Ecological Monographs最新文献

Quantifying terrestrial carbon (C) sequestration potential is crucial for climate change mitigation and achieving C neutrality. Ecosystem manipulative experiments (EMEs) provide valuable in situ assessments of terrestrial C dynamics under global change. Although EMEs have expanded rapidly in China, their current state and role in elucidating spatial drivers of the country's terrestrial C sink and responses to major global change factors remain underexplored. This study systematically reviewed 1140 publications on Chinese EMEs, compiling a dataset of net primary productivity (NPP) and net ecosystem productivity (NEP). We identified 558 EMEs in China since 1991, marked by two phases: (1) a preliminary stage (1991–2004) and (2) exponential growth (2005–present). Most EMEs focused on grasslands, with limited emphasis on CO₂ enrichment and studies in Northwest China. Our findings revealed that China's terrestrial ecosystems serve as a significant C sink (positive NEP), with sink strength positively associated with temperature, soil clay, silt, and nitrogen (N) contents, and negatively with soil sand content and bulk density. Optimal conditions for NPP and NEP were observed at precipitation levels of 850–1176 mm and soil pH between 6.5 and 7.0. Elevated CO₂ levels stimulated NPP and NEP when combined with N addition, particularly organic N, and effects varied with temperature and soil texture (clay, silt, and sand contents). Warming impacts differed by ecosystem and facility type, reducing NPP in wetlands and NEP in open-top chambers. Combined warming with water or N addition generally increased NPP and NEP, while coupling it with reduced precipitation caused declines. Warming above 1.5°C often had adverse impacts. Both NPP and NEP responded nonlinearly to precipitation, exhibiting negative asymmetry in their responses to anomalies. Nitrogen addition consistently stimulated NPP and NEP, with responses influenced by application rates, frequency, duration, and soil texture and pH. Additive effects of combined global change factors on NPP and NEP were common. To improve our understanding of terrestrial C feedbacks to anthropogenic changes, future research should focus on long-term, multifactor studies in mature forests and wetlands, aiding in the pursuit of net-zero targets.

Pollinator-mediated and pollinator-independent interactions both affect plant reproductive success but are often studied independently. Evaluating the separate and cumulative effect of both types of interactions is necessary to understand population dynamics and species coexistence. Here, we ask how interactions during growth and flowering contribute to pollinator-mediated and pollinator-independent density dependence in components of reproduction and total fecundity in communities of Clarkia species. Using experimental plots embedded in natural communities of forbs and grasses, we examine the response of flower number, ovule number per flower, seed set (% of ovules in a fruit that are filled seed), and total fecundity (total seed number per plant) of focal plants of four Clarkia species to varying densities of background Clarkia, forbs, and grasses, with (control) or without supplemental pollination of focal flowers. A comparison of seed set and total fecundity between control and pollen-supplemented flowers provided an estimate of pollen limitation to reproduction, which was largely pollinator mediated in this study. Forbs and grasses exerted a density-dependent, pollinator-independent competitive effect on all reproductive components and on total fecundity. By contrast, interactions between focal and background Clarkia were entirely density-independent, pollinator-mediated, and affected only seed set. Pollinator-mediated effects on seed set between pairs of focal and background Clarkia species were largely competitive, and in line with the known pollination biology of Clarkia species. Our results point to the importance of evaluating pollinator-mediated interactions in the context of natural communities, and that pollinator-mediated interactions between Clarkia species, while strong, are not likely to affect population dynamics at the scale of the small local neighborhood but may do so at larger spatial and/or temporal scales.

