Ecological Applications最新文献

Mid-latitude forest ecosystems in the Northern Hemisphere serve as substantial carbon sinks and also hold a strong transpiration capacity, making them critical components of the global carbon and water cycles. However, the diurnal carbon–water coupling strength over mid-latitude forests and its dependence on environmental factors are unclear. Based on half-hourly flux data from 34 eddy covariance (EC) towers over forest ecosystems located between 30° N and 60° N, here we investigate the characteristics of diurnal carbon–water coupling strength and its response to environmental factors, that is, solar radiation (SR), air temperature (T_a), vapor pressure deficit (VPD), and soil water content (SWC) through correlation analysis, ridge regression, and data binning. We find that there is a distinct difference in diurnal variation between gross primary productivity (GPP) and evapotranspiration (ET), with GPP generally decreasing earlier and faster than ET after its peak. An increase in SR, T_a, or VPD can lead to a reduction in the diurnal coupling strength, while higher SWC makes the coupling stronger. The magnitudes of the negative effects of VPD and T_a vary across the day, with VPD in the afternoon being the most influential factor and T_a playing a dominant role in the early morning. Among the 34 sites, VPD is the dominant factor influencing coupling strength at 30 sites, while T_a is secondarily important over one-third of the studied sites. The weakening of coupling strength is attributed to the asynchronous responses of GPP and ET to environmental factors, particularly under conditions of high VPD and temperature, when GPP tends to decrease while ET does not follow. This study highlights the dynamics of diurnal carbon–water coupling and the complex interactions with environmental factors, emphasizing the need to consider the short-term responses of GPP and ET coupling to environmental factors across diverse ecosystems in future research.

Increased nitrogen (N) deposition due to industrial and agricultural activities poses a significant threat to global biodiversity, disrupting ecosystem functions and services. Above- and belowground communities are closely interdependent and both respond to N enrichment, yet they are frequently studied separately. Whether the biodiversity of these communities responds similarly or synchronously to N inputs remains underexplored. Using a decade-long N addition experiment in a meadow steppe ecosystem, we explored the effects of a gradient of N addition levels (from 0 to 50 g N m⁻² year⁻¹) on the diversity of aboveground plants and belowground nematodes at second, sixth, and tenth years after the initiation of the experiment. Our findings revealed asynchronous responses of above- and belowground biodiversity. Plant diversity showed a progressive, time-dependent decline that intensified with both increasing N concentrations and experimental duration. In contrast, nematode diversity exhibited a threshold response: an initial decline at low N levels (<10 g N m⁻² year⁻¹) followed by stabilization across higher N concentrations, with no significant temporal intensification of this pattern over the course of the decade-long study. Plant richness declined primarily due to rapid species loss, especially among forbs, with little compensatory gain. In contrast, nematode diversity exhibited a more balanced response, driven by species replacements in which gains offset losses. Bacterivores and omnivores-predators were the most negatively affected nematode groups. This study advances our understanding of ecological responses to nitrogen enrichment by revealing the contrasting long-term dynamics of above- and belowground communities in a meadow steppe ecosystem. While plant diversity deteriorates with increased N input, nematode diversity shows signs of resilience via compensatory turnover, highlighting the potential for belowground biota to buffer ecosystem-level biodiversity loss under chronic N deposition. Our findings underscore the critical need to consider both plant and soil biota simultaneously when assessing the impacts of N deposition on biodiversity.

Elton's diversity–invasibility hypothesis, which proposes that diverse communities should be more resistant to biological invasions, has been the focus of much attention. However, little is known about how soil microbes recruited by native plants influence the vulnerability of forest ecosystems to invasion by exotic plants. Here, we present a two-part plant–soil feedback experiment (Part A, diversity effect; Part B, soil inoculation) to examine the effects of soil microorganisms associated with native plant species at different diversity levels on community invasibility of temperate forests, using two invasive plants, Rhus typhina and Phytolacca americana, as test species. Aboveground plant growth and biomass allocation differed significantly between the two invasive plants under simulated diversity, with negative effects on P. americana and positive effects on R. typhina. Both the diversity effects and soil inoculation experiments showed that the growth of P. americana was inhibited, while that of R. typhina was promoted by soil microorganisms. In contrast to the non-mycorrhizal P. americana, the arbuscular mycorrhizal plant R. typhina enhanced its stress tolerance through close associations with soil fungi. Our study suggests that the role of soil microbes in the “diversity–invasibility” relationship might be related to the species identities (e.g., mycorrhizal type) of both invasive and native species. These results shed new light on Elton's diversity–invasibility hypothesis by highlighting the role of plant–soil feedback mechanisms.

