Ecological Applications最新文献

Drylands make up approximately 40% of terrestrial ecosystems and hold up to 20% of the global soil organic carbon pool. Most semiarid drylands are, to some extent, grazed by livestock. However, the impact of livestock grazing on carbon cycle dynamics over large spatial and temporal scales remains uncertain, especially as the effects of climate change become more pronounced. Thus far, there has been little work, which has explored how site-specific land management may interact with localized shifts in climate to affect biogeochemical processes in dryland ecosystems globally, particularly in the tropics. We used DAYCENT, an ecosystem simulation model, to explore how grazing intensity and projected climate change may impact biogeochemical dynamics in dryland sites in North America, South America, Asia, and Africa. Our simulation results showed a site-specific biogeochemical response to livestock grazing and climate change, even across ecologically similar dryland systems. In sites that had smaller projected shifts in climate (i.e., the North and South American sites), heavy grazing decreased soil carbon inputs, outputs, and storage. In the other two sites, particularly in the African site, shifts in climate had the largest impact on simulated biogeochemical processes, with a projected 20% decrease in the soil organic carbon pool in the African site by the end of the century. Our study highlights the importance of considering how localized shifts in climate may affect dryland ecosystem function as this may overwhelm land management effects over longer time scales. Our work also suggests that more research is needed to better understand how small-scale, site-specific sensitivity to climate change and land use may influence dryland carbon cycle dynamics at the global scale, particularly in tropical regions.

Understanding patterns of habitat use across trophic levels and the physical drivers of multispecies aggregations is essential to inform ecosystem-based management. To achieve this, we quantified the spatial distribution and co-occurrence of hotspots (defined using the Getis-Ord statistic) for euphausiids and nine of their commercially important fish and whale predators on the west coast of Canada during summer. We first developed fine-scale spatiotemporal distribution models of euphausiids and Pacific hake using high-resolution acoustic data from coast-wide surveys conducted between 2007 and 2018. We found that the spatiotemporal distribution of hotspots of euphausiids and hake was variable between years with low direct overlap (apart from 2017). The summer of 2015, during the 2014–2016 marine heatwave event, was a particularly anomalous year, as euphausiids and hake showed spatial mismatch in their biomass hotspot distributions. For the other eight predator species, predictions from published species distribution models were used to identify spatial hotspots as an average across years. Co-occurrence patterns were associated with the depth gradient across the shelf and slope and along the canyon and sea valley systems that characterize the Pacific coast of Canada. One assemblage was associated with the deeper parts (200–1000 m+) of the continental slope (euphausiids, hake, redbanded rockfish, sablefish, Pacific ocean perch, and humpback and fin whales) and a different assemblage (redstripe and yellowtail rockfish, and dogfish) was associated with the shallower shelf regions. Important ecological areas with co-occurring multispecies hotspots occurred along the west coast of Vancouver Island, the sea valleys of Queen Charlotte Sound, and the northwest coast of Haida Gwaii. Our results identify areas where multiple species aggregate, which can inform better management and hopefully protection of these regions that support complex food webs, commercial species, and large predators, and are therefore essential for overall ecosystem health.

Environmental DNA (eDNA) metabarcoding is increasingly applied to a variety of questions and challenges across basic and applied ecology. Although streams and rivers (i.e., lotic ecosystems) can serve as conveyor belts of both aquatic and terrestrial eDNA from upstream or riparian areas, precipitation can dilute eDNA due to increasing discharge and/or mobilize eDNA into rivers from adjacent terrestrial ecosystems. Previous research has examined eDNA detectability of single species after high flow events, but no studies have compared aquatic and terrestrial communities recovered by eDNA metabarcoding together in response to rainfall. For this study, we used eDNA metabarcoding to sample three rivers before and after precipitation over six sampling events to evaluate if terrestrial eDNA exhibits a mobilization effect and aquatic eDNA exhibits a dilution effect after rainfall. We found that as rainfall increased, terrestrial taxa richness significantly increased and aquatic taxa richness decreased but not significantly. As such, researchers using eDNA metabarcoding from lotic ecosystems to characterize terrestrial communities might not need to avoid, and could even seek out, precipitation events in their sampling design. However, our study should be replicated over more lotic ecosystems and ecoregions and larger gradients of precipitation events.

Vegetated field margins generally increase plant biodiversity and connectivity in agricultural landscapes. They can deliver ecosystem services, such as providing food and shelter for insects, or maintaining biotic regulation. But they can also represent a risk, for example by hosting competitor plants or cultivated crop pests. In this work, we evaluated the effects of agricultural practices on indicators of three ecosystem services (providing floral resources for pollinators, reducing soil erosion and conserving plant biodiversity), and one ecosystem disservice (competing with the crop by hosting problematic weeds). We used a French nationwide-scale monitoring network, composed of more than 450 fields of cereals, vineyards, and market gardening. Plant sampling and agricultural practices surveys were conducted from 2013 to 2018. We unambiguously found that pesticide use, at either field or municipality levels, or both, had detrimental effects on ecosystem service indicators. Herbicide use and fertilization quantity decreased floral resources, affecting both their quantity and diversity. Pesticide use was also associated with fewer nature-value species and more problematic weeds. Margin management could also sometimes affect the service and disservice indicators. This work not only increases the knowledge on the unintentional negative impacts of agricultural practices on ecosystem service indicators, and then probably on their delivery, but also demonstrates that pesticide reduction is positively associated with proxies for ecosystem services. It also stresses the fact that these practices have to be implemented at both field and municipality levels.

