Forest Net Primary Productivity Research Articles

Does Central Asian forest growth benefit from a warming-wetting climate? Insights from tree-ring records

Abstract Climate warming has pronounced impacts on high-elevation regions, including arid Central Asia, and has multiple impacts on the environment. Forests in these mountainous areas provide essential services by regulating regional climate, sequestering carbon, and supporting soil and water conservation. However, trends in forest productivity and their response to climate change remain unclear. To address this knowledge gap, we collected tree cores from five sample plots in the western Tianshan region. We used tree-ring widths to reconstruct Net Primary Productivity (NPP) and investigated the sensitivity of forest NPP to climate change by analysing weather station data and employing LASSO regression to identify climatic factors influencing forest growth. Our results demonstrate that the reconstructed forest NPP effectively captured significant carbon shifts and revealed a non-significant increase in forest productivity associated with climate warming and higher precipitation between 1970 and 2020 at low and middle elevations in the Tianshan mountains. Humidity is the primary limiting factor affecting forest growth in this region. Conversely, the relationship between temperature and forest growth is not consistent as precipitation increases. Our findings suggest that continued warming will exacerbate water stress in forests.

Influence of soil nutrients on net primary productivity in post-mining forests in the Colombian Pacific

ABSTRACT Tropical forests have the highest rates of net primary productivity (NPP) in terrestrial ecosystems and, therefore, may contribute significantly to the mitigation of global climate change. Although NPP is influenced by soil fertility, and recently, in some regions, mining activity in forest ecosystems has intensified. Little is known about how soils determine the restoration of NPP in forests degraded by mining. We evaluated the influence of soil nutrients on wood NPP of post-mining forests in the biogeographic Chocó region (Colombia), with emphasis on the effects of nitrogen (N) and phosphorus (P) limitations in post-mining forests under successional stages of 12-15 or 30-35 years. For this, permanent plots were established in secondary post-mining forests in Jigualito (Colombian Pacific), the wood NPP (accumulated and current) was evaluated, and it was related to soil properties such as organic matter (OM), acidity, Al, total N, available P, magnesium (Mg), potassium (K), calcium (Ca), and texture. An accumulated wood NPP of 0.72 t ha -1 yr -1 was recorded in post-mining forests 12-15 years old. Meanwhile, in post-mining forests of 30-35 years, the accumulated wood NPP was 6.52 t ha -1 yr -1 . The current wood NPP was 4.25 t ha -1 yr -1 in post-mining forests with 30-35 years of recovery. Accumulated NPP positively correlated with soil OM, total N, Ca, Mg, and effective cation exchange capacity–ECEC in post-mining forests. In post-mining forests, a slow recovery of the wood NPP was denoted in the first years. Soil nutrients determined the wood NPP, and a multiple limitation of nutrients with the succession was observed, which corroborates the need to restore the degraded ecosystem in the region.

Evaluation of five models for constructing forest NPP–age relationships in China based on 3121 field survey samples

Abstract. Forest net primary productivity (NPP), representing the net carbon gain from the atmosphere, varies significantly with forest age. Reliable forest NPP–age relationships are essential for forest carbon cycle modeling and prediction. These relationships can be derived from forest inventory or field survey data, but it is unclear which model is the most effective in simulating forest NPP variation with age. Here, we aim to establish NPP–age relationships for China's forests based on 3121 field survey samples. Five models, including the semi-empirical mathematical (SEM) function, the second-degree polynomial (SDP) function, the logarithmic (L) function, the Michaelis–Menten (M) function, and the Γ function, were compared against field data. Results of the comparison showed that the SEM and Γ functions performed much better than the other three models, but due to the limited field survey samples at old ages, the Γ function showed a sharp decrease in NPP (decreased to almost zero) at old ages when building some forest NPP–age curves, while SEM could capture the variations in forest NPP at old ages reasonably well. Considering the overall performance with currently available forest field survey samples, SEM was regarded as the optimal NPP–age model. The finalized forest NPP–age curves for five forest types in six regions of China can facilitate forest carbon cycle modeling and future projection by using the process-based Integrated Terrestrial Ecosystem Carbon (InTEC) model in China and may also be useful for other regions.

