Ecosphere最新文献

Intraguild predation (IGP) and competition significantly influence resource utilization patterns among sympatric species. The presence of alternative prey (consumed only by intraguild [IG] predators and not IG prey) may promote coexistence and have a profound effect on distribution patterns. Models predict that IG predator distributions should match alternative prey distribution when alternative prey are abundant. IG prey should risk-match by selecting safe habitats. When alternative prey are scarce, coexistence may be facilitated by a more even distribution across habitats or other mechanisms. Based on the models, the distribution of IG prey may be indirectly mediated by the alternative prey. French Frigate Shoals atoll, Hawaii, has a predator community that includes IG predators (tiger sharks), IG prey (gray reef sharks), and competitors (gray reef and Galapagos sharks, tiger and Galapagos sharks). Tiger sharks will consume alternative prey (fledgling seabirds) which occur in high abundance in the summer. We used acoustic telemetry of 128 sharks to test predictions of habitat use. As predicted by the model, tiger sharks showed a strong selection for islets where albatross fledge during the summer, whereas gray reef sharks avoided these areas and used other habitats. During the winter, tiger sharks showed a broader use of habitats and gray reef sharks showed a greater use of islets in lagoons. Galapagos sharks showed greater overlap with tiger sharks, but also avoided the summer islets where birds were fledging. Seabirds partially mediate habitat use by a shark community through their influence on a likely keystone species: tiger sharks. Our study highlights the importance of alternative prey and asymmetrical IGP in driving space-use patterns of marine predators.

Eastern wild turkey (Meleagris gallopavo silvestris, hereafter turkey) populations have been declining across the southeastern United States, including Oklahoma. Little is known about current turkey population numbers, as no robust method has been established for density estimation. Because of widespread population declines, some localized turkey populations now occur at low densities, where monitoring efforts can prove challenging because detection probability and encounter rate are low. We used the space-to-event (STE) unmarked abundance model on camera trap data collected at two sites in southeastern Oklahoma across two years to estimate turkey density. STE uses timelapse photography to sample across cameras at an instant in time, but species occurring at low densities may not be suitable for timelapse photography as encounter frequency between individuals and cameras is reduced with lower densities. Rather, we applied STE to a motion-detection dataset and modified sampling duration to 1 s to approximate instantaneous sampling. Using this approach, we successfully calculated estimates of turkey density. We aimed to estimate poult recruitment as well, via the ratio of poult density to hen density; however, poult detections were too few to ensure that their detections were included in the model's sampling occasions. Consequently, we purposely violated the STE model assumption of instantaneous sampling by increasing sampling duration from 1 s to 40 s to calculate poult density; using this approach as proof of concept, we were able to show that STE can provide poult-per-hen ratios as a proxy for recruitment. Overall, we demonstrated the application of STE as a method for providing defensible estimates of demographic parameters for turkey, a species whose population estimates have been elusive.

Herbivores can be drivers of ecosystem change by triggering and reinforcing vegetation transitions. Such processes may be prevalent in drylands with low productivity where herbivore abundances are linked to climate-driven resource pulses. In the Chihuahuan Desert, ecosystems are being transformed from black grama (Bouteloua eriopoda) grasslands to honey mesquite (Neltuma [formerly Prosopis] glandulosa) shrublands. Domestic livestock, exotic African oryx (Oryx gazella), and native rodents and lagomorphs have all been implicated as drivers of these transitions through multiple mechanisms affecting different plant life stages. Across shrub encroachment gradients, we paired a long-term (21 years) herbivore exclusion experiment focused on established perennial grasses with field trials measuring herbivory risk for perennial grass seedlings. We evaluated the roles of cattle, oryx, and native herbivores in reducing grass cover, and tested whether herbivore effects on grass cover and seedling mortality varied among ecosystem states (grassland, ecotone, and shrubland). Cattle and African oryx did not contribute strongly to vegetation dynamics. However, long-term exclusion of rodents and lagomorphs led to two-to-threefold increases in perennial grass cover compared to control plots (with open access to all herbivores) in shrub-encroached states where mesquite shrubs provided these herbivores with cover from predators. Likewise, herbivory of perennial grass seedlings was highest in the shrub-encroached states and was driven by rodents. Our results indicate that native rodents and lagomorphs exert strong control over perennial grass dynamics, creating positive feedbacks mediated by changes in habitat structure that can reinforce grassland–shrubland transitions in drylands.

