Search Results (50)

Atmospheric aerosols influence the terrestrial carbon cycle through diverse radiative and biogeochemical effects, yet their net impact on vegetation productivity remains contentious and region-specific. To address this, we analyzed the spatiotemporal coupling between aerosol optical depth (AOD) and net primary productivity (NPP) over three African biomes (2013–2023), using multi-source datasets (MODIS, CERES, ERA5, CRU TS). We explicitly distinguished statistically significant relationships (p < 0.05) from non-significant ones when interpreting correlation patterns. Because AOD is an optical measure and does not provide aerosol composition, interpretations involving dust versus smoke are treated as qualitative and indirect. Through structural equation modeling (SEM), we identified two contrasting mechanistic pathways: in the humid Congo Basin rainforest, aerosols were associated with lower NPP via a cooling-mediated pathway (increased cloud albedo leading to reduced temperature and light availability), whereas in the arid savanna, they were associated with more substantial limitations on NPP via a warming-aggravated pathway (increased temperature and potentially coupled water stress). SEM fit was poor for the semi-arid South African plateau, underscoring the dominant role of water availability in strongly water-limited systems. This framework reconciles the paradox of dual aerosol effects by demonstrating that the net impact is dictated by regional climate context. Overall, our conclusions emphasize context-dependent associations rather than direct causal attribution from correlations alone. Our findings provide a process-based understanding that is critical for improving carbon cycle models and for formulating targeted climate adaptation strategies in Africa. Full article

To ensure food security, integrated mulching and irrigation practices are widely used in arid maize fields. Mitigating climate change is vital for sustainable agricultural development. Yet, few studies have examined how different mulching and irrigation methods affect farmland carbon fluxes, particularly with maize variety shifts under policy guidance. In this study, we conducted experimental observations over five growing seasons using eddy covariance systems in maize fields (including seed maize fields and grain maize fields), where drip irrigation under plastic mulch (DM) and border irrigation under plastic mulch (BM) were employed in Northwest China. Results revealed that the multi-year mean gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration (ER) in maize fields under DM were 16.70%, 15.63% and 17.52% higher than those under BM, respectively. The changes in cumulative GPP, cumulative NEP and cumulative ER caused by the alteration of maize varieties were 7.64, 13.34 and 4.20 times, respectively, compared to the changes caused by the irrigation method. After mechanical harvesting, net biome productivity (NBP) was negative in seed maize fields but positive in grain maize fields. However, after the straws were returned to the fields, the NBP of both types of maize fields became positive. Interestingly, the carbon fluxes of seed maize and grain maize, respectively, exhibit strong dependence on soil temperature and leaf area index. Our study will provide important insights for the green and sustainable development of agriculture and the advancement of ecosystem models. Full article

In the current context of global warming, quantifying carbon fluxes between biosphere and atmosphere and identifying ecosystems as carbon sources or sinks is essential. The goal of this study is to quantify net carbon fluxes for the main forest types in peninsular Spain and characterize them as carbon sources or sinks. A hybrid methodology is proposed. First, net primary production (NPP) is obtained through machine learning using site properties, time metrics of meteorological series, and forest inventory data as inputs. The most accurate NPP estimates (R² ≥ 0.8 and relative RMSE ≤ 30%) were obtained by kernel ridge regression and gaussian process regression using latitude, elevation, time metrics of air temperature, precipitation and incoming solar radiation, and growing stock volume as inputs. Secondly, net ecosystem production (NEP) is obtained by subtracting heterotrophic respiration simulated by Biome-BGC from the previous NPP. All considered forest types presented small and mostly positive NPP and NEP values (greater for deciduous than for evergreen forests), thus generally acting as carbon sinks during the 2004–2018 period. Full article

Drought poses a severe threat to grassland biodiversity and ecosystem function. However, quantitative frameworks that capture the interactive effects of drought intensity and duration on productivity remain scarce, limiting impact assessment accuracy. To bridge this gap, we developed and validated a novel hybrid modeling framework to quantify drought impacts on net primary productivity (NPP) across Inner Mongolia’s major grasslands (1961–2012). Drought was characterized using the Standardized Precipitation Index (SPI), and ecosystem productivity was simulated with the Biome-BGC model. Our core innovation is the hybrid model, which integrates linear and nonlinear components to explicitly capture the compounded, nonlinear influence of combined drought intensity and duration. This represents a significant advance over conventional single-perspective approaches. Key results demonstrate that the hybrid model substantially outperforms linear and nonlinear models alone, yielding highly significant regression equations for all grassland types (meadow, typical, desert; all p < 0.001). Independent validation confirmed its robustness and high predictive skill (NSE ≈ 0.868, RMSE = 20.09 gC/m²/yr). The analysis reveals two critical findings: (1) drought duration is a stronger driver of productivity decline than instantaneous intensity, and (2) desert grasslands are the most vulnerable, followed by typical and meadow grasslands. The hybrid model serves as a practical tool for estimating site-specific productivity loss, directly informing grassland management priorities, adaptive grazing strategies, and early-warning system design. Beyond immediate applications, this framework provides a transferable methodology for assessing drought-induced vulnerability in biodiverse ecosystems, supporting conservation and climate-adaptive management. Full article

