Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model

Carbon sequestration potential of plantation forests in New Zealand - no single tree species is universally best

BACKGROUND

Plantation forests are a nature-based solution to sequester atmospheric carbon and, therefore, mitigate anthropogenic climate change. The choice of tree species for afforestation is subject to debate within New Zealand. Two key issues are whether to use (1) exotic plantation species versus indigenous forest species and (2) fast growing short-rotation species versus slower growing species. In addition, there is a lack of scientific knowledge about the carbon sequestration capabilities of different plantation tree species, which hinders the choice of species for optimal carbon sequestration. We contribute to this discussion by simulating carbon sequestration of five plantation forest species, Pinus radiata, Pseudotsuga menziesii, Eucalyptus fastigata, Sequoia sempervirens and Podocarpus totara, across three sites and two silvicultural regimes by using the 3-PG an ecophysiological model.

RESULTS

The model simulations showed that carbon sequestration potential varies among the species, sites and silvicultural regimes. Indigenous Podocarpus totara or exotic Sequoia sempervirens can provide plausible options for long-term carbon sequestration. In contrast, short term rapid carbon sequestration can be obtained by planting exotic Pinus radiata, Pseudotsuga menziesii and Eucalyptus fastigata.

CONCLUSION

No single species was universally better at sequestering carbon on all sites we tested. In general, the results of this study suggest a robust framework for ranking and testing candidate afforestation species with regard to carbon sequestration potential at a given site. Hence, this study could help towards more efficient decision-making for carbon forestry.

Assessing scale-dependent effects on Forest biomass productivity based on machine learning

Estimating forest above-ground biomass (AGB) productivity constitutes one of the most fundamental topics in forest ecological research. Based on a 30-ha permanent field plot in Northeastern China, we modeled AGB productivity as output, and topography, species diversity, stand structure, and a stand density variable as input across a series of area scales using the Random Forest (RF) algorithm. As the grain size increased from 10 to 200 m, we found that the relative importance of explanatory variables that drove the variation of biomass productivity varied a lot, and the model accuracy was gradually improved. The minimum sampling area for biomass productivity modeling in this region was 140 × 140 m. Our study shows that the relationship of topography, species diversity, stand structure, and stand density variables with biomass productivity modeled using the RF algorithm changes when moving from scales typical of forest surveys (10 m) to larger scales (200 m) within a controlled methodology. These results should be of considerable interest to scientists concerned with forest assessment.

Stand carbon storage and net primary production in China's subtropical secondary forests are predicted to increase by 2060

BACKGROUND

Forest ecosystems play an important role in carbon sequestration, climate change mitigation, and achieving China's target to become carbon (C) neutral by 2060. However, changes in C storage and net primary production (NPP) in natural secondary forests stemming from tree growth and future climate change have not yet been investigated in subtropical areas in China. Here, we used data from 290 inventory plots in four secondary forests [evergreen broad-leaved forest (EBF), deciduous and evergreen broad-leaved mixed forest (DEF), deciduous broad-leaved forest (DBF), and coniferous and broad-leaved mixed forest (CDF)] at different restoration stages and run a hybrid model (TRIPLEX 1.6) to predict changes in stand carbon storage and NPP under two future climate change scenarios (RCP4.5 and RCP8.5).

RESULTS

The runs of the hybrid model calibrated and validated by using the data from the inventory plots suggest significant increase in the carbon storage by 2060 under the current climate conditions, and even higher increase under the RCP4.5 and RCP8.5 climate change scenarios. In contrast to the carbon storage, the simulated EBF and DEF NPP declines slightly over the period from 2014 to 2060.

CONCLUSIONS

The obtained results lead to conclusion that proper management of China's subtropical secondary forests could be considered as one of the steps towards achieving China's target to become carbon neutral by 2060.

Forest Management under Climate Change: A Decision Analysis of Thinning Interventions for Water Services and Biomass in a Norway Spruce Stand in South Germany

Climate change is producing threats to forests’ capacity of regulating water regimes. Therefore, thinning strategies can be applied to mitigate climate change impacts more efficiently by providing more spaces for trees to utilize resources e.g., water and nutrients. This study examined the effects of different thinning intensities and intervals on water characteristics and biomass growth of a 75-year-old Norway spruce (Picea abies) stand in the Black Forest, Germany. Here we used a water and management sensitive update of the process-based forest growth model 3PG, 3PG-Hydro. We applied light (10%), moderate (30%), and heavy thinning (50% intensity) in the interval of 10, 25, and 50 years of the management period. We simulated growth with climate change scenario RCP 8.5 data from 1995 to 2065. We analyzed the effects of the different thinning regimens on biomass, evapotranspiration as well as water yield. Thinning intensity and interval as well as their interaction have significant influence on production of stand biomass and water yield for all thinning regimes applied (p < 0.05). However, there is no significant difference (p > 0.05) in accumulated biomass (thinned biomass added to the stand biomass) between the applied thinning regimes. Light thinning in a long interval (50 years) produced highest stand biomass among the applied thinning regimes. Furthermore, the prediction showed that accumulated water yield increased with increasing thinning intensity. Our study concludes that repeated moderate thinning at intermediate intervals results in a high water yield without losing biomass production.

Estimating the distribution and productivity characters of Larix kaempferi in response to climate change

Understanding the distribution, net primary productivity (NPP) and environmental constraints of Larix kaempferi is crucial to predict how global climate change will affect its growth and future dynamics. We simulated future changes in the globally suitable distribution patterns and the NPP dynamics under different representative concentration pathways (RCPs) using MaxEnt and Physiological Principles in Predicting Growth (3-PG) models. The results showed that suitable distribution areas for Larix kaempferi were concentrated in Europe and Asia, followed by North America, under current climate conditions. Globally, about 33.75% of the suitable area was in China. Suitable areas decreased and shifted northward in Asia, Europe and China in the RCP scenarios. Larix kaempferi could adapt or move to higher latitudes/altitudes to mitigate the negative impacts of climate change. The NPP of Larix kaempferi in China was 241.85-863.57 g m^-2 a^-1 simulated by the 3-PG model after local parameterization, which was consistent with the measured NPP. Changes in NPP were predicted in future climates. When the correlations between climate factors and NPP were examined, under the more optimistic scenarios, NPP would increase significantly. The key parameters of the 3-PG model were the optimal temperature for growth, forest age, and the number of days of lost productivity in each frost period. Therefore, climate change has a quantitative and significant impact on the distribution and productivity of L. kaempferi, which was estimated successfully with the two modeling approaches. Our results will contribute to the improved cultivation, environment and management of L. kaempferi and potentially of other deciduous gymnosperms.

Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China

Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China.