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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.

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.

Plant diversity has a positive influence on the number of ecosystem functions maintained simultaneously by a community, or multifunctionality. While the presence of multiple trophic levels beyond plants, or trophic complexity, affects individual functions, the effect of trophic complexity on the diversity–multifunctionality relationship is less well known. To address this issue, we tested whether the independent or simultaneous manipulation of both plant diversity and trophic complexity impacted multifunctionality using a mesocosm experiment from Cedar Creek, Minnesota, USA. Our analyses revealed that neither plant diversity nor trophic complexity had significant effects on single functions, but trophic complexity altered the diversity–multifunctionality relationship in two key ways: It lowered the maximum strength of the diversity–multifunctionality effect, and it shifted the relationship between increasing diversity and multifunctionality from positive to negative at lower function thresholds. Our findings highlight the importance to account for interactions with higher trophic levels, as they can alter the biodiversity effect on multifunctionality.

Predicting the functional consequences of biodiversity loss in realistic, multitrophic communities remains a challenge. No existing biodiversity–ecosystem function study to date has simultaneously incorporated information on species traits, network topology, and extinction across multiple trophic levels, while all three factors are independently understood as critical drivers of post‐extinction network structure and function. We fill this gap by comparing the functional consequences of simulated species loss both within (monotrophic) and across (bitrophic) trophic levels, in an ecological interaction network estimated from spatially explicit field data on tropical fecal detritus producer and consumers (mammals and dung beetles). We simulated trait‐ordered beetle and mammal extinction separately (monotrophic extinction) and the coextinction of beetles following mammal loss (bitrophic extinction), according to network structure. We also compared the diversity effects of bitrophic extinction models using a standard monotrophic function (the daily production or consumption of fecal detritus) and a unique bitrophic functional metric (the proportion of daily detritus production that is consumed). We found similar mono‐ and bitrophic diversity effects, regardless of which species traits were used to drive extinctions, yet divergent predictions when different measures of function were used. The inclusion of information on network structure had little apparent effect on the qualitative relationship between diversity and function. These results contribute to our growing understanding of the functional consequences of biodiversity from real systems and underscore the importance of species traits and realistic functional metrics to assessments of the ecosystem impacts of network degradation through species loss.