A dynamic environment-sensitive site index model for the prediction of site productivity potential under climate change

Yue, Chaofang; Kahle, Hans‐Peter; Wilpert, Klaus von; Kohnle, Ulrich

doi:10.1016/j.ecolmodel.2016.06.005

Cited by 29 publications

(20 citation statements)

References 45 publications

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“…Information concerning trends in site productivity may provide essential information for management, as well as adaptation and mitigation strategies against changing climatic conditions [23]. There have been many site productivity simulations under the changing climate conditions of European forests [5,59,60]. The observed trends of increasing the average temperature and reducing rainfall during the growing season adversely affect North American species (e.g., lodgepole and white spruce) [61].…”

Section: Discussionmentioning

confidence: 99%

Environmental Drivers and Age Trends in Site Productivity for Oak in Southern Poland

Socha

Maj

Cywicka

et al. 2021

Forests

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Site productivity provides critical information for forest management practices and is a fundamental measure in forestry. It is determined using site index (SI) models, which are developed using two primary groups of methods, namely, phytocentric (plant-based) or geocentric (earth-based). Geocentric methods allow for direct site growth modelling, in which the SI is predicted using multiple environmental indicators. However, changes in non-static site factors—particularly nitrogen deposition and rising CO2 concentration—lead to an increase in site productivity, which may be visible as an age trend in the SI. In this study, we developed a geocentric SI model for oak. For the development of the SI model, we used data from 150 sample plots, representing a wide range of local topographic and site conditions. A generalized additive model was used to model site productivity. We found that the oak SI depended predominantly on physicochemical soil properties—mainly nitrogen, carbon, sand, and clay content. Additionally, the oak SI value was found to be slightly shaped by the topography, especially by altitude above sea level, and topographic position. We also detected a significant relationship between the SI and the age of oak stands, indicating the long-term increasing site productivity for oak, most likely caused by nitrogen deposition and changes in climatic conditions. The developed geocentric site productivity model for oak explained 77.2% of the SI variation.

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Section: Discussionmentioning

confidence: 99%

Environmental Drivers and Age Trends in Site Productivity for Oak in Southern Poland

Socha

Maj

Cywicka

et al. 2021

Forests

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“…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].…”

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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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“…Inventory data or remotely sensed observations of canopy height provide a potential means for constructing age-height curves (Croft et al, 2014;Yue et al, 2016) to inform growth rates by age class. Alternately, Hiltner et al (2020) recently optimized mortality rates in an individual-based model at different forest successional stages by using satellite-derived proxies of tree mortality (Hiltner et al, 2020); their optimized model was shown to improve representation of forest states during post-disturbance regrowth.…”

Section: Opportunities For Improving Modeled Age Dynamicsmentioning

confidence: 99%

“…In the last decade, explicit model representation of forests as a function of time since disturbance (hereafter simply, "ecosystem age") has been a grand challenge in an effort to quantify the demographic response of forests to changes in climate, atmospheric CO 2 , land-use change and land management (LUCLM), and fire (Friend et al, 2014;Kondo et al, 2018;Pugh et al, 2019b). Much of the focus of these global modeling studies has been on the effect of natural and anthropogenic disturbances on the carbon dynamics in old-growth versus second-growth forests (Gitz and Ciais, 2003;Shevliakova et al, 2009;Kondo et al, 2018;Yue et al, 2018;Pugh et al, 2019b) but lack finer distinction of demographic effects at different age classes. Following a call to the science community to improve demographic representation in models (Fisher et al, 2016), there is now a growing list of global models that are capable of simulating global ecosystem demographics (Gitz and Ciais, 2003, OSCAR;Shevliakova et al, 2009, LM3V;Haverd et al, 2014, CABLE-POP;Lindeskog et al, 2013, LPJ-GUESS;Yue et al, 2018, ORCHIDEE MICT;Nabel et al, 2020, Jena Scheme for Biosphere Atmosphere Coupling in Hamburg version 4 -JSBACH4), although more models need the capability to represent landscape heterogeneity in forest structure and function.…”

Section: Introductionmentioning

confidence: 99%

Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model

Calle

Poulter

2021

Geosci. Model Dev.

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Abstract. Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in many global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to present the technical developments of a computationally efficient approach for representing age-class dynamics within a global ecosystem model, the Lund–Potsdam–Jena – Wald, Schnee, Landschaft version 2.0 (LPJ-wsl v2.0) dynamic global vegetation model and to determine if explicit representation of demography influenced ecosystem stocks and fluxes at global scales or at the level of a grid cell. The modeled age classes are initially created by simulated fire and prescribed wood harvesting or abandonment of managed land, otherwise aging naturally until an additional disturbance is simulated or prescribed. In this paper, we show that the age module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that simulated patterns of ecosystem function follow classic responses with age. We also present two scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a 45- to 60-year difference in ages between older boreal (50–90∘ N) and younger tropical (23∘ S–23∘ N) ecosystems. Between simulation years 1860 and 2016, land-use change and land management were responsible for a decrease in zonal age by −6 years in boreal and by −21 years in both temperate (23–50∘ N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped to reduce LPJ-wsl v2.0 complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature, and age class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C m−2 yr−1 but as high as 0.60 kg C m−2 yr−1 where the effect was greatest. In the eastern forests of North America, the simulated demographic effect was of similar magnitude, or greater than, the effects of climate; simulated demographic effects were similarly important in large regions of every vegetated continent. Simulated spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40 Pg C increase in biomass turnover when including age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. The LPJ-wsl v2.0 age module represents another step forward towards understanding the role of demography in global ecosystems.

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A dynamic environment-sensitive site index model for the prediction of site productivity potential under climate change

Cited by 29 publications

References 45 publications

Environmental Drivers and Age Trends in Site Productivity for Oak in Southern Poland

Environmental Drivers and Age Trends in Site Productivity for Oak in Southern Poland

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

Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model

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