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Abstract Snow conditions are changing rapidly across our planet, which has important implications for wildlife managers. In Alaska, USA, the later arrival of snow is challenging wildlife managers' ability to conduct aerial fall (autumn) moose (Alces alces) surveys. Complete snow cover is required to reliably detect and count moose using visual observation from an aircraft. With inadequate snow to help generate high‐quality moose survey data, it is difficult for managers to determine if they are effectively meeting population goals and optimizing hunting opportunities. We quantified past relationships and projected future trends between snow conditions and moose survey success across 7 different moose management areas in Alaska using 32 years (1987–2019) of moose survey data and modeled snow data. We found that modeled mean snow depth was 15 cm (SD = 11) when moose surveys were initiated, and snow depths were greater in years when surveys were completed compared to years when surveys were canceled. Further, we found that mean snow depth toward the beginning of the survey season (1 November) was the best predictor of whether a survey was completed in any given year. Based on modeled conditions, the trend in mean snow depth on 1 November declined from 1980 to 2020 in 5 out of 7 survey areas. These findings, coupled with future projections, indicated that by 2055, the delayed onset of adequate snow accumulation in the fall will prevent the completion of moose surveys over roughly 60% of Alaska's managed moose areas at this time of the year. Our findings can be used by wildlife managers to guide decisions related to the future reliability of aerial fall moose surveys and help to identify timelines for development of alternate measurement and monitoring methods. 

Vegetation (species) abundances were measured from LTER heath tundra herbivore exclosures using the point frame method. This file contains the number of pin hits per species for each subplot. 

Ecosystem carbon dioxide (CO2) flux light response curves were measured from Arctic LTER heath tundra herbivore exclosures. Plot photographs were taken of each subplot using five consumer grade red, green and blue (RGB) wavelength camera. Structure from motion (SFM) photogrammetric method was then used to derive canopy structure. This file contains the CO2, normalized difference vegetation index (NDVI) data and photographs for each plot. 

We conducted a manipulative experiment to quantify the impact of small mammal herbivores on the plant community of the tundra at three sites near Toolik Lake, Alaska. At each site we set up grazing fences in July of 2018 to simulate different levels of small mammal herbivore (vole and lemming) activity. Each site had 3 treatment plots and a control plot: 1) Exclosure treatments (EX) were 8 meter (m) x 8m square mesh fences 2) control plots (CT) were 8m x 8m unfenced plots marked with pin flags at corners 3) press treatments (PR) were 20m x 20m square mesh fences stocked with 4 tundra voles (Microtus oeconomus) every summer except for 2024 and 4) pulse treatments (PU) where we stocked the fence with 4 voles in 2018 and then removed and excluded voles from 2019 onward. At each site in each plot we collected relative abundance of plant species and ground cover in 8 1 square meter (m2) plots once each year (except in 2020). 

We conducted a manipulative experiment to quantify the impact of small mammal herbivores on the belowground biogeochemistry of the tundra at three sites near Toolik Lake, Alaska. At each site we set up grazing fences in July of 2018 to simulate different levels of small mammal herbivore (vole and lemming) activity. Each site had 3 treatment plots and a control plot: 1)Exclosure treatments (EX) were 8 meter (m) x 8m square mesh fences 2) control plots (CT) were 8m x 8m unfenced plots marked with pin flags at corners 3) press treatments (PR) were 20m x 20m square mesh fences stocked with 4 tundra voles (Microtus oeconomus) every summer except for 2024 and 4) pulse treatments (PU) where we stocked the fence with 4 voles in 2018 and then removed and excluded voles from 2019 onward. At each site we collected temperature measurements using iButton data loggers from the soil surface, the soil organic layer, and the soil mineral layer every 4 hours from 2018 - 2024. iButton loggers were removed and replaced after soil thaw every summer. 

We conducted a manipulative experiment to quantify the impact of small mammal herbivores on the belowground biogeochemistry of the tundra at three sites near Toolik Lake, Alaska. At each site we set up grazing fences in July of 2018 to simulate different levels of small mammal herbivore (vole and lemming) activity. Each site had 3 treatment plots and a control plot: 1)Exclosure treatments (EX) were 8 meter (m) x 8m square mesh fences 2) control plots (CT) were 8m x 8m unfenced plots marked with pin flags at corners 3) press treatments (PR) were 20m x 20m square mesh fences stocked with 4 tundra voles (Microtus oeconomus) every summer and 4) pulse treatments (PU) where we stocked the fence with 4 voles in 2018 and then removed and excluded voles from 2019-2022. At each site we collected 10 thaw depth measurements along a transect from each treatment. 