Spatial variations in food availability may influence life-history traits of wildlife species, particularly in capital-breeding species that store energy when food is widely available and catabolize it during energy-intensive reproductive periods. The reproductive success of capital breeders is thus highly dependent on the accumulation of fat reserves. Reproductive success may also improve with access to alternative food resources provided by environments with strong human footprint and anthropogenic disturbances, but these environments may also increase mortality risks of wildlife. We performed a systematic review to extract reproduction and survival traits reported in studies on the American black bear (Ursus americanus), a capital breeder. Based on 94 studies widely distributed across North America, we conducted meta-regression analyses to assess whether interpopulation variation in age at primiparity, litter size of cubs, annual cub survival, and annual survival of adult females were associated with environmental conditions, that is, habitat quality, habitat productivity, and anthropogenic disturbances. We found that mean age at primiparity decreased from around 5 to 4 years old in areas with the highest habitat quality and productivity as well as the highest human population densities compared with those with poor habitat quality and productivity and low human population densities. Mean litter size increased by approximately 13% (from 2 to 2.25 cubs per litter) in areas with the highest compared with the lowest proportion of deciduous forest, while cub survival increased by about 13% (from 60% to 73%) in areas with the highest compared with the lowest coverage of agricultural crops. Adult female survival decreased from 92% to 85% in areas where hunting was allowed. These results provide new insights into the factors associated with variations in reproductive success and survival across populations of a widely distributed species, demonstrating the impact of both natural and anthropogenic factors. Our study highlights the necessity of considering the ongoing changes in the distribution and growth of potential food resources, as well as the growing encroachment of humans into wildlife habitats, when planning management and conservation actions at the scale of a species distribution range.

The behavior and abundance of sympatric predators can be affected by a complex dominance hierarchy. The strength of antagonistic interactions in predator communities is difficult to study and remains poorly understood for many predator assemblages. Predators directly and indirectly influence the broader ecosystem, so identifying the relative importance of competition, prey, and habitat in shaping predator interactions has broad conservation and management implications. We investigated space use among five predator species (black bear [Ursus americanus], bobcat [Lynx rufus], coyote [Canis latrans], mountain lion [Puma concolor], and gray wolf [Canis lupus]) across three temporal scales in northern Idaho, USA. We used camera trap data to test whether potentially subordinate predators spatially avoided dominant predators and how prey availability influenced those relationships. We found few instances of subordinate predators spatially avoiding dominant predators and only at the finest temporal scale of our analyses. Instead, habitat features generally influenced predator space use patterns at coarser scales whereas prey and competitor presence influenced space use patterns at finer scales. Co-occurrence was positively associated between coyotes and bobcats at coarser timescales and between mesopredators and apex predators at finer timescales. Bobcats and mountain lions temporarily delayed the use of sites recently visited by coyotes and black bears, respectively. And all predator species used sites sooner following the detection of a competitor in areas with higher relative abundances of prey (primarily white-tailed deer [Odocoileus virginianus]). Our results suggest attraction to shared habitats and prey resources influenced space use in the predator community more than avoidance of competitors. We propose that the effects of interspecific interactions on predator distributions were most evident for mesopredators because their trophic position requires balancing risks and rewards associated with prey, apex predators, and other mesopredators. In addition, relatively high densities of a common prey source likely facilitated the spatial coexistence in this predator community. Our study demonstrates the value of simultaneously assessing multiple interspecific interactions across different spatiotemporal scales to discern relationships within the predator guild.

Changing global climate and wildfire regimes are threatening forest resilience (i.e., the ability to recover from disturbance). Yet distinguishing areas of “no” versus “slow” postfire forest recovery is challenging, and consequences of sparse tree regeneration for plant communities and carbon dynamics are uncertain. We studied previously forested areas where tree regeneration remained sparse 34 years after the large, stand-replacing 1988 Yellowstone fires (Wyoming, USA) to ask the following questions: (1) What are the recovery pathways in areas of sparse and reduced forest recovery and how are they distributed across the landscape? (2) What explains variation in postfire tree regeneration density (total and by species) among sparse recovery pathways? (3) What are the implications of sparse recovery for understory plant communities? (4) How diminished are aboveground carbon stocks in areas of sparse postfire forest recovery? Tree densities and species-specific age distributions, understory plant communities, and carbon stocks were sampled in 55 plots during summer 2022. We detected three qualitatively distinct sparse recovery pathways (persistent sparse or non-forest, continuous tree infilling, and recent seedling and sapling establishment). Nearly half of the plots appeared “locked in” as persistently sparse or non-forest, while the remaining may be on a slow path to forest recovery. Plots with nearby upwind seed sources as well as in situ seed pressure from young postfire trees appear likely to recover to forest. Where trees were sparse or absent, plant communities resembled those found in meadows, capturing compositional changes expected to become more common with continued forest loss. However, forest-affinity species persisted in mesic locations, indicating mismatches between some plant communities and future forest change. Aboveground carbon stocks were low owing to minimal tree reestablishment. Almost all (96%) carbon was stored in coarse wood, a sharp departure from C storage patterns where forests are recovering. If not offset by future tree regeneration, decomposition of dead biomass will protract postfire aboveground carbon stock recovery. As global disturbance regimes and climate continue to change, determining the drivers of ecosystem reorganization and understanding how such changes will cascade to influence ecosystem structure and function will be increasingly important.