Terrestrial carbon sink has exhibited significant interannual variability (IAV) over the past five decades. However, the dominant regions and factors controlling the IAV of global land carbon sink remain controversial. Using six TRENDY models, we quantified regional contributions to the IAV of global land carbon sink from 1981 to 2017 and identified the dominant factors across different ecosystems and the globe. Results indicated that forests and savannas contributed most to global net biome productivity (NBP) IAV (27% and 29%, respectively). Further analyses revealed that root zone soil moisture (RZSM) and vapor pressure deficit (VPD) played a dominant role at the local and global scales, particularly in regions between 20° S and 40° S and 40° N–60° N. Across different ecosystems, the dominant drivers of NBP IAV varied greatly. More precisely, in tropical forests, NBP IAV was dominated by temperature variability, whereas in extra-tropical forests and croplands, VPD variability played a dominant role. Furthermore, in shrublands and grasslands, RZSM and VPD have comparable effects on NBP anomalies. Our findings provided robust evidence for an important joint control of RZSM and VPD in the IAV of land carbon sink, and reduced some of the uncertainty around the dominant drivers of temporal variability in NBP. Full article

Eucalyptus has become a major plantation crop in southern China, with a carbon sequestration capacity significantly higher than that of other species. However, its long-term carbon sequestration capacity and regional-scale potential remain highly uncertain due to commonly applied short-rotation management practices. The InTEC (Integrated Terrestrial Ecosystem Carbon) model is a process-based biogeochemical model that simulates carbon dynamics in terrestrial ecosystems by integrating physiological processes, environmental drivers, and management practices. In this study, the InTEC model was enhanced with an optimized eucalyptus module (InTEC_euc) and a data assimilation module (InTEC_DA), and driven by multiple remote sensing products (Net Primary Productivity (NPP) and carbon density) to simulate the carbon budgets of eucalyptus plantations from 2003 to 2023. The results indicated notable improvements in the performance of the InTEC_euc model when driven by different datasets: carbon density simulation showed improvements in R² (0.07–0.56), reductions in MAE (5.99–28.51 Mg C ha⁻¹), reductions in RMSE (8.1–31.85 Mg C ha⁻¹), and improvements in rRMSE (12.37–51.82%), excluding NPP_Lin. The carbon density-driven InTEC_euc model outperformed the NPP-driven model, with improvements in R² (0.28), MAE (−8.15 Mg C ha⁻¹), RMSE (−9.43 Mg C ha⁻¹), and rRMSE (−15.34%). When the InTEC_DA model was employed, R² values for carbon density improved by 0–0.03 (excluding ACD_Yan), with MAE reductions between 0.17 and 7.22 Mg C ha⁻¹, RMSE reductions between 0.33 and 12.94 Mg C ha⁻¹ and rRMSE improvements ranging from 0.51 to 20.22%. The carbon density-driven InTEC_DA model enabled the production of high-resolution and accurate carbon budget estimates for eucalyptus plantations from 2003 to 2023, with average NPP, Net Ecosystem Productivity (NEP), and Net Biome Productivity (NBP) values of 17.80, 10.09, and 9.32 Mg C ha⁻¹ yr⁻¹, respectively, offering scientific insights and technical support for the management of eucalyptus plantations in alignment with carbon neutrality targets. Full article

