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Images from time-lapse cameras were analyzed to track the greenness curves of 16 plots in the Sensor Network at Niwot Ridge. Images were taken every 30 minutes during daylight hours throughout the growing season. Cameras were angled to view 1m^2 vegetation plots located at each sensor node. Pixels in the portion of the image capturing the vegetation plot were used to calculate the green chromatic coordinate (GCC). The change in GCC over the growing season represents the growth and phenology of the plant communities captured. 

Abstract Climate‐induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector‐borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecasts of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits that may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait‐based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi‐scale forecasts of mosquito population dynamics and phenology for diverse stakeholders. 

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. 

Abstract The Arctic is warming four times faster than the global average¹and plant communities are responding through shifts in species abundance, composition and distribution^2–4. However, the direction and magnitude of local changes in plant diversity in the Arctic have not been quantified. Using a compilation of 42,234 records of 490 vascular plant species from 2,174 plots across the Arctic, here we quantified temporal changes in species richness and composition through repeat surveys between 1981 and 2022. We also identified the geographical, climatic and biotic drivers behind these changes. We found greater species richness at lower latitudes and warmer sites, but no indication that, on average, species richness had changed directionally over time. However, species turnover was widespread, with 59% of plots gaining and/or losing species. Proportions of species gains and losses were greater where temperatures had increased the most. Shrub expansion, particularly of erect shrubs, was associated with greater species losses and decreasing species richness. Despite changes in plant composition, Arctic plant communities did not become more similar to each other, suggesting no biotic homogenization so far. Overall, Arctic plant communities changed in richness and composition in different directions, with temperature and plant–plant interactions emerging as the main drivers of change. Our findings demonstrate how climate and biotic drivers can act in concert to alter plant composition, which could precede future biodiversity changes that are likely to affect ecosystem function, wildlife habitats and the livelihoods of Arctic peoples^5,6. 

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. 

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. 

ABSTRACT Forecasting plant responses under global change is a critical but challenging endeavour. Despite seemingly idiosyncratic responses of species to global change, greater generalisation of ‘winners’ and ‘losers’ may emerge from considering how species functional traits influence responses and how these responses scale to the community level. Here, we synthesised six long‐term global change experiments combined with locally measured functional traits. We quantified the change in abundance and probability of establishment through time for 70 alpine plant species and then assessed if leaf and stature traits were predictive of species and community responses across nitrogen addition, snow addition and warming treatments. Overall, we found that plants with more resource‐acquisitive trait strategies increased in abundance but each global change factor was related to different functional strategies. Nitrogen addition favoured species with lower leaf nitrogen, snow addition favoured species with cheaply constructed leaves and warming showed few consistent trends. Community‐weighted mean changes in trait values in response to nitrogen addition, snow addition and warming were often different from species‐specific trait effects on abundance and establishment, reflecting in part the responses and traits of dominant species. Together, these results highlight that the effects of traits can differ by scale and response of interest. 

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.