Climate change has led to pronounced shifts in phenology, varying across taxa. The Arctic is experiencing particularly rapid warming, but long-term data on phenological changes are rare in this region, especially for arthropods—a diverse taxonomic group that form important links to other trophic levels. Understanding the environmental drivers of arthropod phenological variation is necessary for predicting future trends across taxa and habitats to climate change. Here, we analyze temporal trends and climate associations in arthropod phenology using 25 years of standardized monitoring data from four habitat types in high-Arctic Greenland. We observed earlier peak activity in the arthropod community, with responses varying considerably among families and habitats. Snowmelt timing was a key driver of peak activity, especially for late-active taxa, while temperature was a less important driver, but arthropods generally exhibited earlier activity with warming. Responses in the duration of activity were more complex, with family- and habitat-specific responses to climate variation. Notably, taxa in habitats with late snowmelt responded strongly to snowmelt timing, while those in the pond habitat responded strongly to temperature. Mixed feeders and parasitoids showed rapid peak phenological shifts to earlier snowmelt and warming; however, mixed feeders shortened their activity periods, while parasitoids extended theirs. Our findings highlight the complexity of arthropod community phenological responses to climate change, with potential implications for trophic interactions dependent on temporal overlap. By analyzing phenological metrics across entire activity seasons for taxa with different functional and life-history traits, we identify general trends and consistent patterns that enhance our understanding of arthropod responses to climate change.

Host personality can markedly affect parasite transmission. Especially for parasites with indirect transmission through the environment, the effects of consistent among-individual differences in behavior may have both direct and indirect components. For example, personality may mediate both how hosts respond to infected individuals and the likelihood that hosts indirectly interact with infected conspecifics (e.g., by visiting patches infected hosts have previously contaminated). Integrating parasites, personality, and these different kinds of interaction networks constitutes a key step toward understanding transmission in natural systems. We evaluated these elements using a 5-year field study of a wild population of sleepy lizards, Tiliqua rugosa, and their tick parasites, which transmit among lizards through lizards' shared use of refuges. Using Bayesian models, we evaluated (1) predictors of lizard infestation probability and intensity (i.e., average tick count when infested) and (2) relationships among the predictors. We used the latter set of models to assess indirect relationships between the predictors and the infestation metrics. As predictors, we used lizards' infestation “risk” (derived from a time-lagged refuge sharing transmission network), traits (sex, mass, and the personality axes aggression and boldness), space use (number of unique refuges used and home range overlap with other lizards), and measures of synchronous social interactions (i.e., edge weight and degree). We found both indirect and direct connections between our predictors and tick infestation. For example, boldness was positively directly associated with infection intensity and indirectly positively associated with both infestation probability and intensity via intermediary connections with social network interaction and risk. Using more unique refuges, on the other hand, was indirectly negatively associated with infestation probability (via reduced risk), but directly positively associated with infestation probability, indicating a potential trade-off in the anti-parasite benefits of using more refuges. Our results emphasize that (1) multiple aspects of host behavior may associate with parasite infection, (2) these components may proceed through both direct and indirect pathways, and (3) multiple pathways should be considered together because the pathways may have compounding or counteracting effects.