Assessing forest net primary productivity based on a process-based model: Focusing on pine and oak forest stands in South and North Korea

Assessing forest net primary productivity based on a process-based model: Focusing on pine and oak forest stands in South and North Korea

Spatiotemporal patterns of net primary productivity of subtropical forests in China and its response to drought

Net primary productivity (NPP) is an important indicator used to evaluate the carbon sequestration capacity of forest ecosystems. Subtropical forest ecosystems play an indispensable role in maintaining the global carbon balance, while frequently occurring drought events in recent years have seriously damaged their productivity. However, the spatiotemporal patterns of NPP, as well as its response to drought, remain uncertain. In this study, the multiscale drought characteristics in subtropical China during 1981–2015 were analyzed based on the standardized precipitation evapotranspiration index. Then, simulated and analyzed the spatiotemporal NPP of subtropical forests by the boreal ecosystem productivity simulator model. Finally, the response of NPP to drought was analyzed based on multiple statistical indices. The results show that most regions in subtropical China experienced mild and moderate drought during 1981–2015. In particular, the extent of drought severity has shown a noticeable increasing trend after 2000. The forest NPP ranged from 622.64 to 1323.82 gC·m−2·a−1, with an overall increase rate of 16.15 gC·m−2·a−1; in particular, the contribution of the western forest NPP became increasingly important. Drought stress has limited the growth of subtropical forest NPP in China, with summer and wet season time scales of drought having the greatest impact on forest NPP anomalies, followed by autumn time scales. The limitation is mostly because the drought duration continually increased, leading to differences in the impact of drought on forest NPP before and after 2000, with declines of 59.55 % and 82.45 %, respectively, mainly concentrated in southwestern regions, such as Yunnan, Guangxi, and Sichuan provinces. This study quantitatively analyzed the impact of drought on subtropical forest NPP, and provides scientific basis for subtropical forest response and adaptation to climate change.

Variable influence of photosynthetic thermal acclimation on future carbon uptake in Australian wooded ecosystems under climate change.

Climate change will impact gross primary productivity (GPP), net primary productivity (NPP), and carbon storage in wooded ecosystems. The extent of change will be influenced by thermal acclimation of photosynthesis-the ability of plants to adjust net photosynthetic rates in response to growth temperatures-yet regional differences in acclimation effects among wooded ecosystems is currently unknown. We examined the effects of changing climate on 17 Australian wooded ecosystems with and without the effects of thermal acclimation of C3 photosynthesis. Ecosystems were drawn from five ecoregions (tropical savanna, tropical forest, Mediterranean woodlands, temperate woodlands, and temperate forests) that span Australia's climatic range. We used the CABLE-POP land surface model adapted with thermal acclimation functions and forced with HadGEM2-ES climate projections from RCP8.5. For each site and ecoregion we examined (a) effects of climate change on GPP, NPP, and live tree carbon storage; and (b) impacts of thermal acclimation of photosynthesis on simulated changes. Between the end of the historical (1976-2005) and projected (2070-2099) periods simulated annual carbon uptake increased in the majority of ecosystems by 26.1%-63.3% for GPP and 15%-61.5% for NPP. Thermal acclimation of photosynthesis further increased GPP and NPP in tropical savannas by 27.2% and 22.4% and by 11% and 10.1% in tropical forests with positive effects concentrated in the wet season (tropical savannas) and the warmer months (tropical forests). We predicted minimal effects of thermal acclimation of photosynthesis on GPP, NPP, and carbon storage in Mediterranean woodlands, temperate woodlands, and temperate forests. Overall, positive effects were strongly enhanced by increasing CO2 concentrations under RCP8.5. We conclude that the direct effects of climate change will enhance carbon uptake and storage in Australian wooded ecosystems (likely due to CO2 enrichment) and that benefits of thermal acclimation of photosynthesis will be restricted to tropical ecoregions.

