Search

Abstract Background Understanding how trees develop their root systems is crucial for the comprehension of how wildland and urban forest ecosystems plastically respond to disturbances such as harvest, fire, and climate change. The interplay between the endogenously determined root traits and the response to environmental stimuli results in tree adaptations to biotic and abiotic factors, influencing stability, carbon allocation, and nutrient uptake. Combining the three-dimensional structure of the root system, with root morphological trait information promotes a robust understanding of root function and adaptation plasticity. Low Magnetic Field Digitization coupled with AMAPmod (botAnique et Modelisation de l’Architecture des Plantes) software has been the best-performing method for describing root system architecture and providing reliable measurements of coarse root traits, but the pace and scale of data collection remain difficult. Instrumentation and applications related to Terrestrial Laser Scanning (TLS) have advanced appreciably, and when coupled with Quantitative Structure Models (QSM), have shown some potential toward robust measurements of tree root systems. Here we compare, we believe for the first time, these two methodologies by analyzing the root system of 32-year-old Pinus ponderosa trees. Results In general, at the total root system level and by root-order class, both methods yielded comparable values for the root traits volume, length, and number. QSM for each root trait was highly sensitive to the root size (i.e., input parameter PatchDiam) and models were optimized when discrete PatchDiam ranges were specified for each trait. When examining roots in the four cardinal direction sectors, we observed differences between methodologies for length and number depending on root order but not volume. Conclusions We believe that TLS and QSM could facilitate rapid data collection, perhaps in situ, while providing quantitative accuracy, especially at the total root system level. If more detailed measures of root system architecture are desired, a TLS method would benefit from additional scans at differing perspectives, avoiding gravitational displacement to the extent possible, while subsampling roots by hand to calibrate and validate QSM models. Despite some unresolved logistical challenges, our results suggest that future use of TLS may hold promise for quantifying tree root system architecture in a rapid, replicable manner.

Abstract Hourly‐resolved measurements of stem radial variations (SRVs) provide valuable insights into how climate‐induced changes in hydrological regimes affect tree water status and tree stem radial growth. However, while SRVs are easily measured at the individual tree level, currently no methods are available to monitor this phenomenon across broad regions at intra‐annual (daily to weekly) scales. Near‐surface (in situ) thermal remote sensing—with its sensitivity to plant water status—may provide an approach for monitoring intra‐annual SRVs, with the potential for scaling these approaches to the landscape level. Thus, we explored the suitability of in situ thermal remote sensing, in combination with other environmental data, to monitor SRVs in a coniferous forest of the North American Intermountain West. Specifically, we were interested in answering two main questions: Can we use in situ thermal remote sensing by itself and in combination with environmental variables (i.e., photoperiod, photosynthetically active radiation, and soil moisture) to predict (1) daily tree water status and (2) daily tree stem radial growth derived from SRVs? We used data collected by an environmental monitoring network in central Idaho over three growing seasons (2019–2021) to address these questions. Results showed that leaf temperature (TL) in combination with environmental variables explained up to three‐quarters of the SRV‐based variability in daily tree water status (in the form of tree water deficit [TWD]) and approximately one‐half of the variability in daily stem radial growth. The time of day when TL was acquired also appeared to change the strength, shape, and predictive power of the models, with acquisition times in the morning and evening showing stronger relationships with daily SRVs than other times of the day. Overall, these results highlight the promise of utilizing thermal remote sensing data to derive tree hydrological and growth status, and reveal key considerations (e.g., the time of data acquisition) for future observational and modeling efforts. This study also provides a benchmark against which to compare future efforts to test these observed relationships at coarser spatial scales.

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.

Standing dead trees (known as snags) are historically difficult to map and model using airborne laser scanning (ALS), or lidar. Specific snag characteristics are important for wildlife; for instance, a larger snag with a broken top can serve as a nesting platform for raptors. The objective of this study was to evaluate whether characteristics such as top intactness could be inferred from discrete-return ALS data. We collected structural information for 198 snags in closed-canopy conifer forest plots in Idaho. We selected 13 lidar metrics within 5 m diameter point clouds to serve as predictor variables in random forest (RF) models to classify snags into four groups by size (small (