Climate change and river regulation alter environmental controls on riparian plant occurrence and cover worldwide. Simultaneous changes to river flow and air temperature could result in unanticipated plant responses to novel environmental conditions. Increasing temperature could alter riparian plant response to hydrology and other factors, while river regulation may exacerbate environmental stress through novel flows like those resulting from power generation. Further, plant establishment and growth may require differing conditions, which may be decoupled by novel conditions. Using a large dataset that spans a natural 5°C mean annual temperature (MAT) gradient and a Bayesian model that integrates plant occurrence and cover, we address four questions: (1) Does hotter MAT modify plant response to hydrology, substrate composition, topography, and cover of co-occurring plant species? (2) Does the timing of hydropower tides benefit some species over others? (3) Does dam-induced erosion hinder riparian species more than upland species? (4) Do occurrence and cover respond to different environmental variables, allowing for decoupling of life history processes? We addressed these questions with data collected along 364 km of the Colorado River downstream of Glen Canyon Dam, Arizona, United States of America. Occurrence and cover class were recorded in >10,000 plots from 2016 to 2020, along with environmental covariates that repeat across the climate gradient. For 36 species, plant occurrence and cover were modeled with respect to MAT, hydrology, substrate, topography, other plant cover, and their interactions with MAT. There were four key results. (1) Increasing MAT will not only directly influence plants but will mediate their responses to the environment, including greater dependence on stable water supplies. (2) The timing of hydropower tides shapes plant community composition. (3) Dam-related erosion has an outsized effect on riparian species, which could lead to a loss of regionally unique plant species. (4) For all species, the most important covariates driving occurrence differed from those for cover, suggesting the potential for these life stages to be decoupled. Not only will climate change and river regulation independently alter plant distributions, interactions among hotter temperature, dam-controlled flow patterns, and limited fine sediments will determine which species flourish or perish under future conditions.

Natural and anthropogenic stressors alter the composition, biomass, and nutritional quality of primary producers and microorganisms, the basal organisms that synthesize the biomolecules essential for metazoan growth and survival (i.e., basal resources). Traditional biomarkers have provided valuable insight into the spatiotemporal dynamics of basal resource use, but lack specificity in identifying multiple basal organisms, can be confounded by environmental and physiological processes, and do not always preserve in tissues over long timescales. Carbon stable isotope ratios of essential amino acids (δ¹³C-EAA) show remarkable promise in identifying and distinguishing clades of basal organisms with unique δ¹³C-EAA fingerprints that are independent of trophic processing and environmental variability, providing unparalleled potential in their application. Understanding the biochemical processes that underpin δ¹³C-AA data is crucial, however, for holistic and robust inferences in ecological applications. This comprehensive methodological review, for the first time, conceptualizes these mechanistic underpinnings that drive δ¹³C-EAA fingerprints among basal organisms and incorporates δ¹³C values of non-essential amino acids that are generally overlooked in ecological studies, despite the gain of metabolic information. We conduct meta-analyses of published data to test hypothesized AA-specific isotope fractionations among basal organism clades, demonstrating that phenylalanine separates vascular plant δ¹³C-EAA fingerprints, which strongly covaries with their phylogeny. We further explore the utility of non-essential AAs in separating dietary protein sources of archaeological humans, showing the differences in metabolic information contained within different NEAAs. By scrutinizing the many methodologies that are applied in the field, we highlight the absence of standardized analytical protocols, particularly in sample pretreatments leading to biases, inappropriate use of statistical methods, and reliance on unsuitable training data. To unlock the full potential of δ¹³C-EAA fingerprints, we provide in-depth explanations on knowledge gaps, pitfalls, and optimal practices in this complex but powerful approach for assessing ecosystem change across spatiotemporal scales.

Variance partitioning is a common tool for statistical analysis and interpretation in both observational and experimental studies in ecology. Its popularity has led to a proliferation of methods with sometimes confusing or contradicting interpretations. Here, we present variance partitioning in a model-based Bayesian framework as a general tool for summarizing and interpreting regression-like models to produce additional insight on ecological studies compared with what traditional parameter inference of these models on its own can reveal. For example, we propose predictive variance partitioning as a tool to extend sample-based analyses to analyses of whole populations or predictive scenarios. We also extend variance partitioning to encompass partitioning of variance within and between ecologically relevant subgroups of the observations, or the whole population of interest, to provide information on how the relative roles of processes underlying the study system may vary depending on the environmental or ecological context. We discuss the role of correlated covariates and random effects and highlight uncertainty quantification in variance partitioning. To showcase the utility of our approach, we present a case study comprising a simple occupancy model for a metapopulation of the Glanville fritillary butterfly. As a result, we demonstrate model-based variance partitioning as a general and rigorous statistical tool to gain more insight from ecological data.