Modeling the spatial distribution of wildlife abundance is paramount for management. In group-forming species, group size and occurrence may be governed by different ecological processes. Hierarchical models can conveniently address group size and occurrence as separate processes when estimating abundance. Therefore, identifying factors influencing group size may improve models that the management of group-forming species relies upon. We test this premise on Dall's sheep (Ovis dalli; henceforth sheep), a group-forming ungulate for which spatial distance sampling models are used to inform management, but environmental features that affect the group size of sheep have yet to be explored within a spatial distance sampling framework. We first used multi-level Bayesian models to test how spatially explicit indices of predation risk and food availability explained variation in sheep group size. We then demonstrated how including group size covariates within a spatial distance sampling model can improve model inference. Variation in sheep group size was associated with interactions between and among indices of predation risk and food availability. Larger predicted group sizes occurred in areas with higher indexed predation risk and in areas with lower risk but high indexed food availability (decreased competition). Groups tended to be smaller in steep terrain near topographical apexes and in areas with limited forage. Incorporation of these predictors of group size in our application demonstrated how our understanding of spatial patterns in abundance improved when we simultaneously modeled variation in both group occurrence and size. Our findings indicate that sheep are making complex trade-offs between predation risk and food availability when deciding to aggregate with conspecifics. Explicitly modeling these ecological relationships within our spatial distance sampling model improved predictive performance, increased abundance estimates, and mechanistically linked ecological processes with population monitoring and management. Many wildlife species that form groups are of interest to active wildlife management and our grander understanding of wildlife ecology. Therefore, the concepts we developed here are broadly applicable across a wide range of group-forming taxa.

Dreissenid mussels are among the most prolific aquatic invasive species globally, damaging water industry infrastructure, altering freshwater ecosystem functioning, and costing the global economy millions of US dollars annually. Extensive research has been conducted to predict, prevent, and understand the impacts of dreissenid spread for zebra mussels (Dreissena polymorpha). However, similar efforts for quagga mussels (D. rostriformis bugensis), the more prevalent dreissenid in the western United States, have lagged. To better characterize quagga habitat suitability and trophic relationships across six hydrologically connected Arizona waterbodies, we collected water quality and plankton community data at 20 sampling stations from 2021 to 2023. Four waterbodies had established quagga populations (hereafter “established”), while the remaining two did not (hereafter “negative”), despite suspected opportunities for introduction. Using data reduction techniques and an advanced machine learning (ML) classification algorithm, gradient boosted machine, we identified environmental and ecological conditions that differentiated established from negative stations. Notably, parameters considered crucial to dreissenid invasion (e.g., calcium, alkalinity, temperature, dissolved oxygen) were not among the most important variables to classification, as all examined waterbodies exhibited quagga-suitable ranges. Rather, in this system, the established class was characterized by conditions linked to dreissenid osmoregulation (e.g., higher total dissolved solids and potassium) and indicators of primary productivity and trophic state (e.g., higher chlorophyll a, total phosphorous, and total nitrogen). Further, established stations had lower zooplankton abundances of dreissenid competitors (e.g., Bosmina longirostris, cyclopoid copepodids) and prey (e.g., Keratella sp., Polyarthra spp.), perhaps resulting from food competition and consumption, respectively. Notably, negative waterbodies, Bartlett Reservoir (Bartlett) and Theodore Roosevelt Lake (Roosevelt), exhibited different biotic and abiotic conditions from each other. Stations in both showed indications of lower trophic states, yet Roosevelt exhibited higher densities of quagga-competitor zooplankton, while Bartlett displayed poorer conditions for quagga osmoregulation. Our study illustrates how ML can identify quagga environmental and ecological relationships within established waterbodies and demonstrates that negative waterbodies with suitable calcium concentrations may still have differing invasion risks. Therefore, ML can assist managers in prioritizing risk reduction efforts to waterbodies with less robust invasion inhibiting factors, rather than those with stronger abiotic defenses.

Hurricanes are among the most destructive natural disturbances in mangroves, altering community structure and ecological processes. Despite their impacts, few studies have assessed changes in belowground root processes (i.e., biomass, production, decomposition) following major hurricanes. Here, we quantified and compared changes in mangrove root processes in the Florida Coastal Everglades before (pre-hurricane period: 2000–2004) and after post-hurricane periods (post-Wilma, May 2012; immediate-post-Irma, March 2018; post-Irma, March 2023). We assessed spatiotemporal patterns in root dynamics across four mangrove sites (upstream, midstream, downstream, and estuary mouth) along a well-defined soil phosphorus fertility gradient in the Shark River estuary. Root biomass carbon stocks were highest in the immediate-post-Irma and post-Irma periods. The midstream site had the highest root C stocks, whereas the downstream site had the lowest across periods. Root size class distribution shifted considerably post-hurricane, with fine roots accounting for 32% (post-Wilma) to 66% (immediate-post-Irma and post-Irma) of the total root C stocks across sites. However, root production did not vary among periods at any site, although estimates were higher midstream compared to upstream or downstream. Root total nitrogen and P were ~1.3 times higher in the post-Irma period compared to other periods, with root P consistently increasing from upstream to the estuary mouth. Fine root turnover rates were lower post-hurricane compared to pre-hurricane across sites. Root decay rates declined post-Irma at all sites, except at the midstream site. Our findings suggest that P-rich sediments deposited by hurricanes can enhance belowground C allocation by increasing root biomass and nutrient uptake, while reducing root turnover to facilitate forest recovery. These responses underscore the strong phenotypic plasticity and resilience of mangrove roots in P-limited carbonate settings, highlighting their critical role in C sequestration, resilience, and ecosystem stability as climate-related disturbances and sea-level rise intensify.

