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The Turf Transplant Experiment was set up in the summer of 2024. Paired experimental sites were established in two tundra community types - dry meadow and moist meadow - with one site of each community type pair in a lower elevation/warmer area and one site in a higher elevation/cooler area. Subplot turfs (25 cm^2) were transplanted (1) between sites of the same community type at different elevations/temperatures, (2) between plots within the same site or (3) left in place as non-transplant controls. This data package contains trait measurements on Bistort individuals. 

Anthropogenic climate change is altering interactions among numerous species, including plants and pollinators. Plant-pollinator interactions, crucial for the persistence of most plant and many insect species, are threatened by climate change-driven phenological shifts. Phenological mismatches between plants and their pollinators may affect pollination services, and simulations indicated that these mismatches may reduce floral resources available to up to 50% of insect pollinator species. Although alpine plants rely heavily on vegetative reproduction, seedling recruitment and seed dispersal are likely to be important drivers of alpine community structure. Similarly, advanced flowering may expose plants to increased risk of frost damage and shifted soil moisture regimes; phenologically advanced plants will experience these environmental factors differently, which may alter their floral resource production. These effects may be dependent upon topography. Some species of alpine plants on the Niwot Ridge have displayed advanced phenology under treatments of advanced snowmelt (Forrester, 2021). However, little is understood about how these differences in distribution and phenology affect pollinator community composition and plant fecundity. Here we strive to examine how experimentally-induced changes in the timing of flowering and number of flowers produced by plants impact plant-pollinator interactions and seed set. We also ask how topography and the number of flowers interact with early snowmelt to affect pollination rates and the diversity of pollinating insects. Finally, we ask how seed set of Geum rossii is affected by pollinator visitation at different times of the season, under experimentally advanced snowmelt versus unmanipulated snowmelt, and with visitation by different insect taxa. In summer 2020, we found that plots with advanced phenology experienced peaks in pollinator visitation rates and pollinator diversity earlier than plots with unmanipulated snowmelt. We expect this to be because of the advanced floral phenology of certain key species in these plots. References: Forrester, C.C. (2021). Advancing, Using, and Teaching Climate Change Ecology Research. [Doctoral dissertation, University of Colorado, Boulder]. ProQuest Dissertations and Theses. 

ABSTRACT Microbial environmental transmission among individuals plays an important role in shaping the microbiomes of many species. Despite the importance of the microbiome for host fitness, empirical investigations on environmental transmission are scarce, particularly in systems where interactions across multiple trophic levels influence symbiotic dynamics. Here, we explore microbial transmission within insect microbiomes, focusing on solitary bees. Specifically, we investigate the environmental transmission hypothesis, which posits that solitary bees acquire and deposit their associated microbiota from and to their surroundings, especially flowers. Using experimental setups, we examine the transmission dynamics ofApilactobacillus micheneri, a fructophilic and acidophilic bacterium, between the solitary beeOsmia lignaria(Megachilidae) and the plantPhacelia tanacetifolia(Boraginaceae). Our results demonstrate that bees not only acquire bacteria from flowers but also deposit these microbes onto uninoculated flowers for other bees to acquire them, supporting a bidirectional microbial exchange. We therefore find empirical support for the environmental transmission hypothesis, and we discuss the multitrophic dependencies that facilitate microbial transmission between bees and flowers. 

Theoretical frameworks of terrestrial community assembly often focus on single trophic levels (e.g. plants) without considering how complex interdependencies across different trophic levels influence assembly mechanisms. Yet, when multiple trophic levels are considered (e.g. plant–pollinator, plant–microbe interactions) the focus is typically on network analyses at local spatial scales. As spatial variation in biodiversity (β‐diversity) is increasingly being recognized for its relevance in understanding community assembly and conservation, considering how β‐diversity at one trophic level may be influenced by assembly processes that alter abundance and composition of interacting communities at a different trophic level (multitrophic dependency) is critical. Here, we build on single trophic level community assembly frameworks to explore the assembly processes affecting β‐diversity in multitrophic communities comprising flowering plants, their bee pollinators, and the corresponding bee‐gut microbiota to better understand the importance of multitrophic dependency in community assembly. Using distance‐based redundancy analysis and variation partitioning, we investigated community assembly processes across three interconnected trophic levels in two ecological regions in southern California: the Santa Monica Mountains and three islands of the Channel Island Archipelago. We found that the deterministic effects of multitrophic dependency are stronger on directly connected trophic levels than on indirectly connected trophic levels (i.e. flowers explain bee communities and bees explain bee‐gut bacteria communities, but flowers weakly explain variation in bee‐gut bacteria communities). We also found notable regional variation, where multitrophic dependency was weaker on the Channel Islands as ecological drift was more pronounced. Our results suggest that integrating the influence of multitrophic dependency on community assembly is important for elucidating drivers of β‐diversity and that multitrophic dependency can be determined by the regional context in which β‐diversity is measured. Taken together, our results highlight the importance of considering multiscale perspectives – both multitrophic and multiregional – in community assembly to fully elucidate assembly processes. 

As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows in a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot of each block by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to these plots after snow had naturally melted. This dataset includes geolocations of individual subplots and sensors within the experiment, measured in summer 2023. 