Abstract Most tundra carbon flux modeling relies on leaf area index (LAI), generally estimated from measurements of canopy greenness using the normalized difference vegetation index (NDVI), to estimate the direction and magnitude of fluxes. However, due to the relative sparseness and low stature of tundra canopies, such models do not explicitly consider the influence of variation in tundra canopy structure on carbon flux estimates. Structure from motion (SFM), a photogrammetric method for deriving three-dimensional (3D) structure from digital imagery, is a non-destructive method for estimating both fine-scale canopy structure and LAI. To understand how variation in 3D canopy structure affects ecosystem carbon fluxes in Arctic tundra, we adapted an existing NDVI-based tundra carbon flux model to include variation in SFM-derived canopy structure and its interaction with incoming sunlight to cast shadows on canopies. Our study system consisted of replicate plots of dry heath tundra that had been subjected to three herbivore exclosure treatments (an exclosure-free control [CT], large mammals exclosure), and a large and small mammal exclosure [ExLS]), providing the range of 3D canopy structures employed in our study. We found that foliage within the more structurally complex surface of CT canopies received significantly less light over the course of the day than canopies within both exclosure treatments. This was especially during morning and evening hours, and was reflected in modeled rates of net ecosystem exchange (NEE) and gross primary productivity (GPP). We found that in the ExLS treatment, SFM-derived estimates of GPP were significantly lower and NEE significantly higher than those based on LAI alone. Our results demonstrate that the structure of even simple tundra vegetation canopies can have significant impacts on tundra carbon fluxes and thus need to be accounted for. 

We use a simple model of coupled carbon and nitrogen cycles in terrestrial ecosystems to examine how explicitly representing grazers versus having grazer effects implicitly aggregated in with other biogeochemical processes in the model alters predicted responses to elevated carbon dioxide and warming. The aggregated approach can affect model predictions because grazer-mediated processes can respond differently to changes in climate from the processes with which they are typically aggregated. We use small-mammal grazers in arctic tundra as an example and find that the typical three-to-four-year cycling frequency is too fast for the effects of cycle peaks and troughs to be fully manifested in the ecosystem biogeochemistry. We conclude that implicitly aggregating the effects of small-mammal grazers with other processes results in an underestimation of ecosystem response to climate change relative to estimations in which the grazer effects are explicitly represented. The magnitude of this underestimation increases with grazer density. We therefore recommend that grazing effects be incorporated explicitly when applying models of ecosystem response to global change. 

We use a simple model of coupled carbon and nitrogen cycles in terrestrial ecosystems to examine how explicitly representing grazers versus having grazer effects implicitly aggregated in with other biogeochemical processes in the model alters predicted responses to elevated carbon dioxide and warming. The aggregated approach can affect model predictions because grazer-mediated processes can respond differently to changes in climate from the processes with which they are typically aggregated. We use small-mammal grazers in arctic tundra as an example and find that the typical three-to-four-year cycling frequency is too fast for the effects of cycle peaks and troughs to be fully manifested in the ecosystem biogeochemistry. We conclude that implicitly aggregating the effects of small-mammal grazers with other processes results in an underestimation of ecosystem response to climate change relative to estimations in which the grazer effects are explicitly represented. The magnitude of this underestimation increases with grazer density. We therefore recommend that grazing effects be incorporated explicitly when applying models of ecosystem response to global change. 

Arctic Treeline is the transition from the boreal forest to the treeless tundra and may be determined by growing season temperatures. The physiological mechanisms involved in determining the relationship between the physical and biological environment and the location of treeline are not fully understood. In Northern Alaska, we studied the relationship between temperature and leaf respiration in 36 white spruce ( Picea glauca ) trees, sampling both the upper and lower canopy, to test two research hypotheses. The first hypothesis is that upper canopy leaves, which are more directly coupled to the atmosphere, will experience more challenging environmental conditions and thus have higher respiration rates to facilitate metabolic function. The second hypothesis is that saplings [stems that are 5–10cm DBH (diameter at breast height)] will have higher respiration rates than trees (stems ≥10cm DBH) since saplings represent the transition from seedlings growing in the more favorable aerodynamic boundary layer, to trees which are fully coupled to the atmosphere but of sufficient size to persist. Respiration did not change with canopy position, however respiration at 25°C was 42% higher in saplings compared to trees (3.43±0.19 vs. 2.41±0.14μmolm −2 s −1 ). Furthermore, there were significant differences in the temperature response of respiration, and seedlings reached their maximum respiration rates at 59°C, more than two degrees higher than trees. Our results demonstrate that the respiratory characteristics of white spruce saplings at treeline impose a significant carbon cost that may contribute to their lack of perseverance beyond treeline. In the absence of thermal acclimation, the rate of leaf respiration could increase by 57% by the end of the century, posing further challenges to the ecology of this massive ecotone.