Natural Vegetation Succession Under Climate Change and the Combined Effects on Net Primary Productivity

AbstractClimate change and the resulting natural vegetation succession can alter vegetation productivity. However, the mechanisms underlying future productivity changes under the two influences remain unclear. Here, we used the comprehensive sequence classification system to simulate changes in global potential natural vegetation under different climate scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5), and combined the Carnegie–Ames–Stanford Approach model with random forest to assess the response of net primary productivity (NPP) to climate change and vegetation succession from 2020 to 2100. Except for SSP126, terrestrial NPP in 2100 decreased by 0.86, 2.39, and 2.54 Pg C·a−1 versus 2020 under SSP2‐4.5, SSP5‐8.5, and SSP3‐7.0, respectively. Forest was the primary contributor to terrestrial NPP changes. The total forest area was projected to increase under all scenarios, with SSP2‐4.5 showing the largest increase (358.57 × 104 km2). However, expanding forest regions exhibited a relatively low mean NPP, while stable regions demonstrated a declining pattern. Consequently, forest NPP increased under SSP1‐2.6 but decreased by 4.03, 3.43, and 0.82 Pg C·a−1 in 2100 versus 2020 under SSP5‐8.5, SSP3‐7.0, and SSP2‐4.5, respectively. In comparison, grassland and desert exerted minor influence on terrestrial NPP changes, their total NPP decreased only under the SSP1‐2.6 scenario. The grassland area decreased, but the mean NPP increased, whereas the desert area expanded, resulting in consistent changes in both total and mean NPP. Our results analyzed the effects of climate change and vegetation distribution under its influence on the change of NPP, which can deepen our understanding of their relationship.

Vegetation Dynamics and Its Trends Associated with Extreme Climate Events in the Yellow River Basin, China

As a vital ecological barrier in China, Yellow River Basin (YRB) is strategically significant for China’s national development and modernization. However, YRB has fragile ecosystems, and is sensitive to climatic change. Extreme climate events (e.g., heavy precipitation, heatwaves, and extreme hot and cold) occur frequently in this basin, but the implications (positive and negative effects) of these events on vegetation dynamics remains insufficiently understood. Combing with net primary productivity (NPP), the normalized difference vegetation index (NDVI) and extreme climate indexes, we explored the spatio–temporal characteristics of plants’ growth and extreme climate, together with the reaction of plants’ growth to extreme climate in the Yellow River Basin. This study demonstrated that annual NPP and NDVI of cropland, forest, and grassland in the study region all revealed a climbing tendency. The multi-year monthly averaged NPP and NDVI were characterized by a typical unimodal distribution, with the maximum values of NPP (66.18 gC·m−2) and NDVI (0.54) occurring in July and August, respectively. Spatially, multi–year averaged of vegetation indicators decreased from southeast to northwest. During the study period, carbon flux (NPP) and vegetation index (NDVI) both exhibited improvement in most of the YRB. The extreme precipitation indexes and extreme high temperature indexes indicated an increasing tendency; however, the extreme low temperature indexes reduced over time. NPP and NDVI were negatively associated with extreme low temperature indexes and positively correlated with extreme high temperature indexes, and extreme precipitation indicators other than consecutive dry days. Time lag cross–correlation analysis displayed that the influences of extreme temperature indexes on vegetation indexes (NPP and NDVI) were delayed by approximately six months, while the effects of extreme precipitation indexes were immediate. The study outcomes contribute to our comprehension of plants’ growth, and also their reaction to extreme climates, and offer essential support for evidence–based ecological management practices in the Yellow River Basin.

A multi-dimensional analysis on potential drivers of China's city-level low-carbon economy from the perspective of spatial spillover effects

Under the background of “carbon peak” and “carbon neutrality”, China's cities are at the heart of climate change mitigation. To fulfill the commitments, the potential drivers of China's low-carbon economy at the city level should be explored. Thus, this study estimated the quality of low-carbon economy from the perspectives of carbon emissions and sequestration. Subsequently, spatial econometric approach was adopted to analyze the direct and spatial spillover effects of drivers on low-carbon economy. Moreover, to explore more potential variables, this study combined machine learning algorithms with different weight matrices to assess the importance scores of neighbouring cities' potential variables. The results show that (1) GDP per capita, emissions reduction technological progress, terrestrial vegetation's net primary productivity and the ratio of forest land cover improved cities' low-carbon economy; (2) land urbanization reduced nearby cities' low-carbon economy (especially those with high human footprint index at the inter-city border), which was caused by its negative spatial spillover effects on forest net primary production; (3) based on importance analysis, this study found that the characteristics of different sectors (e.g., the ratio of labor to fixed capital stocks, employment and fixed asset investment expenditure) also significantly influenced nearby cities' low-carbon economy.

