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Light availability drives vertical canopy gradients in photosynthetic functioning and carbon (C) balance, yet patterns of variability in these gradients remain unclear. We measured light availability, photosynthetic CO2 and light response curves, foliar C, nitrogen (N) and pigment concentrations, and the photochemical reflectance index (PRI) on upper and lower canopy needles of white spruce trees (Picea glauca) at the species’ northern and southern range extremes. We combined our photosynthetic data with previously published respiratory data to compare and contrast canopy C balance between latitudinal extremes. We found steep canopy gradients in irradiance, photosynthesis, and leaf traits at the southern range limit, but a lack of variation across canopy positions at the northern range limit. Thus, unlike many tree species from tropical to mid-latitude forests, high latitude trees may not require vertical gradients of metabolic activity to optimize photosynthetic C gain. Consequently, accounting for self-shading is less critical for predicting gross primary productivity at northern relative to southern latitudes. Northern trees also had a significantly smaller net positive leaf C balance than southern trees suggesting that, regardless of canopy position, low photosynthetic rates coupled with high respiratory costs may ultimately constrain the northern range limit of this widely distributed boreal species.SUMMARY STATEMENTCanopy gradients in photosynthetic capacity of white spruce diminish at high compared to low latitudes. Low carbon balance in high latitude trees may determine the extent of northern treeline.

Observing the environment in the vast inaccessible regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest i...

The forest-tundra ecotone (FTE) is exhibiting myriad responses to rapid environmental change. Microstructural variability (at cm to m length scales) of vegetation canopies and geomorphic features may modulate the response of FTE vegetation to regional climate changes. Understanding the influence of microstructure on tree function at the FTE is particularly relevant during vulnerable early growth stages. During these stages, individual trees are tightly coupled to conditions of the surface boundary layer, which can be more conducive to growth than the conditions above the boundary layer. Until recently, however, it has been difficult to characterize microstructure in a replicable, transferable manner. This study builds upon substantial research on ecological responses of trees at the FTE to growth environment conditions by integrating high-resolution terrestrial lidar scanning (TLS) to characterize microstructure. Our main goal was to use TLS technology to understand the effects of microstructure on photosynthetic functioning (i.e., chlorophyll fluorescence) of small-stature white spruce (Picea glauca (Moench) Voss) trees at the FTE. Our specific objectives were to: 1) determine how much variance in photosynthetic functioning is explained by microstructure; 2) identify microstructural metrics that most strongly control variance in photosynthetic functioning; and 3) determine the scales at which microstructural metrics most strongly drive variance in photosynthetic functioning. Random Forest modeling demonstrated that 28% of variance in photosynthetic functioning can be explained through variation in fine-scale environmental conditions that are modulated by microstructure alone. Insolation and canopy roughness were the most important predictors of photosynthetic functioning, and the sensitivity of photosynthetic functioning to canopy roughness was scale-dependent. This suggests that microstructure affects spatial heterogeneity in the boundary layer that may influence carbon assimilation of small-stature spruce trees. This research emphasizes the importance of quantifying microstructure in study systems where fine-scale heterogeneity of the growth environment may modulate plant responses to regional climate change.

Relatively little is known of how the world's largest vegetation transition zone – the Forest Tundra Ecotone (FTE) – is responding to climate change. Newly available, satellite-derived time-series of the photochemical reflectance index (PRI) across North America and Europe could provide new insights into the physiological response of evergreen trees to climate change by tracking changes in foliar pigment pools that have been linked to photosynthetic phenology. However, before implementing these data for such purpose at these evergreen dominated systems, it is important to increase our understanding of the fine scale mechanisms driving the connection between PRI and environmental conditions. The goal of this study is thus to gain a more mechanistic understanding of which environmental factors drive changes in PRI during late-season phenological transitions at the FTE – including factors that are susceptible to climate change (i.e., air- and soil-temperatures), and those that are not (photoperiod). We hypothesized that late-season phenological changes in foliar pigment pools captured by PRI are largely driven by photoperiod as opposed to less predictable drivers such as air temperature, complicating the utility of PRI time-series for understanding climate change effects on the FTE. Ground-based, time-series of PRI were acquired from individual trees in combination with meteorological variables and photoperiod information at six FTE sites in Alaska. A linear mixed-effects modeling approach was used to determine the significance (α = 0.001) and effect size (i.e., standardized slope b*) of environmental factors on late-seasonal changes in the PRI signal. Our results indicate that photoperiod had the strongest, significant effect on late-season changes in PRI (b* = 0.08, p

Solar-Induced chlorophyll Fluorescence (SIF) provides a powerful proxy for determining forest gross primary production (GPP), particularly in evergreen ecosystems where traditional measures of gree...

