New approaches in tree phenomics using IoT technologies and AI machine learning : the TreeTalker network

Climate variability and extremes are observed with increasing amplitude and frequency in almost any continent and extensive tree mortality and widespread forest dieback is an increasing and emergent global concern although direct attribution of extensive tree mortality to warming or drying episodes is still under debate (IPCC AR5). Although tree dieback is a combination of causes, including pathogen/pest invasions, genetic responses and management factors, still climate anomalies, even at shorter time scales, can trigger predisposition factors that may lead to irreversible tree decline and dieback.  Despite there are a number of methods for addressing simultaneously tree functions such as photosynthesis and transpiration at leaf level or at canopy scale the same information at high temporal frequency and at individual tree scale is not yet widely diffused. Taking advantage of new technology and latest developments in sensor science, (e.g Internet of Things) we have developed a new device able to measure simultaneously important tree parameters. The parameters are: 1) tree radial growth, as indicator of photosynthetic carbon allocation in biomass; 2) sap flow, as indicator of tree transpiration and functionality of xylem transport; 3) xylem moisture content as indicator of hydraulic functionality 3) light penetration in the canopy in terms of fractional absorbed radiation and 4) light spectral components related to foliage dieback and physiology, 5) tree stability parameters to allow real time forecast of potential tree fallings. We will present a synthesis of data coming from different forest locations including natural, urban and artificial plantations and discuss the capabilities to extend such network at global scale. Examples of AI machine learning application to ecophysiological data will presented. Finally we discuss the possibility of using the TreeTalker network in large scale phenomics applications for individual tree responses to climate change impacts and identification of plant traits.