Drought characteristics and their impacts on vegetation net primary productivity in the subtropical China

Drought is one of the main factors limiting forest productivity, and thus greatly affects the carbon sink capacity of forests. Here we first chose two drought indices including standardized precipitation evapotranspiration index (SPEI) and self-calibrating Palmer drought severity index (scPDSI) to reflect and analyze the spatiotemporal patterns of drought in the subtropical China. Then, the validated CASA (Carnegie-Amer-Stanford Approach) model was applied to estimate forest net primary productivity (NPP) and further quantify the contributions of drought events and their characteristics on forest NPP. The results showed that drought events during 2000–2015 have resulted in a mean decline of forest NPP of 7.2%. Moderate or severe drought events reduced NPP more significantly than extremely severe drought events. In addition, there was 1–2 years of lagging in the NPP responses to drought, and the lagging time varied with forest types. Our study suggests that forest managers and local governments should pay more attention to the places with moderate and severe drought events, and take measures to avoid NPP decline within the 2 years after drought. Our study also provides data support for further identifying the contribution of drought to ecosystem carbon fluxes in the subtropical China.

NPP and Carbon Emissions under Forest Fire Disturbance in Southwest and Northeast China from 2001 to 2020

With climate change, frequent forest fires and prolonged fire period occur all over the world. Moreover, carbon emission from forest fire affects the carbon cycle of the forest ecosystem. However, this effect varies by region with no uniform conclusions, and fewer comparative studies exist on such differences between regions. In this paper, net primary productivity (NPP) data MOD17A3 were used as an important parameter of forest carbon absorption, along with MODIS fire spot data MCD14DL and burned area data MCD64A1. Forest carbon lost under forest fire interference in the northeast and southwest natural forest areas of China was studied to explore the role of forest fire in the carbon cycle process and its differences in the unlike regions of China. Here, by means of kernel density analysis and M-K trend test, the characteristics of forest fires in China’s southwest and northeast forests were calculated. Forest carbon emission under forest fire disturbance was quantified by reference to the forest fire emission factor list. We show that (1) the total number of forest fire spots in the southwest region from 2001 to 2020 was 1.06 × 105, 1.28 times that of Northeast China. However, the total burned area in the southwest was only 67.84% of that in the northeast. (2) The total carbon emissions from forest fires in the southwest from 2001 to 2020 was 37,559.94 Gg, 10.77% larger than the northeast forest, CH4 and CO2 were 13.52% and 11.29% larger respectively. Moreover, the carbon emissions of forest fire in the northeast showed a downward trend, R2 = 0.16 (p < 0.1), while it remained basically unchanged in the southwest. The contribution of carbon emissions from forest fires changed with forest types, it was shown as: evergreen needleleaf forest (14.98%) > evergreen broadleaf forest (10.81%) > deciduous needleleaf forest (6.52%) > deciduous broadleaf forest (5.22%). (3) From 2001 to 2020, under the premise that the NPP both manifested upward trends, the NPP of the burned areas showed a significant downward trend in the southwest forest, with R2 = 0.42 (p < 0.05), while it increased in the northeast forest, with R2 = 0.37 (p < 0.05). It showed negative correlation between NPP of burned areas and forest fire carbon emissions, and forest fire disturbance had no significant effect on forest NPP in Northeast China, while net carbon loss occurred in Southwest China. In general, under different forest fire characteristics, NPP, which represents forest carbon uptake, and carbon emissions from forest fires show differences. The impact of forest fire disturbance on forest carbon process varies with regions. The study can provide some ideas on the effects of forest fire disturbance on climate change.

