Maximizing carbon sequestration potential in Chinese forests through optimal management.

Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1-3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

Where should China practice forestry in a warming world?

As a nature-based and cost-effective solution, forestation plays a crucial role in combating global warming, biodiversity collapse, environmental degradation, and global well-being. Although China is acknowledged as a global leader of forestation and has achieved considerable overall success in environmental improvements through mega-forestation programs, many negative effects have also emerged at local scales due to the planting of maladapted tree species. To better help achieve carbon neutrality and the new vision of an ecological civilization, China has committed to further increase forestation. However, where forestation lands and such efforts should really be located is not so well understood yet and agreed upon, especially in the face of rapid climate change. Based on an ensemble-learning machine, we predicted the spatial habitats (ecological niche) of the forest, grassland, shrubland, and desert under present and future climate conditions based on the natural climax vegetation distribution across China. We show that the potential forestation lands are mainly located in eastern China, which is east of the Hu Line (also known as the Heihe-Tengchong Line). Under future climate change, forests will shift substantially in the latitudinal, longitudinal, and elevational distribution. Potential forestation lands will increase by 33.1 million hectares through the 2070s, mainly due to the conversions of shrub and grassland to forests along the Hu Line. Our prediction map also indicates that grassland rehabilitation is the universal optimal vegetation restoration strategy in areas west of the Hu Line. This analysis is consistent with much of the observed evidence of forestation failures and recent climate-change-induced forest range shifts. Our results provide an overview and further show the importance of adaptive science-based forestation planning and forest management.

Tradeoff between storage capacity and embolism resistance in the xylem of temperate broadleaf tree species.

Xylem traits are critical plant functional traits associated with water transport, mechanical support, and carbohydrate and water storage. Studies on the xylem hydraulic efficiency-safety tradeoff are numerous; however, the storage function of xylem parenchyma is rarely considered. The effects of a substantial number of xylem traits on water transport, embolism resistance, mechanical support, storage capacity and nonstructural carbohydrate (NSC) content were investigated in 19 temperate broadleaf species planted in an arid limestone habitat in northern China. There was no xylem hydraulic efficiency-safety tradeoff in the 19 broadleaf species. The total parenchyma fraction was negatively correlated with the fiber fraction. Embolism resistance was positively correlated with indicators of xylem mechanical strength such as vessel wall reinforcement, vessel wall thickness and fiber wall thickness, and was negatively related to the axial parenchyma fraction, especially the paratracheal parenchyma fraction. The paratracheal parenchyma fraction was positively correlated with the ratio of the paratracheal parenchyma fraction to the vessel fraction. In addition, the xylem NSC concentration was positively related to the total parenchyma fraction and axial parenchyma fraction. There was a storage capacity-embolism resistance tradeoff in the xylem of 19 broadleaf species in arid limestone habitats. We speculate that the temperate broadleaf species may show a spectrum of xylem hydraulic strategies, from the embolism resistance strategy related to a more negative P50 (the water potential corresponding to 50% loss of xylem conductivity) to the embolization repair strategy based on more paratracheal parenchyma.

The use of classification and regression algorithms using the random forests method with presence-only data to model species' distribution.

Random forests (RF) is a powerful species distribution model (SDM) algorithm. This ensemble model by default can produce categorical and numerical species distribution maps based on its classification tree (CT) and regression tree (RT) algorithms, respectively. The CT algorithm can also produce numerical predictions (class probability). Here, we present a detailed procedure involving the use of the CT and RT algorithms using the RF method with presence-only data to model the distribution of species. CT and RT are used to generate numerical prediction maps, and then numerical predictions are converted to binary predictions through objective threshold-setting methods. We also applied simple methods to deal with collinearity of predictor variables and spatial autocorrelation of species occurrence data. A geographically stratified sampling method was employed for generating pseudo-absences. The detailed procedural framework is meant to be a generic method to be applied to virtually any SDM prediction question using presence-only data. •How to use RF as a standard method for generic species distributions with presence-only data•How to choose RF (CT or RT) methods for the distribution modeling of species•A general and detailed procedure for any SDM prediction question.

