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As part of its long-term climate data core collection, the Niwot Ridge LTER has collected daily air temperature at the Saddle site since 1981. The Saddle station is located at 3525 m.a.s.l. and is an important point location to capture local, ambient meteorological conditions for many biological and environmental datasets collected nearby. The location of the Saddle station has also presented challenges to its operation. Freezing temperatures, snow deposition from strong winds following storms, and exposure to lightning are some elements that have disrupted instrument functionality, affected data quality, and made access for research staff difficult over time, especially in winter months. These interruptions have led to missing or faulty data at times and inconsistent data gap-filling. Additionally, a mixture of mechanical hygrothermograph chart and temperature sensors with electronic data loggers have been used since the inception of the Saddle station to measure and record air temperature. Thus, a close inspection of potential influence from instrument turnover and relevant notes from research staff is required for a quality, daily air temperature time series for Saddle. Here we present a quality-controlled, gap-filled, daily time series of maximum, average, minimum, and diurnal air temperatures that accounts for instrument turnover at the Saddle. Methods follow those used to gap-fill long-term daily air temperature at the Niwot Ridge LTER D1 and C1 stations so there is consistency among core collection daily air temperature datasets. Metadata for this data package centralizes the most complete station history for Saddle air temperature and includes notes to data users on aspects and limitations of the dataset to consider when using these data in scientific analyses. 

As part of its long-term climate data core collection, the Niwot Ridge LTER has collected daily precipitation at the Saddle site since 1981. The Saddle station is located at 3525 m.a.s.l. and is an important point location to capture local, ambient meteorological conditions for many biological and environmental datasets collected nearby. The location of the Saddle station has also presented challenges to its operation. Freezing temperatures, snow deposition from strong winds following storms, and exposure to lightning are some elements that have disrupted instrument functionality, affected data quality, and made access for research staff difficult over time, especially in winter months. Here we present a quality-controlled, gap-filled, daily precipitation time series corrected for blowing snow overcatch at the Saddle station. Methods follow those used to gap-fill long-term daily precipitation at the Niwot Ridge LTER D1 and C1 stations so there is consistency among core collection daily precipitation datasets. Metadata for this data package centralizes the most complete station history for Saddle precipitation and includes notes to data users on aspects and limitations of the dataset to consider when using these data in scientific analyses. Because of unresolved data quality concerns with winter precipitation the first several years of the record, gap-filled data for winter months (October–May) 1981-10-01 through 1987-05-30 are removed. 

Abstract While most studies of species coexistence focus on the mechanisms that maintain coexistence, it is equally important to understand the mechanisms that structure failed coexistence. For example, California annual grasslands are heavily invaded ecosystems, where non‐native annuals have largely dominated and replaced native communities. These systems are also highly variable, with a high degree of rainfall seasonality and interannual rainfall variability—a quality implicated in the coexistence of functionally distinct species. Yet, despite the apparent strength of this variation, coexistence between native and non‐native annuals in this system has faltered.To test how variation‐dependent coexistence mechanisms modulate failed coexistence, we implemented a competition experiment between two previously common native forbs and three now‐dominant non‐native annual grasses spanning a conservative‐acquisitive range of traits. We grew individuals from each species under varying densities of all other species as competitors, under either wetter or drier early season rainfall treatments. Using subsequent seed production, we parameterized competition models, assessed the potential for coexistence among species pairs and quantified the relative influence of variation‐dependent coexistence mechanisms.As expected, we found little potential for coexistence. Competition was dominated by the non‐native grassAvena fatua, while native forbs were unable to invade non‐native grasses. Mutual competitive exclusion was common across almost all species and often contingent on rainfall, suggesting rainfall‐mediated priority effects. Among variation‐dependent mechanisms, the temporal storage effect had a moderate stabilizing effect for four of five species when averaged across competitors, while relative nonlinearity in competition was largely destabilizing, except for the most conservative non‐native grass, which benefited from a competitive release under dry conditions.Synthesis: Our findings suggest that rainfall variability does little to mitigate the fitness differences that underlie widespread annual grass invasion in California, but that it influences coexistence dynamics among the now‐dominant non‐native grasses. 

Abstract A central goal at the interface of ecology and conservation is understanding how the relationship between biodiversity and ecosystem function (B–EF) will shift with changing climate. Despite recent theoretical advances, studies which examine temporal variation in the functional traits and mechanisms (mass ratio effects and niche complementarity effects) that underpin the B–EF relationship are lacking.Here, we use 13 years of data on plant species composition, plant traits, local‐scale abiotic variables, above‐ground net primary productivity (ANPP), and climate from the alpine tundra of Colorado (USA) to investigate temporal dynamics in the B–EF relationship. To assess how changing climatic conditions may alter the B–EF relationship, we built structural equation models (SEMs) for 11 traits across 13 years and evaluated the power of different trait SEMs to predict ANPP, as well as the relative contributions of mass ratio effects (community‐weighted mean trait values; CWM), niche complementarity effects (functional dispersion; FDis) and local abiotic variables. Additionally, we coupled linear mixed effects models with Multimodel inference methods to assess how inclusion of trait–climate interactions might improve our ability to predict ANPP through time.In every year, at least one SEM exhibited good fit, explaining between 19.6% and 57.2% of the variation in ANPP. However, the identity of the trait which best explained ANPP changed depending on winter precipitation, with leaf area, plant height and foliar nitrogen isotope content (δ¹⁵N) SEMs performing best in high, middle and low precipitation years, respectively. Regardless of trait identity, CWMs exerted a stronger influence on ANPP than FDis and total biotic effects were always greater than total abiotic effects. Multimodel inference reinforced the results of SEM analysis, with the inclusion of climate–trait interactions marginally improving our ability to predict ANPP through time.Synthesis. Our results suggest that temporal variation in climatic conditions influences which traits, mechanisms and abiotic variables were most responsible for driving the B–EF relationship. Importantly, our findings suggest that future research should consider temporal variability in the B–EF relationship, particularly how the predictive power of individual functional traits and abiotic variables may fluctuate as conditions shift due to climate change. 

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.