Species mixtures increase fine root length to support greater stand productivity in a natural boreal forest

Abstract Species mixtures have been widely reported to increase aboveground productivity; however, how tree species mixtures affect root systems in natural forests remains unclear. We hypothesize that mixtures have a greater fine root length compared to single species‐dominated stands to support their greater productivity. Here, we collected monthly root images from the minirhizotrons installed in 18 stands either dominated by Populus tremuloides, Pinus banksiana, and their mixtures for three years (2015–2017) in post‐fire boreal forests of two stand ages (8 and 34 years old) to test our hypotheses. We found that the fine root length was higher in mixtures than in single species‐dominated stands, and the magnitude of mixture effects was greater in the 34‐ than in the 8‐year‐old stands in the third year. The mixture effects on fine root length revealed a positive relationship with forest net primary productivity. Root length production, which is the growth of new roots within a year, was not affected by tree species mixtures except for the 8‐year‐old stand in 2015. Tree species mixtures did not affect root length turnover. Root length and root biomass were not significantly correlated at stand level. Synthesis. Our results show that tree species mixtures positively affect fine root length, with that positive effect increasing with stand development in the studied natural forests. Our results suggest that the greater root length in species mixtures supported the greater forest productivity in species mixtures as the greater root length benefits plant uptake of nutrients and water. Therefore, conserving tree species diversity has implications for improving forest productivity and carbon sequestration in forest ecosystems.

Machine learning-based prediction and assessment of recent dynamics of forest net primary productivity in Romania

While the analysis of spatio-temporal changes in the net primary productivity (NPP) of forests can provide critical information on carbon cycle and climate change, these ecological trends have remained unclear in many countries worldwide, including Romania. By using complex (satellite, forest and climate) data, many sophisticated (machine learning) algorithms and some widely applied (the Mann-Kendall test and Sen's slope estimator) statistical procedures, this study investigates, for the first time, recent forest NPP trends (1987–2018) that occurred in Romania, in relation to climate change that affected the country over the past decades. Following the modelling, mapping and assessment of NPP dynamics, results showed almost exclusively positive trends for this ecological parameter, which accounts for ∼99% of all forest NPP changes that occurred throughout the country, after 1987. Interestingly, almost three quarters (∼73%) of all NPP increasing trends are statistically significant, which indicates that Romania's forests have recently experienced a large-scale improvement in carbon fluxes and stocks. Investigations of eco-climatic relationships suggest that climate change has partially contributed to these surprising NPP dynamics observed in recent decades. All these findings can provide valuable information for forest management and for many stakeholders and policymakers who operate in the forestry and climate fields in Romania.

Topography intensifies variations in the effect of human activities on forest NPP across altitude and slope gradients

The distribution pattern of forest net primary productivity (NPP) is mainly driven by biotic (climate) and abiotic (topography and human activity) factors. However, the influence of these factors on NPP's distribution along the elevation and slope gradient is uncertain. Additionally, it remains uncertain whether the pattern of NPP at the regional scale with significant altitude variations is comparable to that at the mountain scale. This study analyzed the NPP distribution pattern in the Yangtze River Basin, a region with high altitude heterogeneity, and investigated the impact of climate and human activity on the NPP along the elevation and slope gradient. The results revealed that as altitude increased, NPP first rose and then declined, reaching a peak at 2200–2300 m above sea level, This is in line with the distribution of NPP in mountainous areas and suggests that regions with large elevation differences may also experience vertical effects. NPP displayed an “N” shaped distribution along the slope gradient and the effect of climatic factors varied at different altitudes. Precipitation has a greater effect on NPP than the temperature in regions with less than 2300 m altitude, whereas temperature has the opposite effect in high-elevation regions (>2300 m). The study also found that afforestation and the returning farmland to forestland mainly occurred in low- and middle-altitude regions and middle-slope regions, leading to rapid NPP growth. These findings reveal that topography influences climate and human impacts on forest NPP, and future forest management strategies should consider the terrain's impact on tree growth and protect forests in high-altitude and steep-slope areas.

