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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. 

In arctic tundra, large and small mammalian herbivores have substantial impacts on the vegetation community and consequently can affect the magnitude of carbon cycling. However, herbivores are often absent from modern carbon cycle models, partly because relatively few field studies focus on herbivore impacts on carbon cycling. Our objectives were to quantify the impact of 21 years of large herbivore and large and small herbivore exclusion on carbon cycling during peak growing season in a dry heath tundra community. When herbivores were excluded, we observed a significantly greater leaf area index as well as greater vascular plant abundance. While we did not observe significant differences in deciduous dwarf shrub abundance across treatments, evergreen dwarf shrub abundance was greater where large and small herbivores were excluded. Both foliose and fruticose lichen abundance were higher in the large herbivore, but not the small and large herbivore exclosures. Net ecosystem exchange (NEE) likewise indicated the highest carbon uptake in the exclosure treatments and lowest uptake in the control (CT), suggesting that herbivory decreased the capacity of dry heath tundra to take up carbon. Moreover, our calculated NEE for average light and temperature conditions for July 2017, when our measurements were taken, indicated that the tundra was a carbon source in CT, but was a carbon sink in both exclosure treatments, indicating removal of grazing pressure can change the carbon balance of dry heath tundra. Collectively, these findings suggest that herbivore absence can lead to changes in plant community structure of dry heath tundra that in turn can increase its capacity to take up carbon.

 

Understanding arctic ecosystem function is key to understanding future global carbon (C) and nutrient cycling processes. However, small mammal herbivores can have effects on ecosystems as structure builders and these effects have been underrepresented in the understanding of arctic systems.

We examined the impact of small mammal structures (hay piles, runways, latrines) on soils and plants in three arctic tundra regions near Utqiaġvik, Toolik Lake, and Nome, Alaska. Our aims were to (1) examine how vole and lemming structures influence plant and soil nutrient pools and microbial processes, (2) determine if structure effects were similar across tundra system types, and (3) understand how changes in the abundance and cover of these structures during different phases of small mammal multi‐annual population cycles might influence biogeochemical cycling.

In general, small mammal structures increased nitrogen (N) availability in soils, although effects varied by study region. Across study regions, hay piles were relatively uncommon (lowest % cover) but increased multiple soil N and P pools, C‐ and N‐acquiring enzyme activities, and leaf phosphorus (P) concentrations, with the specific nutrient variables and size of the effects varying by study region. Latrines had the second highest cover and influenced multiple C, N and P pools, but their effects were mainly observed within a single region. Lastly, runways had the highest % cover of all activity types but increased the fewest number of soil nutrient variables.

We conclude that by influencing soil nutrient availability and biogeochemical cycling, small mammal structures can influence bottom‐up regulation of ecosystem function, particularly during the high phase of the small mammal population cycle. Future changes in these population cycles might alter the role of small mammals in the Arctic and have lasting effects on system processes.

Read the freePlain Language Summaryfor this article on the Journal blog

 

We use a simple model of coupled carbon and nitrogen cycles in terrestrial ecosystems to examine how “explicitly representing grazers” vs. “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 compared with the processes with which they are typically aggregated. We use small‐mammal grazers in a 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.

 

White spruce (Picea glauca) spans a massive range, yet the variability in respiratory physiology and related implications for tree carbon balance at the extremes of this distribution remain as enigmas. Working at both the most northern and southern extents of the distribution range more than 5000 km apart, we measured the short‐term temperature response of dark respiration (R/T) at upper and lower canopy positions.R/Tcurves were fit to both polynomial and thermodynamic models so that model parameters could be compared among locations, canopy positions, and with previously published data. Respiration measured at 25°C (R₂₅) was 68% lower at the southern location than at the northern location, resulting in a significantly lower intercept inR/Tresponse in temperate trees. Only at the southern location did upper canopy leaves have a steeper temperature response than lower canopy leaves, likely reflecting canopy gradients in light. At the northern range limit respiration is nearly twice that of the averageR₂₅reported in a global leaf respiration database. We predict that without significant thermal acclimation, respiration will increase with projected end‐of‐the‐century warming and will likely constrain the future range limits of this important boreal species.

 

For wildlife inhabiting snowy environments, snow properties such as onset date, depth, strength, and distribution can influence many aspects of ecology, including movement, community dynamics, energy expenditure, and forage accessibility. As a result, snow plays a considerable role in individual fitness and ultimately population dynamics, and its evaluation is, therefore, important for comprehensive understanding of ecosystem processes in regions experiencing snow. Such understanding, and particularly study of how wildlife–snow relationships may be changing, grows more urgent as winter processes become less predictable and often more extreme under global climate change. However, studying and monitoring wildlife–snow relationships continue to be challenging because characterizing snow, an inherently complex and constantly changing environmental feature, and identifying, accessing, and applying relevant snow information at appropriate spatial and temporal scales, often require a detailed understanding of physical snow science and technologies that typically lie outside the expertise of wildlife researchers and managers. We argue that thoroughly assessing the role of snow in wildlife ecology requires substantive collaboration between researchers with expertise in each of these two fields, leveraging the discipline‐specific knowledge brought by both wildlife and snow professionals. To facilitate this collaboration and encourage more effective exploration of wildlife–snow questions, we provide a five‐step protocol: (1) identify relevant snow property information; (2) specify spatial, temporal, and informational requirements; (3) build the necessary datasets; (4) implement quality control procedures; and (5) incorporate snow information into wildlife analyses. Additionally, we explore the types of snow information that can be used within this collaborative framework. We illustrate, in the context of two examples, field observations, remote‐sensing datasets, and four example modeling tools that simulate spatiotemporal snow property distributions and, in some cases, evolutions. For each type of snow data, we highlight the collaborative opportunities for wildlife and snow professionals when designing snow data collection efforts, processing snow remote sensing products, producing tailored snow datasets, and applying the resulting snow information in wildlife analyses. We seek to provide a clear path for wildlife professionals to address wildlife–snow questions and improve ecological inference by integrating the best available snow science through collaboration with snow professionals.

 

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.