Impacts of climate change on biological rotation of Larix olgensis plantations for timber production and carbon storage in northeast China using the 3-PGmix model

Predicting the growth suitability of Larix principis-rupprechtii Mayr based on site index under different climatic scenarios

Larix principis-rupprechtii Mayr (larch) is one of the main afforestation and timber production species used in North China. Climate change has led to a change in its suitable distribution and growth. However, the impact of climate change on its growth suitability is not clear. In this study, using forest resource inventory data and spatially continuous environmental factor data (temperature, precipitation, topography, and soil) in Hebei and Shanxi Provinces, China, the random forest model (RF) was used to simulate the larch site index (SI) and growth suitability under three shared socioeconomic pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the current and future (2021-2040, 2041-2060 and 2080-2100). The results revealed that (1) RF had excellent performance in predicting the regional SI (R² = 0.73, MAE = 0.93 m, RMSE = 1.35 m); (2) the main factors affecting the productivity of larch were the mean temperature of the warmest quarter (BIO10), elevation (ELEV), mean diurnal range (BIO2), and annual precipitation (BIO12); and (3) larch currently had a higher SI in the Bashang areas and in the high-altitude mountains. The areas characterized as unsuitable, poorly suitable, moderately suitable, and highly suitable accounted for 15.45%, 42.12%, 31.94%, and 10.49% of the total area, respectively. (4) Future climate warming had an obvious inhibitory effect on the SI, and the effect strengthened with increasing radiation intensity and year. (5) The moderately suitable and highly suitable areas of larch growth showed a downward trend under future climate scenarios. By the end of this century, the suitable growth areas would decrease by 14.14% under SSP1-2.6, 15.17% under SSP2-4.5, and 19.35% under SSP5-8.5. The results revealed the impact of climate change on larch growth suitability, which can provide a scientific basis for larch forest management.

Modeling the spatially heterogeneous relationships between tradeoffs and synergies among ecosystem services and potential drivers considering geographic scale in Bairin Left Banner, China

Understanding the complex relationships of tradeoffs and synergies among ecosystem services (ESs) is essential to achieve a comprehensive, coordinated, and sustainable development for human well-being. However, the quantitative measurement for the properties and intensities within these relationships as well as the deeper exploration of its formation mechanism from a spatial-explicit perspective is still a challenge. In this study, a comprehensive and general methodology was developed to quantitatively illustrate the intensities of tradeoffs/synergies among pairwise ESs and explore the spatially heterogeneous relationships between these relations and several socio-ecological drivers, integrating InVEST, geographical detector and multi-scale geographically weighted regression (MGWR) methods. The results indicated that (1) the properties and intensities of tradeoffs/synergies among various ESs varied greatly over space and presented significant clustered distribution patterns; (2) different relations between ESs were dominated by diverse drivers and the combined effects from multiple factors were stronger than any single one within this process. The tradeoffs/synergies between soil conservation and other ESs were mainly affected by geomorphological drivers including elevation and slope, while relations involved habitat quality could be attributed to vegetation and climate drivers such as precipitation and vegetation fractional cover. The relationships among ESs were more susceptible to topographic and anthropogenic drivers when concerning the carbon storage service; (3) compared to global ordinary least squares and local geographically weighted regression (GWR), the MGWR obtained better performance in explaining relationships between tradeoffs/synergies among ESs and potential drivers by operating different spatial scales. Accordingly, several spatially targeted ecological measures were proposed and recommended to reduce ESs tradeoffs and ultimately achieve better synergies. This research could enrich the methods in revealing the complex evolvement mechanism behind the tradeoffs/synergies among ESs and the proposed framework also provided a new perspective in the field of ESs tradeoffs/synergies studies and might be valuable guidance for other regions worldwide.

The influence of mussel restoration on coastal carbon cycling

Increasing responsiveness to anthropogenic climate change and the loss of global shellfish ecosystems has heightened interest in the carbon storage and sequestration potential of bivalve-dominated systems. While coastal ecosystems are dynamic zones of carbon transformation and change, current uncertainties and notable heterogeneity in the benthic environment make it difficult to ascertain the climate change mitigation capacity of ongoing coastal restoration projects aimed at revitalizing benthic bivalve populations. In this study we sought to distinguish between direct and indirect effects of subtidal green-lipped mussels (Perna canaliculus) on carbon cycling, and combined published literature with in-situ experiments from restored beds to create a carbon budget for New Zealand's shellfish restoration efforts. A direct summation of biogenic calcification, community respiration, and sediment processes suggests a moderate carbon efflux (+100.1 to 179.6 g C m^-2  year^-1 ) occurs as a result of recent restoration efforts, largely reflective of the heterotrophic nature of bivalves. However, an examination of indirect effects of restoration on benthic community metabolism and sediment dynamics suggests that beds achieve greater carbon fixation rates and support enhanced carbon burial compared to nearby sediments devoid of mussels. We discuss limitations to our first-order approximation and postulate how the significance of mussel restoration to carbon-related outcomes likely increases over longer timescales. Coastal restoration is often conducted to support the provisioning of many ecosystem services, and we propose here that shellfish restoration not be used as a single measure to offset carbon dioxide emissions, but rather used in tandem with other initiatives to recover a bundle of valued ecosystem services.