Estimation of Forest Net Primary Production in Northeast China Using the Physiological Principles Predicting Growth Model Driven by Remote Sensing Data

Estimation of Forest Net Primary Production in Northeast China Using the Physiological Principles Predicting Growth Model Driven by Remote Sensing Data

Quantitative Assessment of Climate Change Impacts on Forest Ecosystems

Abstract Characterizing and predicting the response of terrestrial ecosystems to global change is part of the fundamental challenges of contemporary ecology and ecological conservation. The assessment of climate change impact on forest ecosystems has rarely used a multi-index fusion method for quantitative evaluation. We used forest distribution, net primary productivity, and vegetation coverage to establish an assessment model of the impact of climate change on forest ecosystems. We analyzed the change characteristics of these indicators in the Heilongjiang Province of China. Our results indicate the following: (1) from 2001 to 2019, the forest area in Heilongjiang Province ranged from 234,000 to 246,000 km2. The forest net primary productivity (NPP) ranged from 4.40 to 5.55 MgC·ha-1·yr-1, and the vegetation coverage ranged from 42.42% to 67.64%. The forest NPP and the vegetation coverage showed a significant upward trend. (2) The values of forest ecological roles were significantly positively correlated with the climatic potential. (3) The contribution rate of climate change to forest ecosystem change was negatively correlated with forest coverage, which varied from 4.79% to 18.07% in different regions (cities) of the province. Study Implications: Assessing the influence of climate on forest ecosystems comprehensively and accurately before the government prepares ecological measures is necessary. However, the responses of vegetation coverage and net primary productivity to climate change may not be consistent, so climate studies that consider forest ecosystem change trends by a single indicator may have confounding results. We established a model for evaluating the impact of climate change on forest ecosystems to solve this problem. This knowledge may provide a reference for the response, adaptation, and vulnerability assessment of forest ecosystems to climate change.

Simulating the Impacts of Drought and Warming in Summer and Autumn on the Productivity of Subtropical Coniferous Forests

The impacts of drought and/or warming on forests have received great attention in recent decades. Although the extreme drought and/or warming events significantly changed the forest demography and regional carbon cycle, the seasonality quantifying the impacts of these climate extremes with different severities on the productivity of subtropical coniferous forests remains poorly understood. This study evaluated the effects of seasonal drought and/or warming on the net primary productivity (NPP) of subtropical coniferous forests (i.e., Cunninghamia lanceolata and Pinus massoniana forests) from Hengyang–Shaoyang Basin in southern China using the Ecosystem Demography model, Version 2.2 (ED-2.2) and based on the datasets from forest inventory, meteorological reanalysis, and remotely sensed products. The results showed that the goodness of fit of the DBH-height allometric equations was better than that of the default in ED-2.2 after model calibration; the ED-2.2 model qualitatively captured the seasonality of NPP in the subtropical coniferous forests; and the mismatch between simulated annual NPP and MODIS-NPP (MOD17A3HGF) became smaller over time. The effect of seasonal drought on NPP was greater than that of warming; the decline rate of NPP gradually increased and decreased with time (from July to October) under the seasonal drought and warming scenarios, respectively; NPP decreased more seriously under the combined drought-warming scenario in October, with an average decrease of 31.72%, than the drought-only and warming-only scenarios; seasonal drought had an obvious legacy impact on productivity recovery of subtropical coniferous forests, but it was not the case for warming. With the increase in drought severity, the average values of soil available water and NPP together showed a downward trend. With the increase in warming severity, the average values of canopy air space temperature increased, but NPP decreased. Seasonal drought and/or warming limit forest production through decreasing soil moisture and/or increasing canopy air space temperature, which impact on plant photosynthesis and productivity, respectively. Our results highlight the significance of taking into account the impacts of seasonal warming and drought when evaluating the productivity of subtropical coniferous forests, as well as the significance of enhancing the resistance and resilience of forests to future, more severe global climate change.

