54 research outputs found
Non-serotinous woody plants behave as aerial seed bank species when a late-summer wildfire coincides with a mast year
1. Trees which lack obvious fire-adaptive traits such as serotinous seed-bearing structures or vegetative resprouting are assumed to be at a dramatic disadvantage in recolonization via sexual recruitment after fire, because seed dispersal is invariably quite constrained. We propose an alternative strategy in masting tree species with woody cones or cone-like structures: that the large clusters of woody tissue in a mast year will sufficiently impede heat transfer that a small fraction of seeds can survive the flaming front passage; in a mast year, this small fraction would be a very large absolute number.
2. In Kootenay National Park in British Columbia, we examined regeneration by Engelmann spruce (Picea engelmannii), a non-serotinous conifer, after two fires, both of which coincided with mast years. Coupling models of seed survivorship within cones and seed maturation schedule to a spatially realistic recruitment model, we show that (1) the spatial pattern of seedlings on a 630 m transect from the forest edge into the burn was best explained if there was in situ seed dissemination by burnt trees; (2) in areas several hundred meters from any living trees, recruitment density was well correlated with local prefire cone density; and (3) spruce was responding exactly like its serotinous codominant, lodgepole pine (Pinus contorta).
3. We conclude that non-serotinous species can indeed behave like aerial seed bank species in mast years if the fire takes place late in the seed maturation period. Using the example of the circumpolar boreal forest, while the joint probability of a mast year and a late-season fire will make this type of event rare (we estimate P = 0.1), nonetheless, it would permit a species lacking obvious fire-adapted traits to occasionally establish a widespread and abundant cohort on a large part of the landscape
Intraspecific Trait Variation and Phenotypic Plasticity Mediate Alpine Plant Species Response to Climate Change
In a rapidly changing climate, alpine plants may persist by adapting to new conditions. However, the rate at which the climate is changing might exceed the rate of adaptation through evolutionary processes in long-lived plants. Persistence may depend on phenotypic plasticity in morphology and physiology. Here we investigated patterns of leaf trait variation including leaf area, leaf thickness, specific leaf area, leaf dry matter content, leaf nutrients (C, N, P) and isotopes (δ13C and δ15N) across an elevation gradient on Gongga Mountain, Sichuan Province, China. We quantified inter- and intra-specific trait variation and the plasticity in leaf traits of selected species to experimental warming and cooling by using a reciprocal transplantation approach. We found substantial phenotypic plasticity in most functional traits where δ15N, leaf area, and leaf P showed greatest plasticity. These traits did not correspond with traits with the largest amount of intraspecific variation. Plasticity in leaf functional traits tended to enable plant populations to shift their trait values toward the mean values of a transplanted plants’ destination community, but only if that population started with very different trait values. These results suggest that leaf trait plasticity is an important mechanism for enabling plants to persist within communities and to better tolerate changing environmental conditions under climate change
The acquisitive–conservative axis of leaf trait variation emerges even in homogeneous environments
The acquisitive-conservative axis of plant ecological strategies results in a pattern of leaf trait covariation that captures the balance between leaf construction costs and plant growth potential. Studies evaluating trait covariation within species are scarcer, and have mostly dealt with variation in response to environmental gradients. Little work has been published on intraspecific patterns of leaf trait covariation in the absence of strong environmental variation.Methods: We analysed covariation of four leaf functional traits (SLA: specific leaf area, LDMC: leaf dry matter content, Ft: force to tear, and Nm: leaf nitrogen content) in six Poaceae and four Fabaceae species common in the dry Chaco forest of Central Argentina, growing in the field and in a common garden. We compared intraspecific covariation patterns (slopes, correlation and effect size) of leaf functional traits with global interspecific covariation patterns. Additionally, we checked for possible climatic and edaphic factors that could affect the intraspecific covariation pattern.Key Results: We found negative correlations for the LDMC-SLA, Ft-SLA, LDMC-Nm , and Ft-Nm trait pairs. This intraspecific covariation pattern found both in the field and in the common garden and not be explained by climatic or edaphic variation in the field follows the expected acquisitive-conservative axis. At the same time, we found quantitative differences in slopes among different species, and between these intraspecific patterns and the interspecific ones. Many of these differences seem to be idiosyncratic, but some appear consistent among species (e.g.all the intraspecific LDMC-SLA and LDMC-Nm slopes tend to be shallower than the global).Conclusions: Our study indicates that the acquisitive-conservative leaf functional trait covariation pattern occurs at the intraspecific level even in the absence of relevant environmental variation in the field. This suggests a high degree of variation-covariation in leaf functional traits not driven by environmental variables.Fil: Gorne, Lucas Damián. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - CĂłrdoba. Instituto Multidisciplinario de BiologĂa Vegetal. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas FĂsicas y Naturales. Instituto Multidisciplinario de BiologĂa Vegetal; Argentina. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas, FĂsicas y Naturales; ArgentinaFil: DĂaz, Sandra Myrna. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - CĂłrdoba. Instituto Multidisciplinario de BiologĂa Vegetal. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas FĂsicas y Naturales. Instituto Multidisciplinario de BiologĂa Vegetal; Argentina. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas, FĂsicas y Naturales; ArgentinaFil: Minden, Vanessa. University of Oldenburg; Alemania. Vrije Universiteit Brussel; BĂ©lgicaFil: Onoda, Yusuke. Kyoto University. School of Agriculture; JapĂłnFil: Kramer, Koen. Wageningen University; PaĂses BajosFil: Muir, Christopher. University Of Hawaii; Estados UnidosFil: Michaletz, Sean T. University of British Columbia; CanadáFil: Lavorel, Sandra. Centre National de la Recherche Scientifique; FranciaFil: Sharpe, Joanne. Sharplex Services, Edgecomb; Estados UnidosFil: Jansen, Steven. Universitat Ulm; AlemaniaFil: Slot, Martijn. Smithsonian Tropical Research Institute; PanamáFil: Chacon, Maximiliano Eduardo. Universidad de Costa Rica; Costa RicaFil: Boenisch, Gerhard. Max Planck Institute For Biogeochemistry; Alemani
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Continental scale structuring of forest and soil diversity via functional traits.
Trait-based ecology claims to offer a mechanistic approach for explaining the drivers that structure biological diversity and predicting the responses of species, trophic interactions and ecosystems to environmental change. However, support for this claim is lacking across broad taxonomic groups. A framework for defining ecosystem processes in terms of the functional traits of their constituent taxa across large spatial scales is needed. Here, we provide a comprehensive assessment of the linkages between climate, plant traits and soil microbial traits at many sites spanning a broad latitudinal temperature gradient from tropical to subalpine forests. Our results show that temperature drives coordinated shifts in most plant and soil bacterial traits but these relationships are not observed for most fungal traits. Shifts in plant traits are mechanistically associated with soil bacterial functional traits related to carbon (C), nitrogen (N) and phosphorus (P) cycling, indicating that microbial processes are tightly linked to variation in plant traits that influence rates of ecosystem decomposition and nutrient cycling. Our results are consistent with hypotheses that diversity gradients reflect shifts in phenotypic optima signifying local temperature adaptation mediated by soil nutrient availability and metabolism. They underscore the importance of temperature in structuring the functional diversity of plants and soil microbes in forest ecosystems and how this is coupled to biogeochemical processes via functional traits
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Biogeographic patterns of soil diazotrophic communities across six forests in North America.
