A new generation of sensors and monitoring tools to support climate-smart forestry practices

Abstract

Climate-smart forestry (CSF) is an emerging branch of sustainable adaptive forest management aimed at enhancing the potential of forests to adapt to and mitigate climate change. It relies on much higher data requirements than traditional forestry. These data requirements can be met by new devices that support continuous, in-situ monitoring of forest conditions in real time. We propose a comprehensive network of sensors, i.e. a wireless sensor network (WSN), that can be part of a world-wide network of interconnected uniquely addressable objects, an Internet of Things (IoT), which can make data available in near real time to multiple stakeholders, including scientists, foresters, and forest managers, and may partially motivate citizens to participate in big data collection. The use of in-situ sources of monitoring data as ground-truthed training data for remotely sensed data can boost forest monitoring by increasing the spatial and temporal scale of the monitoring, leading to a better understanding of forest processes and potential threats. Here, some of the key developments and applications of these sensors are outlined, together with guidelines for data management. Examples are given of their deployment to detect early warning signals (EWS) of ecosystem regime-shifts in terms of forest productivity, health and biodiversity. Analysis of the strategic use of these tools highlights the opportunities for engaging citizens and forest managers in this new generation of forest monitoring.

An Introduction to Climate-Smart Forestry in Mountain Regions

“…Technological advances in manufacturing miniaturized machine tools and Internet network connecting systems have prompted the development of cyberinfrastructures to address ecological questions (Rundel et al 2009;Torresan et al 2021). The use of satellite imagery and statistical modelling has recently allowed the generation of a spatially continuous map of forest tree density at a global scale (Crowther et al 2015).…”

“…Wireless sensor nodes designed to provide interoperability with space observations, inventory data, meteorological records, and forest operations might reduce uncertainties and increase reliability of CSF indicators (see Chaps. 9, 10 and 11 of this book: Picchi et al 2021;Tognetti et al 2021;Torresan et al 2021). These real-time "windows on mountain forests" also provide compelling new ways to engage the public and provide novel tools for resource managers.…”

Continuous Monitoring of Tree Responses to Climate Change for Smart Forestry: A Cybernetic Web of Trees

“…Integrating image processing (e.g., scientific digital webcams; Bothmann et al 2017) with functional monitoring (e.g., sap flow gauges; Flo et al 2019) provides an example of how different sensors can be linked to address rapid dynamics in plant response to environmental changes. The fast development of advanced equipment and the vast amount of generated data may allow innovative data-driven approaches to replace traditional hypothesis-driven analyses, providing new insights on forest ecophysiology by means of artificial intelligence, e.g., machine learning approaches (Torresan et al 2021).…”

“…A critical feature of a network of sites that are digitally connected is the visualization of records and data storytelling to engage researchers, stakeholders, educators, and the public with climate-smart forests. However, wired systems are costly and energy-demanding, and their use in remote sites is limited (Torresan et al 2021). Advancements in wireless communication and sensor technologies provide researchers with flexible and scalable tools to monitor smart forestry systems.…”

Distinguishing Abrupt and Gradual Forest Disturbances With MODIS-Based Phenological Anomaly Series

“…Despite the advantages, remote-sensing products and applications alone do not provide all the answers needed (Chávez et al, 2019 ) in the current forest monitoring and practice seemingly leading to a limited acceptance of foresters. Thus, a workflow for retrieving up-to-date, reliable and precise information on the forest vitality status from satellite data is of great interest for early stage warning and diagnosis, as well as to support in preventative- and countermeasures in today's forest practice (Torresan et al, 2021 ). However, disturbances in forests lead to a variety of symptoms, from the loss or discoloration of leaves and needles (e.g., insects, fungi, drought) and the disruption of forest structures to the loss of standing wood volume (e.g., storm, fire) (Buma, 2015 ), which are so far assessed individually (Gao et al, 2020 ).…”