Dynamics of forest net primary productivity based on tree ring reconstruction in the Tianshan Mountains

The lack of long-term high-resolution data makes it difficult to determine historical and future trends in net primary productivity (NPP). This study used tree rings as a proxy to investigate the dynamics of NPP in Tianshan forests where coniferous forests are the major species and the other species are deficient. All trees and some tree cores from five sample plots in different geographic locations in the western Tianshan Mountains were selected to reconstruct forest NPP data from 1950 to 2020. Multiple historical events that resulted in large-scale terrestrial carbon fluxes were identified and the existence of 28a and 17a time-scale cycles of historical forest NPP was observed. We discovered that the reconstructed forest NPP in the western Tianshan Mountains did not significantly correlate with satellite-based products (e.g., MODIS NPP, solar-induced chlorophyll fluorescence data). This result was attributed to the lag of forest growth for climate, the accuracy of the satellite-based products and statistical errors due to the short overlap time. We analysed the uncertainties in reconstructing historical forest NPP using tree ring widths and proposed corresponding solutions. We concluded that the reconstructed data remain the ideal proxy for regions lacking long-term empirical data and exhibit a high degree of confidence for expressing trends in forest productivity change over long time series.

Quantifying the effects of the ‘Internet plus Ecology’ framework on carbon sink in the digital age: a representative study of Ant Forest in China

Ecological afforestation is a positive measure to increase the absorption of carbon dioxide and curb global warming. Ant Forest, a successful example of an ‘Internet + voluntary tree planting’ gamified app with more than 500 million users, has contributed to substantial progress on ecological afforestation in China. It represents a new model of transforming the environmental awareness and low-carbon actions of users (e.g. walking, sharing bikes, and reducing plastics and papers) into actual environmental benefits via planting trees. The implications of Ant Forest can provide useful references for linking ecosystem restoration with the internet worldwide. However, the spatial distribution and quantitative effects on the carbon sink of Ant Forest on a finer scale are not fully understood. In this study, 588 Ant Forest blocks with a total area of 136 314 ha were identified based on area of interest data using the web crawler approach. The forest blocks involved 20 cities in 7 provinces and included 11 varieties of trees. More than 90% of these forest blocks were located in Inner Mongolia, Qinghai, and Gansu Provinces, and mostly shrubs were planted. Based on the Carnegie Ames Stanford approach model, the net primary productivity (NPP) of Ant Forest blocks was estimated. The simulated total annual NPP of all Ant Forest areas was 1.06 × 1011 gC, and an obvious increasing trend in NPP from 2016 to 2020 was observed, indicating effective carbon sequestration. We found that Hippophae rhamnoides and Caragana korshinskii had carbon sink advantages over other shrubs due to their higher NPP values per unit area. By strengthening individuals’ low-carbon awareness for reducing carbon emissions and increasing forest NPP to enhance the carbon sink, Ant Forest uses a representative and inspirational ‘Internet plus Ecology’ framework that has much significance for achieving carbon neutrality in China and tackling global climate change.

Responses of Forest Net Primary Productivity to Climatic Factors in China during 1982-2015.

Forest ecosystems play an important role in the global carbon cycle. Clarifying the large-scale dynamics of net primary productivity (NPP) and its correlation with climatic factors is essential for national forest ecology and management. Hence, this study aimed to explore the effects of major climatic factors on the Carnegie-Ames-Stanford Approach (CASA) model-estimated NPP of the entire forest and all its corresponding vegetation types in China from 1982 to 2015. The spatiotemporal patterns of interannual variability of forest NPP were illustrated using linear regression and geographic information system (GIS) spatial analysis. The correlations between forest NPP and climatic factors were evaluated using partial correlation analysis and sliding correlation analysis. We found that over thirty years, the average annual NPP of the forests was 887 × 1012 g C/a, and the average annual NPP per unit area was 650.73 g C/m2/a. The interannual NPP of the entire forest and all its corresponding vegetation types significantly increased (p < 0.01). The increase in the NPP of evergreen broad-leaved forests was markedly substantial among forest types. From the spatial perspective, the NPP of the entire forest vegetation gradually increased from northwest to southeast. Over the years, the proportions of the entire forest and all its corresponding vegetation types with a considerable increase in NPP were higher than those with a significant decrease, indicating, generally, improvements in forest NPP. We also found climatic factors variably affected the NPP of forests over time considering that the rise in temperature and solar radiation improved the interannual forest NPP, and the decline in precipitation diminished the forest NPP. Such varying strength of the relationship between the interannual forest NPP and climatic factors also varied across many forest types. Understanding the spatiotemporal pattern of forest NPP and its varying responses to climatic change will improve our knowledge to manage forest ecosystems and maintain their sustainability under a changing environment.