Natural forests exhibit higher carbon sequestration and lower water consumption than planted forests in China.

Large-scale planted forests (PF) have been given a higher priority in China for improving the environment and mitigating climate change relative to natural forests (NF). However, the ecological consequences of these PF on water resource security have been less considered in the national scale. Moreover, a critically needed comparison on key ecological effects between PF and NF under climate change has rarely been conducted. Here, we compare carbon sequestration and water consumption in PF and NF across China using combination of remote sensing and field inventory. We found that, on average, NF consumed 6.8% (37.5 mm per growing season) less water but sequestered 1.1% (12.5 g C m-2  growing season-1 ) more carbon than PF in the period of 2000-2012. While there was no significant difference in water consumption (p = 0.6) between PF and NF in energy-limited areas (dryness index [DI] < 1), water consumption was significantly (p < 0.001) higher in PF than that in NF in water-limited regions (DI > 1). Moreover, a distinct and larger shift of water yield was identified in PF than in NF from the 1980s to the 2000s, indicating that PF were more sensitive to climate change, leading to a higher water consumption when compared with NF. Our results suggest NF should be properly valued in terms of maximizing the benefits of carbon sequestration and water yield. Future forest plantation projects should be planned with caution, particularly in water-limited regions where they might have less positive effect on carbon sequestration but lead to significant water yield reduction.

Consensus forecasting of species distributions: the effects of niche model performance and niche properties.

Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species' geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species' ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.

On the use of leaf spectral indices to assess water status and photosynthetic limitations in Olea europaea L. during water-stress and recovery.

Diffusional limitations to photosynthesis, relative water content (RWC), pigment concentrations and their association with reflectance indices were studied in olive (Olea europaea) saplings subjected to water-stress and re-watering. RWC decreased sharply as drought progressed. Following rewatering, RWC gradually increased to pre-stress values. Photosynthesis (A), stomatal conductance (gs), mesophyll conductance (gm), total conductance (gt), photochemical reflectance index (PRI), water index (WI) and relative depth index (RDI) closely followed RWC. In contrast, carotenoid concentration, the carotenoid to chlorophyll ratio, water content reflectance index (WCRI) and structural independent pigment index (SIPI) showed an opposite trend to that of RWC. Photosynthesis scaled linearly with leaf conductance to CO2; however, A measured under non-photorespiratory conditions (A1%O2) was approximately two times greater than A measured at 21% [O2], indicating that photorespiration likely increased in response to drought. A1%O2 also significantly correlated with leaf conductance parameters. These relationships were apparent in saturation type curves, indicating that under non-photorespiratory conditions, CO2 conductance was not the major limitations to A. PRI was significant correlated with RWC. PRI was also very sensitive to pigment concentrations and photosynthesis, and significantly tracked all CO2 conductance parameters. WI, RDI and WCRI were all significantly correlated with RWC, and most notably to leaf transpiration. Overall, PRI correlated more closely with carotenoid concentration than SIPI; whereas WI tracked leaf transpiration more effectively than RDI and WCRI. This study clearly demonstrates that PRI and WI can be used for the fast detection of physiological traits of olive trees subjected to water-stress.

Effects of seasonal snow on the growing season of temperate vegetation in China.