Understanding and predicting the effects of climate change on populations requires linking the environmental conditions to demographic rates and the demographic rates to population-level consequences, but often this complete demographic pathway is not studied. Integrated population models (IPMs) incorporate demographic data into a single analytical framework, allowing for the inclusion of environmental covariates to test hypotheses considering how the environment influences demographic rates, and consequently, to which demographic rates population growth rate is most sensitive. In birds, there is strong evidence that environmental conditions impact population growth, and that long-distance migrant avian species with short phenological windows are at greatest risk of population decline due to changing environmental conditions. We built a Bayesian IPM with over 40 years of mark-recapture, fecundity, and nest box occupancy data and incorporated environmental covariates hypothesized to be driving the observed changes in two populations of a fast-lived long-distance migrant, the European pied flycatcher. Using variance decomposition methods, we identified the demographic pathways through which environmental covariates were acting. While several environmental covariates impacted fecundity and survival, only precipitation acted via apparent juvenile and adult survival contributed significantly to variation in population growth rate. Increased precipitation during the nest initiation, incubation, and hatchling stages had negative carry-over effects on juvenile survival during the post-fledging and overwintering period, and increased precipitation negatively impacted adult apparent survival, likely due to the increased energetic demands of caring for eggs and hatchlings in challenging conditions and reduced availability of aerial prey. We show that linking environmental covariates to demographic rates does not sufficiently explain or predict population-level consequences, and that decomposing variation along the complete demographic pathway is a necessary step to appropriately identify how covariates influence population dynamics.

Wildlife and their habitats face profound challenges from climate and landscape-scale changes that extend beyond the influence and time horizon of most biologists and land managers. In this changing environment, long-term datasets can enhance assessments of how demographic trends respond to interactions among local (e.g., habitat restoration decisions) and broad extent drivers, including energy development, to shape wildlife populations. Although many studies evaluate habitat selection or demographics for a single population, our multipopulation, multiscale study quantifies the influence of local management actions given broader environmental forces using both immediate and lagged effects. This approach may be particularly important for species with high site fidelity that may have less adaptive capacity, including mule deer (Odocoileus hemionus), which are experiencing widespread population declines. We analyzed a 40-year (1980-2019) dataset for 37 mule deer populations across Wyoming, USA, to test hypotheses about and quantify the relative influence of conditions within winter use areas on annual rates of juvenile recruitment. Recruitment has been strongly affected by multiple factors largely beyond the control of managers. Land cover (agriculture and shrubland) had the largest positive effects on recruitment, with estimates more than twice the magnitude of other variables, but also had limited presence in some winter use areas. The next strongest effect sizes were shared by energy developments (including oil/gas and wind energy) and climatic conditions, which, except for wind turbines, had broad distributions across winter use areas. Recruitment increased with higher mean winter temperatures and summer precipitation, but declined with wind, oil and gas developments, cumulative drought, and wildfire. Expected increases in drought and decreases in summer precipitation may constrain options to sustain mule deer populations. Although mule deer recruitment may sometimes be enhanced through habitat restoration, effects varied with treatment type, habitat type, and time since treatment. Given large constraining effects of temperature and drought, supporting drought resiliency for important habitat may be useful. Our results can be used to weigh the relative strength of threats and the value of restoration actions, interpret historic demographic change, prioritize populations for conservation, and optimize options for wildlife habitat management.

Very low-intensity selective logging can be a compromise between strict conservation and income-generating land use in tropical forests. Investigating how selective logging influences the understory environment and seedling dynamics as the forest regenerates offers insights into whether logging alters forest dynamics, influencing the composition and structure of future forests. We explored how very low-intensity logging (<2 trees ha^-1) influences understory factors and seedling dynamics across a logging chronosequence (unlogged forest vs. actively logged forest and forest logged 4 and 14 years prior). To do this, we assessed (1) how canopy openness, prevalence of vegetation damage, and elephant trails differ in logged forests at different recovery stages compared to unlogged forest; (2) how these understory factors influence seedling dynamics; (3) how seedling dynamics differ across the logging chronosequence; and (4) how logging impacts liana vs. tree seedlings across the chronosequence. We observed greater canopy openness and vegetation damage in logged forests up to 4 years after logging and higher elephant trail prevalence 14 years after logging compared to unlogged forests. Seedling survival was lower in plots with higher canopy openness, more vegetation damage, and on elephant trails, while growth and recruitment were not affected by these variables. Actively logged forests initially had lower seedling survival and recruitment, but higher growth rates compared to unlogged forests. However, 14 years after logging, seedling dynamics were mostly similar to unlogged forests. Liana seedlings had a slight growth advantage over tree seedlings in all logged forests compared to unlogged forests. Results from our study suggest that very low-intensity selective logging causes temporary shifts in understory dynamics rather than long-term shifts in forest recovery trajectories. These managed areas have potential as land that can contribute to OECM targets-functioning as mixed-use corridors, connecting protected areas across a landscape and contributing to biodiversity and wildlife conservation-especially in countries with high forest cover and low deforestation.