Millions of dollars and countless hours are spent on invasive plant management, and the field of invasion ecology has gained increasing attention in recent decades. Yet, despite these efforts to control and understand plant invasions, successful management is often elusive. Budgetary constraints are a common factor limiting invasive plant management programs, and therefore optimizing control strategies is essential. However, such optimization requires data on management inputs and outcomes, and these data are often missing, lacking, or underutilized. To address this knowledge gap and identify predictors of successful invasive plant control in natural areas, we examined nearly 20 years of invasive plant treatment data in the world's largest urban national park—Santa Monica Mountains National Recreation Area of southern California. We resurveyed 279 sites, which had undergone control in the past two decades, collecting data on the abundance of native and invasive plant species to evaluate long-term management outcomes. We used multiple statistical approaches to identify management inputs and site characteristics that are predictors of eradication, invasive plant cover, and native species recovery. We found that the greater the initial size or percent cover of an infestation, the lower the probability of eradication. We also found that infestations on steeper slopes and in areas that have burned more frequently are less likely to be eradicated. Promisingly, our results also showed that greater reductions in invasives generally benefited native plant communities, though not in all cases. These analyses also highlighted that persistence is key; more frequent treatments (both chemical and nonchemical) and greater investment of labor resulted in larger reductions in invasive plants. Our results highlight how site characteristics and limited resources can complicate invasive plant management, while demonstrating the value of analyzing treatment and monitoring data to identify effective control strategies and guide adaptive management decisions.

Artificial surface water (ASW), created through dams, impoundments, and other engineered water features, is increasingly deployed in arid protected areas to support wildlife. However, our understanding of how and why ASW shapes the spatiotemporal activity and ecologically relevant biomass of large mammalian herbivores remains limited. We evaluated whether one form of ASW, dammed seasonal drainages that create reservoirs, alters the metabolic biomass, spatial distribution, and seasonal activity patterns of large herbivores. Specifically, we tested whether reservoirs shifted large herbivore use from seasonal pulses to persistent disturbance, modify species activity patterns, and if large herbivore distributions correspond with their theoretical water dependence. Using a paired catchment design, we deployed camera traps around 11 reservoirs and 11 undammed drainages in Kruger National Park. Cameras were placed along 2250-m transects. Species-specific activity and metabolic biomass were modeled as a function of catchment type, season, and distance from the edge of reservoirs or undammed drainage. Reservoirs concentrated large herbivore activity year-round, indicating a shift from seasonal to persistent disturbance regimes. Dammed catchments supported higher large herbivore metabolic biomass in both wet and dry seasons, with effects extending to just over 1 km in the dry season and >2 km during the wet season. Elephants comprised more than 50% of the observed biomass, and other species such as hippopotamus, impala, and zebra also concentrated their activity near reservoirs. In contrast, browsing species like giraffe, duiker, and steenbok were more active in catchments with undammed drainages. Contrary to expectation, species' water dependence scores did not consistently predict species responses. While ASW can enhance wildlife visibility and forage access, it also risks excluding some species and concentrating herbivore impacts, with implications for vegetation change, human–wildlife conflict along park boundaries, and ecosystem resilience. We recommend adaptive ASW management strategies, including the strategic placement and temporal manipulation of surface water, to balance wildlife needs with long-term conservation goals—particularly under increasing climatic variability.

Predicting population abundance while accounting for uncertainty is an essential task for managers of endangered species but is often hindered by the challenge and expense of comprehensive data collection. Many traditional methods for estimating abundance of rare or elusive species are costly and logistically difficult, with occupancy-based methods being a popular alternative. While the theoretical relationship between occupancy and abundance is well studied, there are few examples of methodological approaches for predicting abundance from occupancy. This study presents a novel approach to bridge the gap between abundance and occurrence for species with low capture probability, using the Pacific pocket mouse (Perognathus longimembris pacificus; PPM) in Southern California, USA, as a model system. PPM have been monitored across three subpopulations in this region using track tubes to inform occupancy over space and time and live captures to inform PPM demography and phenology. Paired capture–recapture data and presence–absence data collected between 2012 and 2022 were used to estimate density, occupancy, and detection, respectively. Density was modeled as a function of both occupancy and detection, and abundance at monthly and annual scales was predicted from estimates of density for all subpopulations. Our methodology leverages all available data in an integrated Bayesian analysis where uncertainty in site-level abundance is naturally accounted for when scaling abundance estimates to the population level. While occupancy and detection were both predictive of and positively correlated with density, a meaningful amount of variation in density was not explained by our model, revealing avenues for future study as well as providing a realistic assessment of uncertainty in population-level abundance predictions. In addition to advancing the current understanding of Pacific pocket mouse population dynamics, this approach is applicable to a wide array of species and ecosystems where population management is necessary, but individuals have low capture probability and available resources may preclude direct estimation of density at relevant spatial scales. From a design perspective, our results demonstrate the utility of strategically deploying density-based monitoring methods within long-term occupancy monitoring programs. More generally, our findings underscore the potential of this approach to inform methods to include abundance estimation in spatial occupancy monitoring programs for endangered species.

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.

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.

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.