Variations in seasonal snowfall regulate regional and global climatic systems and vegetation growth by changing energy budgets of the lower atmosphere and land surface. We investigated the effects of snow on the start of growing season (SGS) of temperate vegetation in China. Across the entire temperate region in China, the winter snow depth increased at a rate of 0.15 cm yr(-1) (P = 0.07) during the period 1982-1998, and decreased at a rate of 0.36 cm yr(-1) (P = 0.09) during the period 1998-2005. Correspondingly, the SGS advanced at a rate of 0.68 day yr(-1) (P < 0.01) during 1982-1998, and delayed at a rate of 2.13 day yr(-1) (P = 0.07) during 1998-2005, against a warming trend throughout the entire study period of 1982-2005. Spring air temperature strongly regulated the SGS of both deciduous broad-leaf and coniferous forests, whereas the winter snow had a greater impact on the SGS of grassland and shrubs. Snow depth variation combined with air temperature contributed to the variability in the SGS of grassland and shrubs, as snow acted as an insulator and modulated the underground thermal conditions. In addition, differences were seen between the impacts of winter snow depth and spring snow depth on the SGS; as snow depths increased, the effect associated went from delaying SGS to advancing SGS. The observed thresholds for these effects were snow depths of 6.8 cm (winter) and 4.0 cm (spring). The results of this study suggest that the response of the vegetation's SGS to seasonal snow change may be attributed to the coupling effects of air temperature and snow depth associated with the underground thermal conditions.

[Research advances in simulating land water-carbon coupling].

The increasing demand of adaptive management of land, forest, and water resources under the background of global change and water resources crisis has promoted the comprehensive study of coupling ecosystem water and carbon cycles and their restrictive relations. To construct the water-carbon coupling model and to approach the ecosystem water-carbon balance and its interactive response mechanisms under climate change at multiple spatiotemporal scales is nowadays a major concern. After reviewing the coupling relationships of water and carbon at various scales, this paper explored the implications and estimation methods of the key processes and related parameters of water-carbon coupling, the construction of evapotranspiration model at large scale based on RS, and the importance of this model in water-carbon coupling researches. The applications of assimilative multivariate data in water-carbon coupling researches under future climate change scenarios were also prospected.

[The variability of vegetation beginning date of greenness period in spring in the north-south transect of eastern China based on NOAA NDVI].

NDVI based on NOAA/AVHRR from 1982 to 2003 are used to monitor variable rules for the growing season in spring of vegetation in the north-south transect of eastern China (NSTEC). The following, mainly, are included: (1) The changing speed of greenness period in spring of most regions in NSTEC is slow and correlation with the year is not distinct; (2) The regions in which greenness period in spring distinctly change mainly presented an advance; (3) The regions in which inter-annual fluctuation of greenness period in spring is over 10 days were found in 3 kinds of areas: the area covered with agricultural vegetation types; the areas covered with evergreen vegetation types; the areas covered with steppe vegetation types; (4) changes of vegetation greenness period in spring have spatio-temporal patterns.

[Canopy interception of sub-alpine dark coniferous communities in western Sichuan, China].

Based on field measurements of throughfall and stemflow in combination with climatic data collected from the meteorological station adjacent to the studied sub-alpine dark coniferous forest in Wolong, Sichuan Province, canopy interception of sub-alpine dark coniferous forests was analyzed and modeled at both stand scale and catchment scale. The results showed that monthly interception rate of Fargesia nitida, Bashania fangiana--Abies faxoniana old-growth ranged from 33% Grass to 72%, with the average of 48%. In growing season, there was a linear or powerful or exponential relationship between rainfall and interception an. a negative exponential relationship between rainfall and interception rate. The mean maximum canopy interception by the vegetation in the catchment of in.44 km was 1.74 ment and the significant differences among the five communities occurred in the following sequence: Moss-Fargesia nitida, Bashan afanglana-A. faxoniana stand > Grass-F. nitida, B. fangiana-A. faxoniana stand > Moss-Rhododendron spp.-A. faxoniana stand > Grass-Rh. spp.-A. faxoniana stand > Rh. spp. shrub. In addition, a close linear relationship existed between leaf area index (LAI) and maximum canopy interception. The simulated value of canopy interception rate, maximum canopy interception rate and addition interception rate of the vegetation in the catchment were 39%, 25% and 14%, respectively. Simulation of the canopy interception model was better at the overall growing season scale, that the mean relative error was 9%-14%.