Chianucci, F. | Search bioRxiv

bioRxiv2022

coveR: An R package for processing Digital Cover Photography images to retrieve forest canopy attributes

O_LIDigital Cover Photography (DCP) is an increasingly popular tool for estimating canopy cover and leaf area index (LAI). However, existing solutions to process canopy images are predominantly tailored for fisheye photography, whereas open-access tools for DCP are lacking. C_LIO_LIWe developed an R package (coveR) to support the whole processing of DCP images in an automated, fast, and reproducible way. The package functions, which are designed for step-by-step single-image analysis, can be performed sequentially in a pipeline, while also allowing simple implementation for batch-processing bunches of images. C_LIO_LIA case study is presented to demonstrate the reliability of canopy attributes derived from coveR in pure beech (Fagus sylvatica L.) stands with variable canopy density and structure. Estimates of gap fraction and effective LAI from DCP were validated against reference measurements obtained from terrestrial laser scanning. C_LIO_LIBy providing a simple, transparent, and flexible image processing procedure, coveR supported the use of DCP for routine measurements and monitoring of forest canopy attributes. This, combined with the implementability of DCP in many devices, including smartphones, micro-cameras, and remote trail cameras, can greatly expand the accessibility of the method also by non-experts. C_LI

plant biology↗

bioRxiv2021

With great power comes great responsibility: an analysis of sustainable forest management quantitative indicators in the DPSIR framework

The monitoring of environmental policies in Europe has taken place since the 1980s and still remains a challenge for decision- and policy-making. For forests, it is concretized through the publication of a State Of Europes Forests every five years, the last report just been released. However, the process lacks a clear analytical framework and appears limited to orient and truly assess sustainable management of European forests. We classified the 34 quantitative sustainable forest management indicators in the Driver-Pressure-State-Impact-Response (DPSIR) framework to analyse gaps in the process. In addition, we classified biodiversity-related indicators in the simpler Pressure-State-Response (PSR) framework. We showed that most of the sustainable forest management indicators assess the state of European forests, but almost half could be classified in another DPSIR category. For biodiversity, most indicators describe pressures, while direct taxonomic state indicators are very few. Our expert-based classification show that sustainable forest management indicators are unbalanced regarding the DPSIR framework. However, completing this framework with other indicators would help to have a better view and more relevant tools for decision-making. The results for biodiversity were comparable, but we showed that some indicators from other criteria than the one dedicated to biodiversity could also help understanding threats and actions concerning it. Such classification helps in the decision process, but is not sufficient to fully support policy initiative. In particular, the next step would be to better understand the links between DPSIR and PSR categories.

ecology↗