Feral cattle (Bos taurus) and horses (Equus ferus caballus) are commonly introduced to European rewilding areas to halt vegetation succession and to conserve light-demanding species. Yet, we still do not understand how the habitat preference of animals shapes vegetation structure at the landscape scale. Here, we used spatial preference modeling to understand drivers of space-use based on GPS-collared horses and cattle in a 120-ha rewilding area in Denmark. Using a time series of a satellite-based vegetation productivity index, we tested the ability of animal space-use to explain changes in vegetation, as well as the trend of its spatial variability at the reserve scale, as a measure of landscape-scale vegetation heterogeneity. We expected that animal space-use would be driven mainly by topography and vegetation characteristics and that highly used areas with open vegetation would remain open. We, indeed, found that vegetation density and landscape connectivity were good predictors of space-use preference for both cattle and horses. Additionally, both cattle and horses were strongly attracted to an artificial shelter located inside the reserve, warranting consideration of the use and placement of artificial infrastructure. Space-use diverged during periods of resource scarcity emphasizing the value of introducing a variety of herbivore functional types for optimizing structural ecosystem heterogeneity. As expected, we found that cattle and horses slow down vegetation succession in highly used areas, as shown by the negative correlation between changes in growing season productivity and intensively used areas dominated by short herbaceous and shrubby vegetation. We could also show that the highly used areas showed the largest reductions and the fastest recovery in vegetation greenness following the pan-European drought in 2018. A ~2/3 reduction in herbivore population size subsequent to the drought was followed by a general greening of the landscape, but with no clear relationship with space-use intensity. Our study supports that trophic rewilding with year-round grazing can limit vegetation densification at the landscape scale under near-natural conditions. This is pertinent in the face of accelerating succession toward increasingly dark and tree-dominated vegetation in temperate Europe's natural areas, and the associated biodiversity loss.

Urban environments pose a threat to biodiversity through processes such as habitat degradation and biotic homogenization. Despite this, cities are increasingly recognized for their potential to conserve bees and other pollinators. Planting understory vegetation is one way of providing more floral resources to support urban bee communities and the ecosystem services they provide. However, the influence of vegetation origin and landscape context on urban bee communities is unclear, particularly in the Southern Hemisphere. We sampled the bee communities at 32 understory plantings dominated by exotic or indigenous (native to the local bioregion) vegetation around inner Melbourne, Australia. For each site, we recorded the amount of impervious surface and irrigated turf in 200-m buffers. Indigenous plantings were found to promote significantly greater alpha and beta diversity in bee communities compared to exotic plantings. Particular plant taxa were highly effective at attracting a variety of bees, with a maximum of 19 bee species (including specialists) hosted by indigenous Wahlenbergia capillaris (Campanulaceae). Apis mellifera was highly dominant and strongly associated with exotic plantings, whereas many indigenous bee species were positively associated with indigenous plantings. This study shows indigenous understory plants have a positive influence on indigenous bee communities relative to exotic plantings which tend to attract only A. mellifera. Planting indigenous plants in cities is therefore recommended as a conservation action for local bee species.

Despite the ecological expression and conservation importance of diverse behavioral tactics in animals, there is often friction associated with conventional analytical approaches and inference concerning variation in spatial behavior. Implicitly or explicitly, population-level inferences are generally the main objective of studies, but interpretations can be ambiguous in the presence of divergent behavioral tactics across individuals or cohorts, as with generalist species. We pursued a novel analytical approach and assessed the underlying mechanisms driving variation in spatial behaviors of generalist species using the American black bear (Ursus americanus) as our focal species. We quantified individual variation in habitat selection expressed by black bears using individual models for 35 collared bears across four study areas in Wyoming, USA. We modeled how state-dependent factors (age, sex, δ¹⁵Nitrogen, and body fat) and resource availability influenced behavioral variation in resource selection. We observed vast variation among individuals, demonstrating patterns consistent with a generalist species. Black bear resource selection differed with changes in state dependence and resource availability. Specifically, traits uniquely important to black bear success, body fat and carnivory, explained variation in selection for forage indexed by normalized difference vegetation index (NDVI), forests, and riparian areas. Environmental heterogeneity via differences in resource availability magnified behavioral variation in resource selection by black bears. Selection trends for NDVI and deciduous shrubs were explained by resource availability, indicating black bears exhibited functional responses in habitat selection. These insights emerged from our analytical approach; had we implemented a more conventional, population-level assessment, we would have simply concluded that black bears displayed behavioral neutrality with respect to forage resources. Acknowledgment of behavioral variation when considering spatial behavior of generalist species provides a more representative understanding of individuals within a population, and our analytical approach offers a solution to uncovering drivers of individual variation in spatial behavior.