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.

Aboveground Biomass of Wetland Vegetation Under Climate Change in the Western Songnen Plain

Understanding the spatiotemporal dynamics of aboveground biomass (AGB) is crucial for investigating the wetland ecosystem carbon cycle. In this paper, we explored the spatiotemporal change of aboveground biomass and its response to climate change in a marsh wetland of western Songen Plain by using field measured AGB data and vegetation index derived from MODIS datasets. The results showed that the AGB could be established by the power function between measured AGB density and the annual maximum NDVI (NDVI_max) of marsh: Y = 302.06 × NDVI_max ^1.9817. The averaged AGB of marshes showed a significant increase of 2.04 g⋅C/m²/a, with an average AGB value of about 111.01 g⋅C/m² over the entire western Songnen Plain. For the influence of precipitation and temperature, we found that the annual mean temperature had a smaller effect on the distribution of marsh AGB than that of the total precipitation in the western Songnen Plain. Increased precipitation in summer and autumn would increase AGB by promoting marshes' vegetation growth. In addition, we found that the minimum temperature (T_min) and maximum temperatures (T_max) have an asymmetric effect on marsh AGB on the western Songnen Plain: warming T_max has a significant impact on AGB of marsh vegetation, while warming at night can non-significantly increase the AGB of marsh wetland. This research is expected to provide theoretical guidance for the restoration, protection, and adaptive management of wetland vegetation in the western Songnen Plain.

Climate Change Effects on Height–Diameter Allometric Relationship Vary with Tree Species and Size for Larch Plantations in Northern and Northeastern China

Tree height–diameter relationship is very important in forest investigation, describing forest structure and estimating carbon storage. Climate change may modify the relationship. However, our understanding of the effects of climate change on the height–diameter allometric relationship is still limited at large scales. In this study, we explored how climate change effects on the relationship varied with tree species and size for larch plantations in northern and northeastern China. Based on the repeated measurement data of 535 plots from the 6th to 8th national forest inventory of China, climate-sensitive tree height–diameter models of larch plantations in north and northeast China were developed using two-level nonlinear mixed effect (NLME) method. The final model was used to analyze the height–diameter relationship of different larch species under RCP2.6, RCP 4.5, and RCP8.5 climate change scenarios from 2010 to 2100. The adjusted coefficient of determination Radj2, mean absolute error (MAE) and root mean squared error (RMSE) of the NLME models for calibration data were 0.92, 0.76 m and 1.06 m, respectively. The inclusion of climate variables mean annual temperature (MAT) and Hargreaves climatic moisture deficit (CMD) with random effects was able to increase Radj2 by 19.5% and reduce the AIC (Akaike’s information criterion), MAE and RMSE by 22.2%, 44.5% and 41.8%, respectively. The climate sensitivity of larch species was ranked as L. gmelinii > the unidentified species group > L. principis > L. kaempferi > L. olgensis under RCP4.5, but L. gmelinii > L. principis > the unidentified species group > L. olgensis > L. kaempferi under RCP2.6 and RCP8.5. Large trees were more sensitive to climate change than small trees.

A Decade's Change in Vegetation Productivity and Its Response to Climate Change over Northeast China

In this study, we simulated vegetation net primary productivity (NPP) using the boreal ecosystem productivity simulator (BEPS) between 2003 and 2012 over Northeast China, a region that is significantly affected by climate change. The NPP was then validated against the measurements that were calculated from tree ring data, with a determination coefficient (R²) = 0.84 and the root mean square error (RMSE) = 42.73 gC/m²·a. Overall, the NPP showed an increasing trend over Northeast China, with the average rate being 4.48 gC/m²·a. Subsequently, partial correlation and lag analysis were conducted between the NPP and climatic factors. The partial correlation analysis suggested that temperature was the predominant factor that accounted for changes in the forest NPP. Solar radiation was the main factor that affected the forest NPP, and the grass NPP was the most closely associated with precipitation. The relative humidity substantially affected the annual variability of the shrub and crop NPPs. The lag time of the NPP related to precipitation increased with the vegetation growth, and it was found that the lag period of the forest was longer than that of grass and crops, whereas the cumulative lag month of the forest was shorter. This comprehensive analysis of the response of the vegetation NPP to climate change can provide scientific references for the managing departments that oversee relevant resources.