Ecological Applications最新文献

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.

Large old trees are widely recognized as ecologically important across forest landscapes and concern regarding the decline of these trees is well documented because of their role in maintaining biodiversity for a broad range of organisms. In response to a growing need to inventory such trees, we developed and present the methodology to map and quantify the occurrence of large trees based on height and dbh thresholds using airborne LiDAR data and associated canopy height models. The innovative, succinct, and flexible solution we offer is based on the integration and augmentation of several existing packages within the open-source statistical software R. We use local tree-height and crown diameter data to calibrate an algorithm to count individual trees above specified height thresholds, including supercanopy trees. To satisfy large-tree definitions based on dbh, we used individual-tree height and dbh data available from existing forest inventory plots to define height-dbh curves for dominant forest community types, which then allowed height thresholds to be used as a surrogate for specified dbh thresholds. We illustrate the use of these methods to efficiently map and quantify large tree distributions within 8 forest communities across a study area consisting of 1.65 million ha of productive, industrially managed forest in New Brunswick, Canada. Spatial maps are presented, along with large-tree frequency statistics for specific communities, according to the definitions outlined in New Brunswick's provincial forest management guidelines. In excess of 37 million large trees are estimated to be broadly distributed across the study area. The methods developed identify patterns in the distribution of large trees across extensive areas (e.g., in millions of hectares) as one metric for maintenance of biodiversity at the landscape level. The methodology may be readily adapted to alternative forest-specific definitions of large trees based on tree height or dbh.

Shrubs of the genus Vaccinium serve as foundation species in boreal ecosystems as they define much of the structure of the ground vegetation and play key roles in many ecosystem services and processes. For example, Vaccinium myrtillus (bilberry) and Vaccinium vitis-idaea (cowberry) constitute staple foods for several species of large herbivores (Cervidae, deer) in Northern Europe. However, changes to the tree layer from forestry practices have resulted in declines in habitat suitability and the abundance of these shrubs over recent decades. Here, we assess whether related changes to tree basal area and species composition also affect the macronutrient composition of these shrubs, and if so, how such alterations may influence food selection by moose (Alces alces). We sampled bilberry and cowberry twigs during wintertime in five study areas dispersed latitudinally in Sweden, using 65 forest stands dominated by Scots pine (Pinus sylvestris) or Norway spruce (Picea abies) that varied in age and site fertility, while also taking into account soil C:N, pH, and moisture. We found that the macronutrient composition of bilberry and cowberry forage was significantly altered by forest density and tree species composition. In denser and more spruce-dominated forests (i.e., lower understory light), forage contained less nonstructural carbohydrates, but more protein and lignin, compared to shrubs growing in more open and pine-dominated forests. We also found that the forage available in such shaded environments was closer to the presumed nutritional target balance of moose. Our results illustrate that management decisions influence the macronutrient composition of understory shrubs in a way that may be important for herbivore foraging choices. We suggest that a larger variation in forest structure, both within and among stands across the landscape, will provide cervids with greater variation in forage qualities, since even small differences in forest structure can increase the nutritional variation of the forage. We discuss our results in the context of plant resource allocation, herbivore nutritional balancing and game and forest management.

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.