Recent advancements in understanding remotely sensed solar‐induced chlorophyll fluorescence often suggest a linear relationship with gross primary productivity at large spatial scales. However, the quantum yields of fluorescence and photochemistry are not linearly related, and this relationship is largely driven by irradiance. This raises questions about the mechanistic basis of observed linearity from complex canopies that experience heterogeneous irradiance regimes at subcanopy scales. We present empirical data from two evergreen forest sites that demonstrate a nonlinear relationship between needle‐scale observations of steady‐state fluorescence yield and photochemical yield under ambient irradiance. We show that accounting for subcanopy and diurnal patterns of irradiance can help identify the physiological constraints on needle‐scale fluorescence at 70–80% accuracy. Our findings are placed in the context of how solar‐induced chlorophyll fluorescence observations from spaceborne sensors relate to diurnal variation in canopy‐scale physiology.

The Arctic-Boreal Zone (ABZ) is characterized by spatially heterogeneous vegetation composition and structure, leading to challenges for inferring patterns in vegetation productivity. A mechanistic understanding of the patterns and processes underlying spectral remote sensing observations is necessary to overcome these challenges. Solar-induced chlorophyll fluorescence (SIF), near-infrared reflectance of vegetation (NIRv), and chlorophyll/carotenoid index (CCI) show promise for tracking productivity and disentangling links to the activity and distribution of chlorophyll at coarse spatial scales (e.g. 0.5°), but their effectiveness for studying mixed landscapes characteristic of the ABZ remains unclear. Here, we use airborne observations collected during NASA’s Arctic-Boreal Vulnerability Experiment to examine the spatial covariation between SIF, NIRv, and CCI at a scale (30 m) commensurate with the best available landcover products across interior Alaska. Additionally, we compare relationships among SIF and vegetation indices from spaceborne observations (TROPOMI and MODIS) resampled to a 0.01° (∼1000 m) scale. We find that the strength of the SIF-NIRv linear relationship degrades when compared from the spaceborne to the airborne scale (R 2 = 0.50 vs. 0.26) as does the strength of the SIF-CCI linear relationship (R 2 = 0.30 vs. 0.18), though the degradation of SIF-CCI is less severe than that of SIF-NIRv. The relationship of SIF with either vegetation index is strongly dependent on landcover class at both airborne and spaceborne scales. We provide context for how further work could leverage SIF with reflectance indices measurable from a variety of platforms to improve mapping of vegetation dynamics in this ecoregion.

Northern herbivore ranges are expanding in response to a warming climate. Forage quality also influences herbivore distributions, but less is known about the effects of climate change on plant biochemical properties. Remote sensing could enable landscape-scale estimations of forage quality, which is of interest to wildlife managers. Despite the importance of integrated forage quality metrics like digestible protein (DP) and digestible dry matter (DDM), few studies investigate remote sensing approaches to estimate these characteristics. We evaluated how well DP and DDM could be estimated using hyperspectral remote sensing and assessed whether incorporating shrub structural metrics affected by browsing would improve our ability to predict DP and DDM. We collected canopy-level spectra, destructive-vegetation samples, and flew unoccupied aerial vehicles (UAVs) in willow (Salix spp.) dominated areas in north central Alaska in July 2019. We derived vegetation canopy structural metrics from 3D point cloud data obtained from UAV imagery using structure-from-motion photogrammetry. The best performing model for DP included a spectral vegetation index (SVI) that used a red-edge and shortwave infrared band, and shrub height variability (hvar; Nagelkerke R 2 = 0.81, root mean square error RMSE = 1.42%, cross validation ρ = 0.88). DDM’s best model included a SVI with a blue and a red band, the normalized difference red-edge index, and hvar (adjusted R 2 = 0.73, RMSE = 4.16%, cross validation ρ = 0.80). Results from our study demonstrate that integrated forage quality metrics may be successfully quantified using hyperspectral remote sensing data, and that models based on those data may be improved by incorporating additional shrub structural metrics such as height variability. Modern airborne sensor platforms such as Goddard’s LiDAR, Hyperspectral & Thermal Imager provide opportunities to fuse data streams from both structural and optical data, which may enhance our ability to estimate and scale important foliar properties.

