Vertical gradients in photosynthetic physiology diverge at the latitudinal range extremes of white spruce.

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.

Variation in White spruce needle respiration at the species range limits: A potential impediment to Northern expansion.

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/T curves 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 in R/T response 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 average R25 reported 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.

Remote sensing tracks daily radial wood growth of evergreen needleleaf trees.

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.

A mechanism of expansion: Arctic deciduous shrubs capitalize on warming-induced nutrient availability.

Warming-induced nutrient enrichment in the Arctic may lead to shifts in leaf-level physiological properties and processes with potential consequences for plant community dynamics and ecosystem function. To explore the physiological responses of Arctic tundra vegetation to increasing nutrient availability, we examined how a set of leaf nutrient and physiological characteristics of eight plant species (representing four plant functional groups) respond to a gradient of experimental nitrogen (N) and phosphorus (P) enrichment. Specifically, we examined a set of chlorophyll fluorescence measures related to photosynthetic efficiency, performance and stress, and two leaf nutrient traits (leaf %C and %N), across an experimental nutrient gradient at the Arctic Long Term Ecological Research site, located in the northern foothills of the Brooks Range, Alaska. In addition, we explicitly assessed the direct relationships between chlorophyll fluorescence and leaf %N. We found significant differences in physiological and nutrient traits between species and plant functional groups, and we found that species within one functional group (deciduous shrubs) have significantly greater leaf %N at high levels of nutrient addition. In addition, we found positive, saturating relationships between leaf %N and chlorophyll fluorescence measures across all species. Our results highlight species-specific differences in leaf nutrient traits and physiology in this ecosystem. In particular, the effects of a gradient of nutrient enrichment were most prominent in deciduous plant species, the plant functional group known to be increasing in relative abundance with warming in this ecosystem.

Navigating snowscapes: scale-dependent responses of mountain sheep to snowpack properties.

Winters are limiting for many terrestrial animals due to energy deficits brought on by resource scarcity and the increased metabolic costs of thermoregulation and traveling through snow. A better understanding of how animals respond to snow conditions is needed to predict the impacts of climate change on wildlife. We compared the performance of remotely sensed and modeled snow products as predictors of winter movements at multiple spatial and temporal scales using a data set of 20,544 locations from 30 GPS-collared Dall sheep (Ovis dalli dalli) in Lake Clark National Park and Preserve, Alaska, USA from 2005 to 2008. We used daily 500-m MODIS normalized difference snow index (NDSI), and multi-resolution snow depth and density outputs from a snowpack evolution model (SnowModel), as covariates in step selection functions. We predicted that modeled snow depth would perform best across all scales of selection due to more informative spatiotemporal variation and relevance to animal movement. Our results indicated that adding any of the evaluated snow metrics substantially improved model performance and helped characterize winter Dall sheep movements. As expected, SnowModel-simulated snow depth outperformed NDSI at fine-to-moderate scales of selection (step scales < 112 h). At the finest scale, Dall sheep selected for snow depths below mean chest height (<54 cm) when in low-density snows (100 kg/m3 ), which may have facilitated access to ground forage and reduced energy expenditure while traveling. However, sheep selected for higher snow densities (>300 kg/m3 ) at snow depths above chest height, which likely further reduced energy expenditure by limiting hoof penetration in deeper snows. At moderate-to-coarse scales (112-896 h step scales), however, NDSI was the best-performing snow covariate. Thus, the use of publicly available, remotely sensed, snow cover products can substantially improve models of animal movement, particularly in cases where movement distances exceed the MODIS 500-m grid threshold. However, remote sensing products may require substantial data thinning due to cloud cover, potentially limiting its power in cases where complex models are necessary. Snowpack evolution models such as SnowModel offer users increased flexibility at the expense of added complexity, but can provide critical insights into fine-scale responses to rapidly changing snow properties.

Spectral determination of concentrations of functionally diverse pigments in increasingly complex arctic tundra canopies.