ABSTRACT Climate change is altering precipitation regimes that control nitrogen (N) cycling in terrestrial ecosystems. In ecosystems exposed to frequent drought, N can accumulate in soils as they dry, stimulating the emission of both nitric oxide (NO; an air pollutant at high concentrations) and nitrous oxide (N₂O; a powerful greenhouse gas) when the dry soils wet up. Because changes in both N availability and soil moisture can alter the capacity of nitrifying organisms such as ammonia‐oxidizing bacteria (AOB) and archaea (AOA) to process N and emit N gases, predicting whether shifts in precipitation may alter NO and N₂O emissions requires understanding how both AOA and AOB may respond. Thus, we ask: How does altering summer and winter precipitation affect nitrifier‐derived N trace gas emissions in a dryland ecosystem? To answer this question, we manipulated summer and winter precipitation and measured AOA‐ and AOB‐derived N trace gas emissions, AOA and AOB abundance, and soil N concentrations. We found that excluding summer precipitation increased AOB‐derived NO emissions, consistent with the increase in soil N availability, and that increasing summer precipitation amount promoted AOB activity. Excluding precipitation in the winter (the most extreme water limitation we imposed) did not alter nitrifier‐derived NO emissions despite N accumulating in soils. Instead, nitrate that accumulated under drought correlated with high N₂O emission via denitrification upon wetting dry soils. Increases in the timing and intensity of precipitation that are forecasted under climate change may, therefore, influence the emission of N gases according to the magnitude and season during which the changes occur. 

Abstract Studies of community assembly often explore the role of niche selection in limiting the diversity of functional traits (underdispersion) or increasing the diversity of functional traits (overdispersion) within local communities. While these patterns have primarily been explored with morphological functional traits related to environmental tolerances and resource acquisition, plant metabolomics may provide an additional functional dimension of community assembly to expand our understanding of how niche selection changes along environmental gradients. Here, we examine how the functional diversity of leaf secondary metabolites and traditional morphological plant traits changes along local environmental gradients in three temperate forest ecosystems across North America. Specifically, we asked whether co‐occurring tree species exhibit local‐scale over‐ or underdispersion of metabolomic and morphological traits, and whether differences in trait dispersion among local communities are associated with environmental gradients of soil resources and topography. Across tree species, we find that most metabolomic traits are not correlated with morphological traits, adding a unique dimension to functional trait space. Within forest plots, metabolomic traits tended to be overdispersed while morphological traits tended to be underdispersed. Additionally, local environmental gradients had site‐specific effects on metabolomic and morphological trait dispersion patterns. Taken together, these results show that different suites of traits can result in contrasting patterns of functional diversity along environmental gradients and suggest that multiple community assembly mechanisms operate simultaneously to structure functional diversity in temperate forest ecosystems. 

Abstract Climate change is altering interactions among plants and pollinators. In alpine ecosystems, where snowmelt timing is a key driver of phenology, earlier snowmelt may generate shifts in plant and pollinator phenology that vary across the landscape, potentially disrupting interactions. Here we ask how experimental advancement of snowmelt timing in a topographically heterogeneous alpine-subalpine landscape impacts flowering, insect pollinator visitation, and pathways connecting key predictors of plant-pollinator interaction. Snowmelt was advanced by an average of 13.5 days in three sites via the application of black sand over snow in manipulated plots, which were paired with control plots. For each forb species, we documented flowering onset and counted flowers throughout the season. We also performed pollinator observations to measure visitation rates. The majority (79.3%) of flower visits were made by dipteran insects. We found that plants flowered earlier in advanced snowmelt plots, with the largest advances in later-flowering species, but flowering duration and visitation rate did not differ between advanced snowmelt and control plots. Using piecewise structural equation models, we assessed the interactive effects of topography on snowmelt timing, flowering phenology, floral abundance, and pollinator visitation. We found that these factors interacted to predict visitation rate in control plots. However, in plots with experimentally advanced snowmelt, none of these predictors explained a significant amount of variation in visitation rate, indicating that different predictors are needed to understand the processes that directly influence pollinator visitation to flowers under future climate conditions. Our findings demonstrate that climate change-induced early snowmelt may fundamentally disrupt the predictive relationships among abiotic and biotic drivers of plant-pollinator interactions in subalpine-alpine environments. 

Summary Predicting shifts in species composition with global change remains challenging, but plant functional traits provide a key link to scale from plant to community and ecosystem levels. The extent to which functional trait shifts may mediate ecosystem response to climate change remains a critical question.We ran point‐scale Community Land Model (CLM) simulations with site‐specific functional trait and phenology observations to represent alpine tundra growth strategies. We validated our results with site observations and compared parameterized results to those using the default parameterization. We then quantified the relative contribution of plant functional trait shifts vs climate change scenarios (and the resulting phenological shifts) to uncertainty in future tundra ecosystem productivity outcomes.We found that using community‐specific functional traits and phenology observations significantly improved productivity estimates compared with overestimates in a default simulation. Uncertainty in potential plant trait shifts often had a larger effect on ecosystem productivity responses than uncertainty in the forced response from different climate change scenarios.These findings highlight the key role of functional traits in shaping vegetation responses to climate change and the value of incorporating site‐level measurements into land models to more accurately forecast climate change impacts on ecosystem function.