How much does it take to be old? Modelling the time since the last harvesting to infer the distribution of overmature forests in France

Lucie Thompson,André Torre,Frédéric Bray,Nicolas Debaive,Eugénie Cateau,Yoan Paillet,Patrick Vallet,Eva Knop

doi:10.1111/ddi.13436

Abstract

AbstractAimThe distribution of overmature forests in metropolitan France is poorly known, with only a few well‐studied prominent sites, and has never been evaluated countrywide. Here, we modelled French forest reserves' time since the last harvesting operation—a proxy for forest maturity—then inferred the current statistical distribution of overmature forests (i.e., forests over 50 years without harvesting) in France.LocationMetropolitan France.MethodsWe used inventories from forest reserves and managed forests to calibrate a generalised linear mixed model explaining the time since the last harvesting with selected structural attributes and environmental variables. We then projected this model on the independent National Forest Inventory dataset. We thus obtained an updated estimation of the proportion and a rough distribution of overmature forest stands in metropolitan France.ResultsWe found that high basal area of very large trees, high volumes of standing and downed deadwood, high diversity of tree‐related microhabitats and more marginally diversity of decay stages best characterised the time since the last harvesting. Volumes of stumps and high density of coppices translating legacy of past forest management also distinguished more overmature plots. Our projection yielded an estimated 3% of French forests over 50 years without harvesting mostly located in more inaccessible areas (i.e., mountainous areas).Main conclusionsOur study showed that the time since the last harvesting could be derived from a combination of key structural attributes characterising overmature temperate forests. It gives the first robust statistical estimate of the proportion of overmature forests in France and may serve to report on their status. Our method could be extended in countries with accessible National Forest Inventory and calibration data, thus producing indicators at an international level.

Highlights

Old-growth forests have a key role in the mitigation of climate change
Wirth et al (2009) present various ways to define forest maturity. Their structural definition is a combination of dominant tree species' age and estimated longevity, with stands considered old-growth if they harbour dominant species older than half of their longevity. This definition is problematic in that (a) tree age is best determined by core sampling, a tedious task which may underestimate tree age (Speer, 2009) and (b) longevity is not a well-known species feature, it depends on various factors and might be biased by the long history of forest management displayed in European forests, resulting in most trees being harvested before they die of natural senescence (Cateau et al, 2015)
We modelled the time since the last harvesting as a function of stand structure and environmental variables using a generalised linear mixed model, with gamma error distribution, log link, and a “site” random effect, to take into account the nested sampling design (Bolker et al, 2009)

Summary

Introduction

Old-growth forests have a key role in the mitigation of climate change. They act as carbon storage and sinks (Achard & Hansen, 2012; Frey et al, 2016; Luyssaert et al, 2008). The use of the time since the last harvesting is a way of assessing the degree of naturalness of the forest in question, with increased occurrence of maturity feature or structural attributes in older unmanaged plots Those plots display more trees with larger diameters at breast height (Burrascano et al, 2013; Heiri et al, 2009; Paillet et al, 2015), a higher abundance of tree-related microhabitats (Larrieu et al, 2018; Paillet et al, 2017; Winter & Möller, 2008) along with high volumes of deadwood (Harmon, 2009; Siitonen et al, 2000). Those specific structural attributes harboured by more mature forests have high conservation value for biodiversity (Bauhus et al, 2009; Burrascano et al, 2013; Siitonen et al, 2000)

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