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Creators/Authors contains: "Elmendorf, Sarah C."

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  1. ; ( , Scientific Reports)
    Abstract Tundra plants are widely considered to be constrained by cool growing conditions and short growing seasons. Furthermore, phenological development is generally predicted by daily heat sums calculated as growing degree days. Analyzing over a decade of seasonal flower counts of 23 plant species distributed across four plant communities, together with hourly canopy-temperature records, we show that the timing of flowering of many tundra plants are best predicted by a modified growing degree day model with a maximum temperature threshold. Threshold maximums are commonly employed in agriculture, but until recently have not been considered for natural ecosystems and to our knowledge have not been used for tundra plants. Estimated maximum temperature thresholds were found to be within the range of daily temperatures commonly experienced for many species, particularly for plants at the colder, high Arctic study site. These findings provide an explanation for why passive experimental warming—where moderate changes in mean daily temperatures are accompanied by larger changes in daily maximum temperatures—generally shifts plant phenology less than ambient warming. Our results also suggest that many plants adapted to extreme cold environments may have limits to their thermal responsiveness. 
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    Free, publicly-accessible full text available December 1, 2024
  2. ; ; ; ; ; ( , Annals of Botany)
    Abstract Background and Aims

    The Arctic is warming at an alarming rate, leading to earlier spring conditions and plant phenology. It is often unclear to what degree changes in reproductive fitness (flower, fruit and seed production) are a direct response to warming versus an indirect response through shifting phenology. The aim of this study was to quantify the relative importance of these direct and indirect pathways and project the net effects of warming on plant phenology and reproductive fitness under current and future climate scenarios.

     Methods

    We used two long-term datasets on 12 tundra species in the Canadian Arctic as part of the International Tundra Experiment (ITEX). Phenology and reproductive fitness were recorded annually on tagged individual plants at both Daring Lake, Northwest Territories (64° 52' N, - 111° 35' W) and Alexandra Fiord, Nunavut (78° 49' N, - 75° 48' W). The plant species encompassed a wide taxonomic diversity across a range of plant functional types with circumpolar/boreal distributions. We used hierarchical Bayesian structural equation models to compare the direct and indirect effects of climate warming on phenology and reproductive fitness across species, sites and years.

     Key Results

    We found that warming, both experimental and ambient, drove earlier flowering across species, which led to higher numbers of flowers and fruits produced, reflecting directional phenotypic selection for earlier flowering phenology. Furthermore, this indirect effect of climate warming mediated through phenology was generally about two to three times stronger than the direct effect of climate on reproductive fitness. Under future climate predictions, individual plants showed a ~2- to 4.5-fold increase in their reproductive fitness (flower counts) with advanced flowering phenology.

     Conclusions

    Our results suggest that, on average, the benefits of early flowering, such as increased development time and subsequent enhanced reproductive fitness, might outweigh its risks. Overall, this work provides important insights into population-level consequences of phenological shifts in a warming Arctic over multi-decadal time scales.

     
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  3. ; ; ; ; ; ; ; ( , Remote Sensing)
    Plot-level photography is an attractive time-saving alternative to field measurements for vegetation monitoring. However, widespread adoption of this technique relies on efficient workflows for post-processing images and the accuracy of the resulting products. Here, we estimated relative vegetation cover using both traditional field sampling methods (point frame) and semi-automated classification of photographs (plot-level photography) across thirty 1 m2 plots near Utqiaġvik, Alaska, from 2012 to 2021. Geographic object-based image analysis (GEOBIA) was applied to generate objects based on the three spectral bands (red, green, and blue) of the images. Five machine learning algorithms were then applied to classify the objects into vegetation groups, and random forest performed best (60.5% overall accuracy). Objects were reliably classified into the following classes: bryophytes, forbs, graminoids, litter, shadows, and standing dead. Deciduous shrubs and lichens were not reliably classified. Multinomial regression models were used to gauge if the cover estimates from plot-level photography could accurately predict the cover estimates from the point frame across space or time. Plot-level photography yielded useful estimates of vegetation cover for graminoids. However, the predictive performance varied both by vegetation class and whether it was being used to predict cover in new locations or change over time in previously sampled plots. These results suggest that plot-level photography may maximize the efficient use of time, funding, and available technology to monitor vegetation cover in the Arctic, but the accuracy of current semi-automated image analysis is not sufficient to detect small changes in cover. 
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  4. ; ; ; ; ; ; ; ; ; ; et al ( , Arctic Science)
    Open top chambers (OTCs) were adopted as the recommended warming mechanism by the International Tundra Experiment (ITEX) network in the early 1990’s. Since then, OTCs have been deployed across the globe. Hundreds of papers have reported the impacts of OTCs on the abiotic environment and the biota. Here we review the impacts of the OTC on the physical environment, with comments on the appropriateness of using OTCs to characterize the response of biota to warming. The purpose of this review is to guide readers to previously published work and to provide recommendations for continued use of OTCs to understand the implications of warming on low stature ecosystems. In short, the OTC is a useful tool to experimentally manipulate temperature, however the characteristics and magnitude of warming varies greatly in different environments, therefore it is important to document chamber performance to maximize the interpretation of biotic response. When coupled with long-term monitoring, warming experiments are a valuable means to understand the impacts of climate change on natural ecosystems. 
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  5. ; ( , Proceedings of the National Academy of Sciences)
  6. ; ; ; ; ; ; ; ; ; ( , Journal of Ecology)
    Abstract