Soil diazotrophs play important roles in ecosystem functioning by converting atmospheric N2 into biologically available ammonium. However, the diversity and distribution of soil diazotrophic communities in different forests and whether they follow biogeographic patterns similar to macroorganisms still remain unclear. By sequencing nifH gene amplicons, we surveyed the diversity, structure and biogeographic patterns of soil diazotrophic communities across six North American forests (126 nested samples). Our results showed that each forest harboured markedly different soil diazotrophic communities and that these communities followed traditional biogeographic patterns similar to plant and animal communities, including the taxa-area relationship (TAR) and latitudinal diversity gradient. Significantly higher community diversity and lower microbial spatial turnover rates (i.e. z-values) were found for rainforests (~0.06) than temperate forests (~0.1). The gradient pattern of TARs and community diversity was strongly correlated (r(2) > 0.5) with latitude, annual mean temperature, plant species richness and precipitation, and weakly correlated (r(2) < 0.25) with pH and soil moisture. This study suggests that even microbial subcommunities (e.g. soil diazotrophs) follow general biogeographic patterns (e.g. TAR, latitudinal diversity gradient), and indicates that the metabolic theory of ecology and habitat heterogeneity may be the major underlying ecological mechanisms shaping the biogeographic patterns of soil diazotrophic communities
Intraspecific trait variability is a key feature underlying high Arctic plant community resistance to climate warming
In the high Arctic, plant community species composition generally responds slowly to climate warming, whereas less is known about the community functional trait responses and consequences for ecosystem functioning. The slow species turnover and large distribution ranges of many Arctic plant species suggest a significant role of intraspecific trait variability in functional responses to climate change. Here we compare taxonomic and functional community compositional responses to a long-term (17-year) warming experiment in Svalbard, Norway, replicated across three major high Arctic habitats shaped by topography and contrasting snow regimes. We observed taxonomic compositional changes in all plant communities over time. Still, responses to experimental warming were minor and most pronounced in the drier habitats with relatively early snowmelt timing and long growing seasons (Cassiope and Dryas heaths). The habitats were clearly separated in functional trait space, defined by 12 size- and leaf economics-related traits, primarily due to interspecific trait variation. Functional traits also responded to experimental warming, most prominently in the Dryas heath and mostly due to intraspecific trait variation. Leaf area and mass increased and leaf δ15N decreased in response to the warming treatment. Intraspecific trait variability ranged between 30% and 71% of the total trait variation, reflecting the functional resilience of those communities, dominated by long-lived plants, due to either phenotypic plasticity or genotypic variation, which most likely underlies the observed resistance of high Arctic vegetation to climate warming. We further explored the consequences of trait variability for ecosystem functioning by measuring peak season CO2 fluxes. Together, environmental, taxonomic, and functional trait variables explained a large proportion of the variation in net ecosystem exchange (NEE), which increased when intraspecific trait variation was accounted for. In contrast, even though ecosystem respiration and gross ecosystem production both increased in response to warming across habitats, they were mainly driven by the direct kinetic impacts of temperature on plant physiology and biochemical processes. Our study shows that long-term experimental warming has a modest but significant effect on plant community functional trait composition and suggests that intraspecific trait variability is a key feature underlying high Arctic ecosystem resistance to climate warming.publishedVersio
Tree water dynamics in a drying and warming world
Disentangling the relative impacts of precipitation reduction and vapour pressure deficit (VPD) on plant water dynamics and determining whether acclimation may influence these patterns in the future is an important challenge. Here, we report sap flux density (FD), stomatal conductance (Gs), hydraulic conductivity (KL) and xylem anatomy in piñon pine (Pinus edulis) and juniper (Juniperus monosperma) trees subjected to five years of precipitation reduction, atmospheric warming (elevated VPD) and their combined effects. No acclimation occurred under precipitation reduction: lower Gs and FD were found for both species compared to ambient conditions. Warming reduced the sensibility of stomata to VPD for both species but resulted in the maintenance of Gs and FD to ambient levels only for piñon. For juniper, reduced soil moisture under warming negated benefits of stomatal adjustments and resulted in reduced FD, Gs and KL. Although reduced stomatal sensitivity to VPD also occurred under combined stresses, reductions in Gs, FD and KL took place to similar levels as under single stresses for both species. Our results show that stomatal conductance adjustments to high VPD could minimize but not entirely prevent additive effects of warming and drying on water use and carbon acquisition of trees in semi-arid regions.The Los Alamos Survival-Mortality (SUMO) Experiment was funded by the US Department of Energy, Office of Science, Biological and Environmental Research. C.G. and S.M. were supported by a Director’s Fellowship from the Los Alamos National Laboratory. A.V. was supported by a fellowship from Generalitat Valenciana (BEST/2016/289) and the project Survive-2 (CGL2015-69773-C2-2-P MINECO/FEDER) from the Spanish Government. CEAM is funded by Generalitat Valenciana
Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data
The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400-2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values (r (2) = 0.61-0.88, RMSEmean = 12%-64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic.Peer reviewe
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Open Science principles for accelerating trait-based science across the Tree of Life.
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges
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