Development and evaluation of an individual tree growth and yield model for the mixed species forest of the Adirondacks Region of New York, USA

Weiskittel, Aaron R.; Kuehne, Christian; McTague, J. P.; Oppenheimer, Mike

doi:10.1186/s40663-016-0086-3

Cited by 22 publications

(8 citation statements)

References 31 publications

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“…Recently, several new solutions have been proposed to model the growth of various forest-forming species [29,42,48,50,56,[59][60][61][62]. New growth functions have been used to develop site index models for different countries, such as Sweden [63], Finland [64], Spain [59,65,66], the USA [67,68], Turkey [61], and Poland [35,36,41,42,69].…”

Section: Modelsmentioning

confidence: 99%

Site Index Models for Main Forest-Forming Tree Species in Poland

Socha

Grabska

Orzeł

2020

Forests

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Site index is the most commonly used measure of potential site productivity, providing key information for forest management practices. It is determined using species-specific site index models that take into account climatic and edaphic factors. To reliably estimate the site index, appropriate models are necessary. In Poland, however, outdated guidelines, i.e., yield tables, are used to determine site classes, which result in the inappropriate estimation of height growth and increments of stands. Therefore, the aim of this study is to develop new site index models for the main forest forming tree species in Poland, in a total of eight species. For the development of site index models, we used growth trajectories of 3052 sample trees, representing the whole range of geographic locations and site conditions. Five dynamic models were selected and parametrized to develop the site index models. The models were evaluated using quantitative measures of goodness of fit (MAE, R2, and AIC), the analysis of residuals, and the assessment of how the model reflects the biological phenomena of height growth. Results showed that depending on the species, different models have the highest predictive ability. There are significant differences in results using traditional yield tables and developed site index models. For most of the species, the largest differences characterized either the youngest or the oldest age classes. These differences can be attributed to the changes in growth conditions from the time when yield tables were developed. Growth dynamics of forest stands may also show spatial variability, thus, in future research additional site variables and, regional variability should be taken into account.In recent years, forest ecosystems in Europe have experienced changes due to both the mean climate variables and the higher risk of extreme weather events [14]. Therefore, for effective long-term planning, forest management has to take into account the impact of climate change on stand growth and site productivity. In general, recent climate changes seem to have had a positive impact on forest productivity, although, this may vary at regional scales [15]. In northern and western Europe, a positive effect on forest growth and wood production is expected [14]. The site index considers the impact of climate conditions, expressing how the climatic and edaphic factors influence site productivity. Therefore, it is frequently used to analyze how environmental changes affect forest ecosystems [16][17][18][19][20]. Climate-sensitive site productivity models provide key information to develop forest management guidelines for adaptation steps and apply mitigation strategies against changing climatic conditions [21]. Site index models also play a crucial role in estimating the dynamics of forest carbon pools. According to the good practice guidance (GPG) of the Intergovernmental Panel on Climate Change (IPCC), the past and future dynamics of forest carbon pools should be calculated using stand volume. Stand volume is most commonly es...

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Section: Modelsmentioning

confidence: 99%

Site Index Models for Main Forest-Forming Tree Species in Poland

Socha

Grabska

Orzeł

2020

Forests

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“…(4)) included one distance-independent and one distance-dependent competition index, respectively BAL and . Both BAL and Hegyi competition indices are widely adopted in forest literature (Silveira et al, 2015;Orellana et al, 2016;Weiskittel et al, 2016;Hess et al, 2018;Kahriman et al, 2018). The inclusion of both competition indices suggests that a single competition index might not be enough to fully explain the competition (Kuehne, et al, 2019), and that different types of competition indices are suitable for different components of the overall competition (Tomé and Burkhart, 1989).…”

Section: Discussionmentioning

confidence: 99%

How Competition Indices Behave at Different Neighborhood Coverages and Modifications in a Natural Araucaria Forest in Southern Brazil

Orso

Mallmann

Pelissari

et al. 2020

CERNE

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“…This concern is often ignored during model validation. Some studies report the bias relative to the simulation period (e.g., Weiskittel et al 2016), but more often, the short period of observation for the validation data makes it difficult to evaluate a model's longterm error. BA bias has been evaluated for the 2014 version of Artemis over a 40-year simulation period (Power 2016).…”

Section: Discussionmentioning

confidence: 99%

Temporal pattern in basal area prediction error of a growth model for Quebec’s temperate forest

PowerHugues

AugerIsabelle

2020

The Forestry Chronicle

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Pour les utilisateurs, l’évaluation des performances et de la fiabilité d’un modèle de croissance est essentielle. Cependant, les biais spécifiques à l’espèce et à l’année d’observation sont rarement signalés, bien que des changements dans les conditions de croissance soient susceptibles d’augmenter la présence de tels biais dans les modèles. Dans cette étude, nous avons analysé l’erreur de prévision de la surface terrière d’Artemis, un modèle de croissance à l’échelle de l’arbre. Même si les prévisions du modèle étaient peu biaisées dans la plupart des conditions, nous avons détecté des tendances liées à l’espèce et à l’année d’observation. Ces tendances étaient les plus fortes pour l’érable à sucre (Acer saccharum Marsh.), pour lequel une sous-estimation de la surface terrière en 1975 évoluait vers une surestimation en 2010. Pour le sapin baumier (Abies balsamea (L.) Mill.), la tendance contraire a pu être observée. Une meilleure prise en compte par le modèle des conditions de croissance et des perturbations biotiques pourrait aider à diminuer les biais. Ces résultats sont pertinents pour les développeurs et pour les utilisateurs, qui doivent savoir que les prévisions du modèle de croissance pour ces deux espèces sont susceptibles d’être de plus en plus biaisées avec l’allongement de la période de simulation.

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Development and evaluation of an individual tree growth and yield model for the mixed species forest of the Adirondacks Region of New York, USA

Cited by 22 publications

References 31 publications

Site Index Models for Main Forest-Forming Tree Species in Poland

Site Index Models for Main Forest-Forming Tree Species in Poland

How Competition Indices Behave at Different Neighborhood Coverages and Modifications in a Natural Araucaria Forest in Southern Brazil

Temporal pattern in basal area prediction error of a growth model for Quebec’s temperate forest

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