As the Arctic warms, tundra vegetation is becoming taller and more structurally complex, as tall deciduous shrubs become increasingly dominant. Emerging studies reveal that shrubs exhibit photosynthetic resource partitioning, akin to forests, that may need accounting for in the "big leaf" net ecosystem exchange models. We conducted a lab experiment on sun and shade leaves from S. pulchra shrubs to determine the influence of both constitutive (slowly changing bulk carotenoid and chlorophyll pools) and facultative (rapidly changing xanthophyll cycle) pigment pools on a suite of spectral vegetation indices, to devise a rapid means of estimating within canopy resource partitioning. We found that: (1) the PRI of dark-adapted shade leaves (PRIo) was double that of sun leaves, and that PRIo was sensitive to variation among sun and shade leaves in both xanthophyll cycle pool size (V + A + Z) (r (2) = 0.59) and Chla/b (r (2) = 0.64); (2) A corrected PRI (difference between dark and illuminated leaves, ΔPRI) was more sensitive to variation among sun and shade leaves in changes to the epoxidation state of their xanthophyll cycle pigments (dEPS) (r (2) = 0.78, RMSE = 0.007) compared to the uncorrected PRI of illuminated leaves (PRI) (r (2) = 0.34, RMSE = 0.02); and (3) the SR680 index was correlated with each of (V + A + Z), lutein, bulk carotenoids, (V + A + Z)/(Chla + b), and Chla/b (r (2) range = 0.52-0.69). We suggest that ΔPRI be employed as a proxy for facultative pigment dynamics, and the SR680 for the estimation of constitutive pigment pools. We contribute the first Arctic-specific information on disentangling PRI-pigment relationships, and offer insight into how spectral indices can assess resource partitioning within shrub tundra canopies.

Accuracy of WAAS-Enabled GPS-RF Warning Signals When Crossing a Terrestrial Geofence.

Geofences are virtual boundaries based on geographic coordinates. When combined with global position system (GPS), or more generally global navigation satellite system (GNSS) transmitters, geofences provide a powerful tool for monitoring the location and movements of objects of interest through proximity alarms. However, the accuracy of geofence alarms in GNSS-radio frequency (GNSS-RF) transmitter receiver systems has not been tested. To achieve these goals, a cart with a GNSS-RF locator was run on a straight path in a balanced factorial experiment with three levels of cart speed, three angles of geofence intersection, three receiver distances from the track, and three replicates. Locator speed, receiver distance and geofence intersection angle all affected geofence alarm accuracy in an analysis of variance (p = 0.013, p = 2.58 × 10(-8), and p = 0.0006, respectively), as did all treatment interactions (p < 0.0001). Slower locator speed, acute geofence intersection angle, and closest receiver distance were associated with reduced accuracy of geofence alerts.

Assessing leaf photoprotective mechanisms using terrestrial LiDAR: towards mapping canopy photosynthetic performance in three dimensions.

Terrestrial laser scanning (TLS) data allow spatially explicit (x, y, z) laser return intensities to be recorded throughout a plant canopy, which could considerably improve our understanding of how physiological processes vary in three-dimensional space. However, the utility of TLS data for the quantification of plant physiological properties remains largely unexplored. Here, we test whether the laser return intensity of green (532-nm) TLS correlates with changes in the de-epoxidation state of the xanthophyll cycle and photoprotective non-photochemical quenching (NPQ), and compare the ability of TLS to quantify these parameters with the passively measured photochemical reflectance index (PRI). We exposed leaves from five plant species to increasing light intensities to induce NPQ and de-epoxidation of violaxanthin (V) to antheraxanthin (A) and zeaxanthin (Z). At each light intensity, the green laser return intensity (GLRI), narrowband spectral reflectance, chlorophyll fluorescence emission and xanthophyll cycle pigment composition were recorded. Strong relationships between both predictor variables (GLRI, PRI) and both explanatory variables (NPQ, xanthophyll cycle de-epoxidation) were observed. GLRI holds promise to provide detailed (mm) information about plant physiological status to improve our understanding of the patterns and mechanisms driving foliar photoprotection. We discuss the potential for scaling these laboratory data to three-dimensional canopy space.

Networking the forest infrastructure towards near real-time monitoring - A white paper.

Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction.

High Leaf Respiration Rates May Limit the Success of White Spruce Saplings Growing in the Kampfzone at the Arctic Treeline.

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.

Active ground optical remote sensing for improved monitoring of seedling stress in nurseries.

