Warming associated with climate change will advance the onset of spring phenology for many forest plants across the Eastern United States. Understory forbs and spring ephemerals that fix a disproportionate amount of carbon during early spring may be negatively affected by earlier canopy closure; however, information on the spatial patterns of phenological change for these communities is still lacking. To assess the potential for changes in spring phenological windows, we synthesized observations from the Appalachian Mountain Club's (AMCs) Mountain Watch (MW) project, the National Phenology Network (NPN), and AMC's iNaturalist projects between 2004 and 2022 (n = 118,250) across the length of the Appalachian Trail (AT) Corridor (34° N–46° N latitude). We used hierarchical Bayesian modeling to examine the sensitivity of spring flowering and leaf-out for 11 understory species and 14 canopy tree species to mean spring temperature (April–June). We conducted analyses across the AT Corridor, partitioned by regions of 4° latitude (south, mid-Atlantic, and north). Spring phenologies for both understory plants and canopy trees advanced with warming (~6 and ~3 days/°C, respectively). However, the sensitivity of each group varied by latitude, with the phenology of trees and understory plants advancing to a greater degree in the mid-Atlantic region (~10 days/°C) than in the southern or northern regions (~5 days/°C). While we find evidence that phenological windows remain stable in the southern and mid-Atlantic portions of the AT, we observed an expansion of the spring phenological window in the north where there was greater understory forb temperature sensitivity compared with trees (~2.7 days/°C). Our analyses indicate the differential sensitivity of forest plant phenology to potential warming across a large latitudinal gradient in the Eastern United States. Further, evidence for a temperature-driven expansion of the spring phenological window suggests a potential beneficial effect for understory plants in the northern AT, although phenological mismatch with potential pollinators and increased vulnerability to late winter frosts are possible. Using extensive citizen-science datasets allows us to synthesize regional- and continental-scale data to explore spatial and temporal trends in spring phenology related to warming. Such data can help to standardize approaches in phenological research and its application to forest climate resiliency.
Patterns of population connectivity shape ecological and evolutionary phenomena from population persistence to local adaptation and can inform conservation strategy. Connectivity patterns emerge from the interaction of individual behavior with a complex and heterogeneous environment. Despite ample observation that dispersal patterns vary through time, the extent to which variation in the physical environment can explain emergent connectivity variation is not clear. Empirical studies of its contribution promise to illuminate a potential source of variability that shapes the dynamics of natural populations. We leveraged simultaneous direct dispersal observations and oceanographic transport simulations of the clownfish Amphiprion clarkii in the Camotes Sea, Philippines, to assess the contribution of oceanographic variability to emergent variation in connectivity. We found that time-varying oceanographic simulations on both annual and monsoonal timescales partly explained the observed dispersal patterns, suggesting that temporal variation in oceanographic transport shapes connectivity variation on these timescales. However, interannual variation in observed mean dispersal distance was nearly 10 times the expected variation from biophysical simulations, revealing that additional biotic and abiotic factors contribute to interannual connectivity variation. Simulated dispersal kernels also predicted a smaller scale of dispersal than the observations, supporting the hypothesis that undocumented abiotic factors and behaviors such as swimming and navigation enhance the probability of successful dispersal away from, as opposed to retention near, natal sites. Our findings highlight the potential for coincident observations and biophysical simulations to test dispersal hypotheses and the influence of temporal variability on metapopulation persistence, local adaptation, and other population processes.
Animals disperse seeds in various ways that affect seed deposition sites and seed survival, ultimately shaping plant species distribution, community composition, and ecosystem structure. Some animal species can disperse seeds through multiple pathways (e.g., defecation, regurgitation, epizoochory), each likely producing distinct seed dispersal outcomes. We studied how seed traits (size and toughness) interact with disperser species to influence seed dispersal pathway and how this ultimately shapes the proportion of seeds deposited in various habitat types. We focused on three frugivorous species of duikers (African forest antelopes) in the Dja Faunal Reserve, a tropical rainforest in southern Cameroon. Duikers can both defecate and regurgitate seeds, the latter predominantly occurring during rumination at their bedding sites (or “nests”). We located duiker nests and dungs along 18 linear 1-km-transects to assess: (1) how seed traits affect the likelihood of dispersal via defecation versus regurgitation, (2) if defecated versus regurgitated seeds are deposited at different rates in different forest types (assessed by indigenous Baka), microhabitats, and forest structural attributes (measured by drone lidar), and (3) if these differ between three duiker species that vary in size and diel activity patterns. We found that duikers predominantly defecated small seeds (<3 mm length) and regurgitated larger and tougher seeds (>10 mm length), the latter including 25 different plant species. The three duiker species varied in their nesting habits, with nocturnal bay duikers (Cephalophus dorsalis) nesting in dense understory vegetation at proportions 3–4 times higher than Peter's and yellow-backed duikers (Cephalophus callipygus and Cephalophus silvicultor). As a result, bay duikers deposited larger regurgitated seeds at a higher rate in habitats with denser understory where lianas and palms predominate and near fallen trees. This directed regurgitation seed deposition likely plays an important and unique role in forest succession and structure. This study highlights the importance of ungulate seed dispersal by regurgitation, a vastly understudied process that could impact many ecosystems given the prevalence of ruminating ungulates worldwide.