A species' use of space provides insight into fundamental resource requirements and population dynamics. Here we investigate how microhabitat features and intraspecific interaction contribute to space use by the singing vole (Microtus miurus) on arctic tundra. We used mark-recapture of singing voles to estimate home range using a kernel density estimator. To assess intraspecific interactions, regions within home ranges were classified as “exclusive” or “shared” based on overlap among individuals. The spatial distribution of singing vole encounters was analyzed in conjunction with multivariate hierarchical cluster analysis of vegetation cover to assess microhabitat affinity. “Shared” regions within home ranges were used more than expected based on proportional availability. We observed significant affinities for microhabitats at both the scale of individual home ranges and of the singing vole population. Our results suggest that heterogeneity in microhabitat features and social interactions are im...

Relationships between gross primary productivity (GPP) and the remotely sensed photochemical reflectance index (PRI) suggest that time series of foliar PRI may provide insight into climate change effects on carbon cycling. However, because a large fraction of carbon assimilated via GPP is quickly returned to the atmosphere via respiration, we ask a critical question-can PRI time series provide information about longer term gains in aboveground carbon stocks? Here we study the suitability of PRI time series to understand intra-annual stem-growth dynamics at one of the world's largest terrestrial carbon pools-the boreal forest. We hypothesized that PRI time series can be used to determine the onset (hypothesis 1) and cessation (hypothesis 2) of radial growth and enable tracking of intra-annual tree growth dynamics (hypothesis 3). Tree-level measurements were collected in 2018 and 2019 to link highly temporally resolved PRI observations unambiguously with information on daily radial tree growth collected via point dendrometers. We show that the seasonal onset of photosynthetic activity as determined by PRI time series was significantly earlier (p .05) than the onset of radial tree growth determined from the point dendrometer time series which does not support our first hypothesis. In contrast, seasonal decline of photosynthetic activity and cessation of radial tree growth was not significantly different (p .05) when derived from PRI and dendrometer time series, respectively, supporting our second hypothesis. Mixed-effects modeling results supported our third hypothesis by showing that the PRI was a statistically significant (p .0001) predictor of intra-annual radial tree growth dynamics, and tracked these daily radial tree-growth dynamics in remarkable detail with conditional and marginal coefficients of determination of 0.48 and 0.96 (for 2018) and 0.43 and 0.98 (for 2019), respectively. Our findings suggest that PRI could provide novel insights into nuances of carbon cycling dynamics by alleviating important uncertainties associated with intra-annual vegetation response to climate change.

Forests reduce snow accumulation on the ground through canopy interception and subsequent evaporative losses. To understand snow interception and associated hydrological processes, studies have typically relied on resource-intensive point scale measurements derived from weighed trees or indirect measurements that compared snow accumulation between forested sites and nearby clearings. Weighed trees are limited to small or medium-sized trees, and indirect comparisons can be confounded by wind redistribution of snow, branch unloading, and clearing size. A potential alternative method could use terrestrial lidar (light detection and ranging) because three-dimensional lidar point clouds can be generated for any size tree and can be utilized to calculate volume of the intercepted snow. The primary objective of this study was to provide a feasibility assessment for estimating snow interception volume with terrestrial laser scanning (TLS), providing information on challenges and opportunities for future research. During the winters of 2017 and 2018, intercepted snow masses were continuously measured for two model trees suspended from load-cells. Simultaneously, autonomous terrestrial lidar scanning (ATLS) was used to develop volumetric estimates of intercepted snow. Multiplying ATLS volume estimates by snow density estimates (derived from empirical models based on air temperature) enabled the comparison of predicted vs. measured snow mass. Results indicate agreement between predicted and measured values (R2 ≥ 0.69, RMSE ≥ 0.91 kg, slope ≥ 0.97, intercept ≥ −1.39) when multiplying TLS snow interception volume with a constant snow density estimate. These results suggest that TLS might be a viable alternative to traditional approaches for mapping snow interception, potentially useful for estimating snow loads on large trees, collecting data in difficult to access terrain, and calibrating snow interception models to new forest types around the globe.

Changing trends in the indications for paediatric tracheostomies, with decreasing numbers of tracheostomies being performed, have been reported in the literature. In a retrospective analysis of the period 1971 to 1990 the experience of tracheostomies in children under the age of 15 at Our Lady's Hospital (Dublin) is reviewed. Only 29 tracheostomies were performed during this time with an increase in numbers (90%) performed during the second 10 year period. The major underlying indication for tracheostomy in both 10 year periods was for the management of an airway problem secondary to congenital abnormalities (65%). In 14 children the operation was performed during the first year of life. However, while 90% of the children were under the age of one in the period 1971-1980 this fell to 26% during 1981-1990. Complications occurred in 41% overall, however, in the under 1 year old group 64% developed complications. There were no deaths as a direct result of the tracheostomy or its complications, but six children died because of the severity of the underlying disease. The average length of time before decannulation was 2.1 years, with decannulation difficulties occurring infrequently (11%).