Active ground optical remote sensing (AGORS) devices mounted on overhead irrigation booms could help to improve seedling quality by autonomously monitoring seedling stress. In contrast to traditionally used passive optical sensors, AGORS devices operate independently of ambient light conditions and do not require spectral reference readings. Besides measuring red (590-670 nm) and near-infrared (>760 nm) reflectance AGORS devices have recently become available that also measure red-edge (730 nm) reflectance. We tested the hypothesis that the additional availability of red-edge reflectance information would improve AGORS of plant stress induced chlorophyll breakdown in Scots pine (Pinus sylvestris). Our results showed that the availability of red-edge reflectance information improved AGORS estimates of stress induced variation in chlorophyll concentration (r2>0.73, RMSE<1.69) when compared to those without (r2=0.57, RMSE=2.11).

Behavioral modifications by a large-northern herbivore to mitigate warming conditions.

BACKGROUND: Temperatures in arctic-boreal regions are increasing rapidly and pose significant challenges to moose (Alces alces), a heat-sensitive large-bodied mammal. Moose act as ecosystem engineers, by regulating forest carbon and structure, below ground nitrogen cycling processes, and predator-prey dynamics. Previous studies showed that during hotter periods, moose displayed stronger selection for wetland habitats, taller and denser forest canopies, and minimized exposure to solar radiation. However, previous studies regarding moose behavioral thermoregulation occurred in Europe or southern moose range in North America. Understanding whether ambient temperature elicits a behavioral response in high-northern latitude moose populations in North America may be increasingly important as these arctic-boreal systems have been warming at a rate two to three times the global mean. METHODS: We assessed how Alaska moose habitat selection changed as a function of ambient temperature using a step-selection function approach to identify habitat features important for behavioral thermoregulation in summer (June-August). We used Global Positioning System telemetry locations from four populations of Alaska moose (n = 169) from 2008 to 2016. We assessed model fit using the quasi-likelihood under independence criterion and conduction a leave-one-out cross validation. RESULTS: Both male and female moose in all populations increasingly, and nonlinearly, selected for denser canopy cover as ambient temperature increased during summer, where initial increases in the conditional probability of selection were initially sharper then leveled out as canopy density increased above ~ 50%. However, the magnitude of selection response varied by population and sex. In two of the three populations containing both sexes, females demonstrated a stronger selection response for denser canopy at higher temperatures than males. We also observed a stronger selection response in the most southerly and northerly populations compared to populations in the west and central Alaska. CONCLUSIONS: The impacts of climate change in arctic-boreal regions increase landscape heterogeneity through processes such as increased wildfire intensity and annual area burned, which may significantly alter the thermal environment available to an animal. Understanding habitat selection related to behavioral thermoregulation is a first step toward identifying areas capable of providing thermal relief for moose and other species impacted by climate change in arctic-boreal regions.

Ecological insights from three decades of animal movement tracking across a changing Arctic.

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.

A gradient of nutrient enrichment reveals nonlinear impacts of fertilization on Arctic plant diversity and ecosystem function.

Rapid environmental change at high latitudes is predicted to greatly alter the diversity, structure, and function of plant communities, resulting in changes in the pools and fluxes of nutrients. In Arctic tundra, increased nitrogen (N) and phosphorus (P) availability accompanying warming is known to impact plant diversity and ecosystem function; however, to date, most studies examining Arctic nutrient enrichment focus on the impact of relatively large (>25x estimated naturally occurring N enrichment) doses of nutrients on plant community composition and net primary productivity. To understand the impacts of Arctic nutrient enrichment, we examined plant community composition and the capacity for ecosystem function (net ecosystem exchange, ecosystem respiration, and gross primary production) across a gradient of experimental N and P addition expected to more closely approximate warming-induced fertilization. In addition, we compared our measured ecosystem CO 2 flux data to a widely used Arctic ecosystem exchange model to investigate the ability to predict the capacity for CO 2 exchange with nutrient addition. We observed declines in abundance-weighted plant diversity at low levels of nutrient enrichment, but species richness and the capacity for ecosystem carbon uptake did not change until the highest level of fertilization. When we compared our measured data to the model, we found that the model explained roughly 30%-50% of the variance in the observed data, depending on the flux variable, and the relationship weakened at high levels of enrichment. Our results suggest that while a relatively small amount of nutrient enrichment impacts plant diversity, only relatively large levels of fertilization-over an order of magnitude or more than warming-induced rates-significantly alter the capacity for tundra CO 2 exchange. Overall, our findings highlight the value of measuring and modeling the impacts of a nutrient enrichment gradient, as warming-related nutrient availability may impact ecosystems differently than single-level fertilization experiments.