    Fine‐scale microclimate variation due to complex topography can shape both current vegetation distributional patterns and how vegetation responds to changing climate. Topographic heterogeneity in mountains is hypothesized to mediate responses to regional climate change at the scale of metres. For alpine vegetation especially, the interplay between changing temperatures and topographically mediated variation in snow accumulation will determine the overall impact of climate change on vegetation dynamics.

    We combined 30 years of co‐located measurements of temperature, snow and alpine plant community composition in Colorado, USA, to investigate vegetation community trajectories across a snow depth gradient.

    Our analysis of long‐term trends in plant community composition revealed notable directional change in the alpine vegetation with warming temperatures. Furthermore, community trajectories are divergent across the snow depth gradient, with exposed parts of the landscape that experience little snow accumulation shifting towards stress‐tolerant, cold‐ and drought‐adapted communities, while snowier areas shifted towards more warm‐adapted communities.

    Synthesis: Our findings demonstrate that fine‐scale topography can mediate both the magnitude and direction of vegetation responses to climate change. We documented notable shifts in plant community composition over a 30‐year period even though alpine vegetation is known for slow dynamics that often lag behind environmental change. These results suggest that the processes driving alpine plant population and community dynamics at this site are strong and highly heterogeneous across the complex topography that is characteristic of high‐elevation mountain systems.

     
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  7. ; ; ; ; ; ; ( , Ecology Letters)
    Abstract

    Global change is altering patterns of community assembly, with net outcomes dependent on species' responses to the abiotic environment, both directly and mediated through biotic interactions. Here, we assess alpine plant community responses in a 15‐year factorial nitrogen addition, warming and snow manipulation experiment. We used a dynamic competition model to estimate the density‐dependent and ‐independent processes underlying changes in species‐group abundances over time. Density‐dependent shifts in competitive interactions drove long‐term changes in abundance of species‐groups under global change while counteracting environmental drivers limited the growth response of the dominant species through density‐independent mechanisms. Furthermore, competitive interactions shifted with the environment, primarily with nitrogen and drove non‐linear abundance responses across environmental gradients. Our results highlight that global change can either reshuffle species hierarchies or further favour already‐dominant species; predicting which outcome will occur requires incorporating both density‐dependent and ‐independent mechanisms and how they interact across multiple global change factors.

     
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  8. ; ; ; ; ; ; ; ; ; ; et al ( , Nature Communications)
    null (Ed.)
    Abstract Rapid climate warming is altering Arctic and alpine tundra ecosystem structure and function, including shifts in plant phenology. While the advancement of green up and flowering are well-documented, it remains unclear whether all phenophases, particularly those later in the season, will shift in unison or respond divergently to warming. Here, we present the largest synthesis to our knowledge of experimental warming effects on tundra plant phenology from the International Tundra Experiment. We examine the effect of warming on a suite of season-wide plant phenophases. Results challenge the expectation that all phenophases will advance in unison to warming. Instead, we find that experimental warming caused: (1) larger phenological shifts in reproductive versus vegetative phenophases and (2) advanced reproductive phenophases and green up but delayed leaf senescence which translated to a lengthening of the growing season by approximately 3%. Patterns were consistent across sites, plant species and over time. The advancement of reproductive seasons and lengthening of growing seasons may have significant consequences for trophic interactions and ecosystem function across the tundra. 
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  9. ; ; ; ; ; ; ; ; ; ; et al ( , Arctic Science)
    Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates. 
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  10. ; ; ; ; ; ; ; ; ; ; et al ( , Ecology)
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