastly, infection probability during the wet season was lower (mean = 0.04 [95% CI = 0.03–0.05]) than the dry season (mean = 0.10 [95% CI = 0.05–0.15]), and recovery probability during the wet season was lower (mean = 0.19 [95% CI = 0.11–0.28]) than the dry season (mean = 0.54 [95% CI = 0.20–0.88]). Our findings suggest that survival probabilities of uninfected individuals, as well as per-capita entry probabilities, are similar pre- and post-Bd, leading to a stable and similar sized pre-Bd population. These results contribute to understanding disease dynamics and tropical amphibian ecology.