Networking the forest infrastructure towards near real-time monitoring - A white paper.
Automated, standardized linking methods
Ecophysiology
Forest monitoring and observation infrastructure
Meta-network
Nowcasting and predictions in near real-time
Remote sensing
Journal
The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500
Informations de publication
Date de publication:
10 May 2023
10 May 2023
Historique:
received:
14
12
2022
revised:
06
02
2023
accepted:
07
02
2023
pubmed:
13
2
2023
medline:
13
2
2023
entrez:
12
2
2023
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 36775147
pii: S0048-9697(23)00783-0
doi: 10.1016/j.scitotenv.2023.162167
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
162167Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Zweifel Roman reports financial support was provided by Federal Office for the Environment.