New technologies for forest monitoring in Alpine region

The science of forest digitalization via technological innovation offers an opportunity to develop new methods for mass monitoring forest resources. A key constraint is the ability to collect data, store and analyze said retrieved data. The TreeTalker® (TT+) is a multisensory IoT-driven platform designed to detect and collect information on individual trees where its nested sensor approach captures several key eco-physiological parameters autonomously and in semi-real-time. Key parameters are: 1) tree radial growth, as an indicator of photosynthetic carbon allocation in biomass; 2) sap flux density, as an indicator of tree transpiration and functionality of xylem transport; 3) stem water content as an indicator of hydraulic functionality 4) light penetration in the canopy in terms of fractional absorbed radiation 5) light spectral components related to foliage dieback and phenology and 6) tree stability parameters to allow real time forecast of potential tree fall. The focus of this study is to design/calibrate and validate sensors for stem water content and sap flow measurement using the TreeTalker platform with the application of these platforms for monitoring ecophysiological parameters at a single tree scale providing time series data for forest monitoring. i. Stem water content To demonstrate the capability of the TreeTalker, a three-phase experimental process was performed including (1) sensor sensitivity analysis, (2) sensor calibration, and (3) long-term field data monitoring. A negative linear correlation was demonstrated under temperature sensitivity analysis, and for calibration, multiple linear regression was applied on harvested field samples, explaining the relationship between the sample volumetric water content and the sensor output signal. Furthermore, in a field scenario, TreeTalkers were mounted on adult Fagus sylvatica L. and Quercus petraea L. trees, from June 2020 to October 2021, in a beech-dominated forest near Marburg, Germany, where they continuously monitored sap flux density and stem volumetric water content (stem VWC). The results show that the range of stem VWC registered is highly influenced by the seasonal variability of climatic conditions. Depending on tree characteristics, edaphic and microclimatic conditions, variations in stem VWC and reactions to atmospheric events occurred. Low sapwood water storage occurs in response to drought, which illustrates the high dependency of trees on stem VWC under water stress. Consistent daily variations in stem VWC were also clearly detectable. Stem VWC constitutes a significant portion of daily transpiration (using TreeTalkers, up to 4% for the beech forest in our experimental site). The diurnal–nocturnal pattern of stem VWC and sap flow revealed an inverse relationship. ii. Sap flow: an empirical approach Here, a new IoT-based multisensing device, TreeTalker® with its tailored firmware is exploited to input different heating duration to capture high-frequency data of both heating and cooling phases. Using this advance in technology, its application, we aim to assess the applicability and thus merit of the TreeTalker toward sap flux density measurement and computation. Capability analysis of TT+ is verified both under a lab scenario using an artificial hydraulic column of sawdust and a stem segment of F. sylvatica L. in the field via mounted TT+ devices and with the comparison of commercial sap flow sensors on different species. Installing a TT+ on the artificial flow system, temperature evolution data from heating and reference probes are recorded both in heating and cooling phases to compute values of different flow indices under different flux densities. Applied continuous heating mode and a transient regime with four different combinations of heating and cooling times (in minutes) 10/10, 5/10, 15/45, and 10/50 are tested by TT+ and calibration of flux density vs flow indices conducted by applying optimal fitting curve on the source data up to 8 (L dm-2 h-1). Nonetheless, comparing TT+ set on the transient regime (10H/50C) performance across different species of Norway spruce, European beech, and oak in situ with well know thermal approaches (TDP: Continous Heating and HPV: Heat Pulse Velocity method) proved that the TT+ is capable to measure sap flow with reasonable accuracy (≈80%) for network-based mass monitoring in remote areas with low power consumption. iii. Semi-analytical solution for transient regime Measurement of xylem sap flow via thermal dissipation probes (TDP) and the transient regime (TTD), which is essentially derived from the TDP system, are two widely accepted and applied methods for estimating whole-tree transpiration. So far, thermal dissipation approaches use empirical equations to estimate sap flow and although robust, by nature, are limited by their accuracy. To overcome the limitations typically associated with the empirical approach, a novel method is introduced to solve the heat partial differential equation driven by the mechanisms of conduction/convection for the transient thermal dissipation method (TTD) with heating/cooling cycles. Also, a simple semi-analytical method was developed to exploit the convolution integral of the heat flow equation. The capability of the novel solution is approved by comparing its results with observations under the controlled condition as well as the output of the available well-known empirical equations under field circumstances. An essential feature of the TreeTalker platform, therefore, is to capture the full heat flow curve at the microprocessor level and integrate a semi-analytical approach to mathematically evaluate the amount of sap velocity and thermal diffusivity at a large scale and in real-time. iv. TT+ applications at forest monitoring In this investigation, two sites (Molveno and Val Canali) are established with a total of 84 TT+ in the Alpine zone, Northern Italy. The Italian Alps are important ecosystems supporting rich landscapes and biodiversity with their forests supporting several key ecosystem services. Thus, monitoring these ecosystems is of critical importance to track the variation of individuals’ ecological demands in different species. For this study, we focus on two of the most dominant tree species across the Central European Forest, Fagus Sylvatica L. and Picea Abies L., to evaluate the TT+ as a novel biosensing platform for mass monitoring. Furthermore, we explore the relationships between site characteristics and abiotic factors using collected TreeTalkers data. Although not a complete substitute for field data collection, platforms such as the Treetalker can enhance established methods for mass monitoring, offers big data solutions on individual trees, and further the pursuit of forest digitalization. Yet, as with any new technology challenges remain related to obstacles such as sensor green character, durability, flexible design, maintenance, precision, and accuracy.