Modeling dead wood in Fennoscandian old-growth forests dominated by Norway spruce

Abstract

If equilibrium is assumed in unmanaged forests, the volume of coarse woody debris (CWD), V CWD , may be calculated from (i) the volume of living trees, V living , (ii) average volume of a dead stem in relation to when it was alive, k, (iii) tree mortality rate, m, and (iv) residence time of CWD, t, by the equation V CWD = V living kmt. We parameterized this equation with data from Norway spruce (Picea abies (L.) Karst.) dominated forests in Fennoscandia. The V living was assumed to be directly proportional to forest productivity. Tree mortality data were from the National Forest Inventory, while it was difficult to find quantitative data on k and t. The predicted amounts (74-138 m 3 /ha, with larger amounts in the south) and size distribution (a negative exponential distribution of the number of stems) of CWD corresponded fairly well to averages from field inventories. By using a computer simulation program, the variability in tree mortality, density of living trees, and residence time of CWD were considered. In the simulations, the amount of CWD varied widely between 1-ha plots, especially for individual decay classes. Therefore, this model could be used to predict averages from larger landscapes unaffected by large disturbances, while no model can predict the amount of CWD at individual plots.Résumé : S'il existe un équilibre dans les forêts non aménagées, le volume de DLG (débris ligneux grossiers), V DLG , peut se calculer à partir (i) du volume des arbres vivants, V vivants , (ii) du volume moyen d'une tige morte relativement à son volume lorsque elle était encore vivante, k, (iii) du taux de mortalité des arbres, m, et (iv) du temps de résidence des DLG, t, avec l'équation V DLG = V vivants kmt. Nous avons estimé les paramètres de cette équation à l'aide de données provenant de forêts dominées par l'épicéa commun (Picea abies (L.) Karst.) en Fennoscandie. Nous avons assumé que V vivants était directement proportionnel à la productivité de la forêt. Les données de mortalité des arbres proviennent de l'inventaire forestier national, alors qu'il a été difficile de trouver de l'information sur k et t. Les quantités prédites (74-138 m 3 /ha, avec des quantités plus élevées dans le Sud) et la distribution de la taille des DLG (une distribution exponentielle négative du nombre de tiges) correspondent assez bien aux moyennes obtenues par des inventaires sur le terrain. La variabilité de la mortalité des tiges, de la densité des arbres vivants et du temps de résidence des DLG a été considérée à l'aide d'un programme de simulation. Dans les simulations, la quantité de DLG variait très fortement entre les places-échantillons d'un hectare, surtout pour les classes individuelles de décomposition. Conséquemment, ce modèle pourrait être utilisé pour prédire les valeurs moyennes pour des paysages à plus grande échelle qui n'ont pas été affectés par des perturbations importantes, alors qu'aucun modèle ne peut prédire la quantité de DLG dans chaque place-échantillon.[Traduit par la Rédaction] Ranius et al. 1034

Biomass conversion factors (density and carbon concentration) by decay classes for dead wood of Pinus sylvestris, Picea abies and Betula spp. in boreal forests of Sweden

“…To be able to determine the amount of C in the dead wood it is therefore necessary to have conversion factors from volume per decay class to biomass and to C concentration of the biomass. A considerable number of studies have been carried out on decomposition rates (Sollins, 1982;Harmon et al, 1987;Harmon and Hua, 1991;Krankina and Harmon, 1995;Stone et al, 1998;Naesset, 1999b;Ranius et al, 2004) of coarse woody debris but little is known about conversion factors relating decay class to C concentration. In particular, it is hard to find more than one study made on a certain decay class system.…”

Modelling deadwood supply for biodiversity conservation: Considerations, challenges and recommendations

“…Another alternative when deadwood production is linked to live tree growth is to allow the model to generate starting conditions. For example, Ranius et al (2004), starting with no legacy deadwood, ran simulations for 750 years. Over time, the number of stems entering the deadwood model through mortality reached equilibrium with the number of stems reaching complete decomposition, resulting in a stabilized deadwood pool comparable to oldgrowth boreal conditions in Fennoscandia.…”

“…When working in oldgrowth systems, the rates of tree mortality and decomposition are often assumed to be in equilibrium, with the influx of recently killed trees equal to the loss of deadwood through complete decomposition, maintaining a constant balance (Ranius et al 2004). However, this assumption is unlikely to hold in most forest systems, especially where pulses of mortality occur from disturbances such as fire, windthrow, insects, pathogens, or harvesting.…”

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“…For example, diversity of typical epixylic bryophyte species is known to be higher on logs in mid stages of decay (Kushnevskaya et al 2007), but there is insufficient information on the period of time that a log will occur in a required decay stage for particular species. Mean times for complete decay of logs of Norway spruce Picea abies have been estimated as 60 years in Southern Sweden (Ranius et al 2004) and 100 years in south-central Scandinavia (Storaunet, Rolstad 2002). Decay rate of snags compared to logs is much slower, and decay rate has a linear relationship with time after fall of snag or living tree (Storaunet, Rolstad 2002).…”

“…The rate of decay of CWD for a tree species depends of mode of origin (e.g. snag versus log), bole diameter (Holeksa et al 2008) and other factors like environmental conditions (Ranius et al 2004). Also height above ground of a log is related (negatively) to decay stage, and hence to diversity of saproxylic species (Botting, DeLong 2009).…”