The seasonal timing and magnitude of photosynthesis in evergreen needleleaf forests (ENFs) has major implications for the carbon cycle and is increasingly sensitive to changing climate. Earlier spring photosynthesis can increase carbon uptake over the growing season or cause early water reserve depletion that leads to premature cessation and increased carbon loss. Determining the start and the end of the growing season in ENFs is challenging due to a lack of field measurements and difficulty in interpreting satellite data, which are impacted by snow and cloud cover, and the pervasive “greenness” of these systems. We combine continuous needle-scale chlorophyll fluorescence measurements with tower-based remote sensing and gross primary productivity (GPP) estimates at three ENF sites across a latitudinal gradient (Colorado, Saskatchewan, Alaska) to link physiological changes with remote sensing signals during transition seasons. We derive a theoretical framework for observations of solar-induced chlorophyll fluorescence (SIF) and solar intensity-normalized SIF (SIFrelative) under snow-covered conditions, and show decreased sensitivity compared with reflectance data (~20% reduction in measured SIF vs. ~60% reduction in near-infrared vegetation index [NIRv] under 50% snow cover). Needle-scale fluorescence and photochemistry strongly correlated (r2 = 0.74 in Colorado, 0.70 in Alaska) and showed good agreement on the timing and magnitude of seasonal transitions. We demonstrate that this can be scaled to the site level with tower-based estimates of LUEP and SIFrelative which were well correlated across all sites (r2 = 0.70 in Colorado, 0.53 in Saskatchewan, 0.49 in Alaska). These independent, temporally continuous datasets confirm an increase in physiological activity prior to snowmelt across all three evergreen forests. This suggests that data-driven and process-based carbon cycle models which assume negligible physiological activity prior to snowmelt are inherently flawed, and underscores the utility of SIF data for tracking phenological events. Our research probes the spectral biology of evergreen forests and highlights spectral methods that can be applied in other ecosystems.
Peatlands cover approximately 12% of the Canadian landscape and play an important role in the carbon cycle through their centennial- to millennial-scale storage of carbon under waterlogged and anoxic conditions. In recognizing the potential of these ecosystems as natural climate solutions and therefore the need to include them in national greenhouse gas inventories, the Canadian Model for Peatlands module (CaMP v. 2.0) was developed by the Canadian Forest Service. Model parameterization included compiling peat profiles across Canada to calibrate peat decomposition rates from different peatland types, to define typical bulk density profiles, and to describe the hydrological (i.e., water table) response of peatlands to climatic changes. A total of 1217 sites were included in the dataset from published and unpublished sources. The CORESITES table contains site location and summary data for each profile, as well as an estimate of total carbon mass per unit area (in megagrams of C per hectare). Total carbon mass per unit area at each location was calculated using bulk density and carbon content through each profile. The PROFILES table contains data for depth (in centimeters), bulk density (in grams per cubic meter), ash and carbon content (in percentage), and material descriptions for contiguous samples through each peat profile. Data gaps for bulk density and C content were filled using interpolation, regression trees, and assigned values based on material description and/or soil classification to allow for the estimation of total carbon mass per unit area. A subset of the sites (N = 374) also have pH and pore water trace-elemental geochemistry data and are found in the WATER table. The REFERENCES table contains the full citation of each source of the data and is linked to each core location through the SOURCEDATA table. The LOOKUP table defines codes in the database that required more space that what was sufficient in the metadata tables. The data can be accessed on Open Government Canada and will be useful for future work on carbon stock mapping and ecosystem modeling. All metadata and data are provided © Her Majesty the Queen in Right of Canada, 2023 and information contained in this publication may be reproduced for personal or public noncommercial purposes with attribution, whereas commercial reproduction and distribution are prohibited except with written permission from NRCan; complete details are noted in the Supporting Information file Metadata S1 (see Class III.B.3: Copyright restrictions).
When planning abundance surveys, the impact of search intensity on the quality of the density estimates is rarely considered. We constructed a time-budget modeling framework for abundance surveys using principles from optimal foraging theory. We link search intensity to the number of sample units surveyed, searcher detection probability, the number of detections made, and the precision of the estimated population density. This framework allowed us to determine how a searcher should behave to produce optimized density estimates. Using data collected from quadrat and removal surveys of zebra mussels (Dreissena polymorpha) in central Minnesota, we applied this framework to evaluate potential improvements. We found that by tuning searcher behavior, density estimates from removal surveys of zebra mussels could be improved by up to 60% in some cases, without changing the overall survey time. Our framework also predicts a critical population density where the best survey method switches from removal surveys at low densities to quadrat surveys at high densities, consistent with past empirical work. In addition, we provide simulation tools to apply this form of analysis to a number of other commonly used survey designs. Our results provide insights into how to improve the performance of many survey methods in high-density environments by either tuning searcher behavior or decoupling the estimation of population density and detection probability.
Associational effects, whereby plants influence the biotic interactions of their neighbors, are an important component of plant–insect interactions. Plant chemistry has been hypothesized to mediate these interactions. The role of chemistry in associational effects, however, has been unclear in part because the diversity of plant chemistry makes it difficult to tease apart the importance and roles of particular classes of compounds. We examined the chemical ecology of associational effects using backcross-bred plants of the Solanum pennellii introgression lines. We used eight genotypes from the introgression line system to establish 14 unique neighborhood treatments that maximized differences in acyl sugars, proteinase inhibitor, and terpene chemical diversity. We found that the chemical traits of the neighboring plant, rather than simply the number of introgression lines within a neighborhood, influenced insect abundance on focal plants. Furthermore, within-chemical class diversity had contrasting effects on herbivore and predator abundances, and depended on the frequency of neighboring plant chemotypes. Notably, we found insect mobility—flying versus crawling—played a key role in insect response to phytochemistry. We highlight that the frequency and chemical phenotype of plant neighbors underlie associational effects and suggest this may be an important mechanism in maintaining intraspecific phytochemical variation within plant populations.
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