Shrub expansion into grassland systems is a global phenomenon. Changing land uses and climate change are the main drivers, with common outcomes including reduced species richness and loss of historical grasslands. Coastal systems are no exception, and along the mid-Atlantic coast, Morella cerifera (southern wax myrtle) is rapidly expanding into grassland communities. Morella shrubs form dense monospecific thickets. It has been documented that established thickets modify the microclimate resulting in higher soil moisture, low light availability, and moderated temperatures within. It is unknown how M. cerifera affects plant communities that thrive on the edge of these thickets. We assessed these communities for differences in microclimate, vegetation composition, and nutrient availability to quantify effects of living along the shrub edge. Plots were identified in the swale (low-elevation habitat behind dunes) on Hog Island, Virginia, USA, along the edge of shrub thickets and paired with an adjacent open grassland plot. Trait-based comparisons were completed on species that overlapped between both communities (i.e., Spartina patens, Solidago sempervirens, Andropogon virginicus, and Panicum amarum). Along the shrub edge, we found reduced species richness, but increased cover, stem density, and height of grasses relative to open grasslands, with morphological traits indicative of competition along the thicket edge. The microclimate of the shrub edge was highly shaded, had higher soil moisture at lower depths, and cooler summer temperatures relative to the open grassland. Spartina patens was the most dominant species in both communities; however, the relative importance of the species was 250% higher in the shrub edge. As the shrub thicket continues to expand, we expect increased dominance of Spartina patens around the thicket. Shrubs and the modified shrub edge community may impact resilience to sea-level rise and storms with future climate change.

Urban expansion and anthropogenic development result in wildlife-habitat loss and fragmentation, increased human–wildlife conflicts, and biodiversity loss across the globe. However, some animal species are well adapted to anthropogenic land use and find novel foraging opportunities or refuge from predation in urban and suburban areas. White-tailed deer (Odocoileus virginianus) are abundant in suburban landscapes throughout much of North America and persist at high densities, which causes harmful effects on surrounding plant communities. Using a large camera-trapping dataset (n = 207 camera traps over a 365-day sampling period), we quantified white-tailed deer detection rates in various anthropogenic and natural habitat types in the Cleveland Metroparks, an expansive metropolitan park system. We examined whether deer detection rates varied among habitat types during the summer forage, pre-rut/rut, winter forage, and fawning periods. We also investigated how deer detection rates varied in response to enhanced vegetation index (EVI) values and coyote detection rates during each of these periods. Throughout the year, we found that deer detection rates were greater at camera stations with an abundance of herbaceous and shrubby wetlands, low-to-moderate amounts of anthropogenically developed land use (such as residential housing areas), and herbaceous and woody developed areas (e.g., lawns, picnic areas, or sports fields). During the pre-rut/rut period, deer detection rates were greater in areas with higher EVI values, which suggests that deer may have been searching out areas with green forage as plants senesced during autumn. Deer detection rates were positively associated with coyote activity during the fawning period, which indicates that coyotes and deer were using the same areas at this time of year, or that deer were more active in an attempt to evade coyotes. We suggest that metropolitan parks will experience high deer densities that lead to degraded forest ecosystems due to foraging subsidies that are provided by adjacent residential land use and an abundance of anthropogenically modified green spaces within and around metropolitan parks.

Microbes play central roles in soil nutrient cycling; yet, a limited range of microbial community characteristics have been used to explain ecosystem nutrient cycling rates, and their importance relative to plant and abiotic factors remains unclear. In this study, we assessed which of 126 commonly measured soil fungal and bacterial community characteristics best explained net soil ammonium, nitrate, and phosphate mineralization rates in temperate forests in the Northeastern United States, as well as the relative contributions of microbial, plant, and abiotic factors. Using boosted regression tree modeling, we identified the microbial variables with the highest contributions to models explaining nutrient cycling rates: the relative abundances of ectomycorrhizal fungi and nitrogen (N)-decomposition genes from oligotrophic bacteria were the most important for net ammonification, the relative abundances of indicator taxa in bacterial networks, nitrifying bacteria, and copiotrophic bacteria were the most important for net nitrification, and the relative abundance of fungal phosphorus (P)-cycling oxidoreductase genes was the most important for net soil phosphate change. Microbial variables explained more variation than plant and abiotic variables in multivariate linear models of net nitrification and net phosphate release rates, but not net ammonification rates, which were largely explained by soil edaphic factors. Leaf litter traits were also important in explaining variation in net nitrification rates, and soil temperature was important in explaining rates of net phosphate release in soil. Collectively, our findings suggest that the N-cycling capacity of microbial functional guilds and P-cycling capacity of fungi should be incorporated into ecosystem biogeochemical models to improve our predictions and understanding of nutrient cycling and related ecological processes.