Does one model fit all? Patterns of beech mortality in natural forests of three European regions

Abstract

Large uncertainties characterize forest development under global climate change. Although recent studies have found widespread increased tree mortality, the patterns and processes associated with tree death remain poorly understood, thus restricting accurate mortality predictions. Yet, projections of future forest dynamics depend critically on robust mortality models, preferably based on empirical data rather than theoretical, not well-constrained assumptions. We developed parsimonious mortality models for individual beech (Fagus sylvatica L.) trees and evaluated their potential for incorporation in dynamic vegetation models (DVMs). We used inventory data from nearly 19,000 trees from unmanaged forests in Switzerland, Germany, and Ukraine, representing the largest dataset used to date for calibrating such models. Tree death was modelled as a function of size and growth, i.e., stem diameter (dbh) and relative basal area increment (relBAI), using generalized logistic regression accounting for unequal re-measurement intervals. To explain the spatial and temporal variability in mortality patterns, we considered a large set of environmental and stand characteristics. Validation with independent datasets was performed to assess model generality. Our results demonstrate strong variability in beech mortality that was independent of environmental or stand characteristics. Mortality patterns in Swiss and German strict forest reserves were dominated by competition processes as indicated by J-shaped mortality over tree size and growth. The Ukrainian primeval beech forest was additionally characterized by windthrow and a U-shaped size-mortality function. Unlike the mortality model based on Ukrainian data, the Swiss and German models achieved good discrimination and acceptable transferability when validated against each other. We thus recommend these two models to be incorporated and examined in DVMs. Their mortality predictions respond to climate change via tree growth, which is sufficient to capture the adverse effects of water availability and competition on the mortality probability of beech under current conditions.

Capturing ecological processes in dynamic forest models: why there is no silver bullet to cope with complexity

“…For the old‐growth simulations, the U‐shaped mortality formulation was clearly preferred over the reverse J‐shaped one, suggesting that at some point, large trees become susceptible to additional mortality agents (Canham et al 2001, Nagel and Diaci 2006, Perivancich 2010, Trotsiuk et al 2012, Holzwarth et al 2013). This is in line with ecological theory postulating high competition‐induced mortality of small trees and amplified mortality of large trees due to their exposure to a high number of mortality agents (Goff and West 1975, Lorimer and Frelich 1984, Franklin et al 1987), although the empirical evidence for an increasing mortality probability for larger diameters is not conclusive (Harcombe 1987, Monserud and Sterba 1999, Holzwarth et al 2013, Ruiz‐Benito et al 2013, Hülsmann et al 2016, 2018). Unfortunately, even though this pattern may be present in reality it is often not detectable due to the comparably low number of large trees in almost any dataset (Holzwarth et al 2013, Hülsmann et al 2016) and the possibly long right tail of the dbh distribution.…”

“…Such a relationship results from ecological theory because of high competition‐induced mortality of small trees and amplified mortality of large trees due to their exposure to a high number of mortality agents (Goff and West 1975, Lorimer and Frelich 1984, Franklin et al 1987, Harcombe 1987). Yet, empirical studies have not revealed a consistent pattern but either U‐ or reverse J‐shaped mortality over tree size (Monserud and Sterba 1999, Hurst et al 2011, Holzwarth et al 2013, Ruiz‐Benito et al 2013, Hülsmann et al 2016, Hülsmann et al 2018). In the case of ForClim, detailed inspection of model formulation and behavior revealed that high competition‐induced mortality rates of small trees are represented by the stress‐induced mortality formulation indeed.…”

How to kill a tree: empirical mortality models for 18 species and their performance in a dynamic forest model

“…Hülsmann et al. ). Subsequently, such mortality models should be incorporated in DVMs, a step that is made only rarely (but see Wyckoff and Clark , Wernsdörfer et al.…”

“…We followed the approach of model calibration and evaluation that was established and tested for Fagus sylvatica L. in Hülsmann et al. (). Specifically, we addressed three main questions: (1) Can life history traits such as maximum longevity and shade tolerance be used to group tree species into meaningful PFTs that account for species differences in mortality?…”

A framework for modeling adaptive forest management and decision making under climate change

“…A further key element of process understanding that needs further attention is tree mortality. Although many empirical and probabilistic models of tree mortality have been developed so far (e.g., Wunder et al 2008, Allen et al 2010, Hülsmann et al 2016, Vanoni et al 2016, the underlying processes and particularly their interactions are still poorly understood (Bigler et al 2006, McDowell et al 2011) making the integration of tree mortality in dynamic forest models challenging (Manusch et al 2012). In particular the implementation of disturbance-induced mortality and interactions and feedbacks among different disturbance agents, climate, vegetation, and forest management requires further process and understanding (Seidl et al , 2013.…”