Forest–atmosphere interactions through mass and energy fluxes significantly influence climate processes. However, due to anthropogenic actions, native Araucaria forests in southern Brazil, part of the Atlantic Forest biome, have been drastically reduced. This study quantifies CO₂ and energy flux contributions from each forest stratum to improve understanding of surface–atmosphere interactions. Eddy covariance data from November 2009 to April 2012 were used to assess fluxes in an Araucaria forest in Paraná, Brazil, across the ecosystem, understory, and overstory strata. On average, the ecosystem acts as a carbon sink of −298.96 g C m⁻² yr⁻¹, with absorption doubling in spring–summer compared to autumn–winter. The understory primarily acts as a source, while the overstory functions as a CO₂ sink, driving carbon absorption. The overstory contributes 63% of the gross primary production (GPP) and 75% of the latent heat flux, while the understory accounts for 94% of the ecosystem respiration (RE). The energy fluxes exhibited marked seasonality, with higher latent and sensible heat fluxes in summer, with sensible heat predominantly originating from the overstory. Annual ecosystem evapotranspiration reaches 1010 mm yr⁻¹: 60% of annual precipitation. Water-use efficiency is 2.85 g C kgH₂O⁻¹, with higher values in autumn–winter and in the understory. The influence of meteorological variables on the fluxes was analyzed across different scales and forest strata, showing that solar radiation is the main driver of daily fluxes, while air temperature and vapor pressure deficit are more relevant at monthly scales. This study highlights the overstory’s dominant role in carbon absorption and energy fluxes, reinforcing the need to preserve these ecosystems for their crucial contributions to climate regulation and water-use efficiency. Full article

The exploitation of the Amazon biome in search of net profit, specifically in the production of cocoa (Theobroma cacao) and açaí (Euterpe oleracea), has caused deforestation, degradation of natural resources, and high greenhouse gas (GHG) emissions, highlighting the urgency of improving the environmental, economic and social sustainability of these crops. These species were selected for their rapid expansion in the Amazon, driven by global demand, their local economic relevance, and their potential to either promote conservation or drive deforestation, depending on the production system. This study analyzes the pillars of environmental, social, and economic sustainability of cocoa and açaí production systems in the Amazon, comparing monoculture, agroforestry, and extractivism to support forest conservation strategies in the biome. Analysis of the environmental life cycle, social life cycle, and economic performance were used to determine the carbon footprint, the final point of workers, and the net profit of the activities. According to the results found in this study, cocoa monoculture had the largest carbon footprint (1.35 tCO₂eq/ha), followed by agroforestry (1.20 tCO₂eq/ha), açaí monoculture (0.84 tCO₂eq/ha) and extractivism (0.25 tCO₂eq/ha). In the carbon balance, only the areas outside indigenous lands presented positive carbon. Regarding the economic aspect, the net profit of açaí monoculture was USD 6783.44/ha, extractivism USD 6059.42/ha, agroforestry USD 4505.55/ha, and cocoa monoculture USD 3937.32/ha. In the social sphere, in cocoa and açaí production, the most relevant negative impacts are the subcategories of child labor and gender discrimination, and the positive impacts are related to the sub-category of forced labor. These results suggest that açaí and cocoa extractivism, under responsible management plans, offer a promising balance between profitability and environmental conservation. Furthermore, agroforestry systems have also demonstrated favorable outcomes, providing additional benefits such as biodiversity conservation and system resilience, which make them a promising sustainable alternative. Full article

Elephants exhibit remarkable cognitive and social abilities, which are integral to their navigation, resource acquisition, and responses to environmental challenges such as climate change and human–wildlife conflict. Their capacity to acquire, recall, and utilise spatial information enables them to traverse large, fragmented landscapes, locate essential resources, and mitigate risks. While older elephants, particularly matriarchs, are often regarded as repositories of ecological knowledge, the mechanisms by which younger individuals acquire this information remain uncertain. Existing research suggests that elephants follow established movement patterns, yet direct evidence of intergenerational knowledge transfer is limited. This review synthesises current literature on elephant navigation and decision-making, exploring how their behavioural strategies contribute to resilience amid increasing anthropogenic pressures. Empirical studies indicate that elephants integrate environmental and social cues when selecting routes, accessing water, and avoiding human-dominated areas. However, the extent to which these behaviours arise from individual memory, social learning, or passive exposure to experienced individuals requires further investigation. Additionally, elephants function as ecosystem engineers, shaping landscapes, maintaining biodiversity, and contributing to climate resilience. Recent research highlights that elephants’ ecological functions can indeed contribute to climate resilience, though the mechanisms are complex and context-dependent. In tropical forests, forest elephants (Loxodonta cyclotis) disproportionately disperse large-seeded, high-carbon-density tree species, which contribute significantly to above-ground carbon storage. Forest elephants can improve tropical forest carbon storage by 7%, as these elephants enhance the relative abundance of slow-growing, high-biomass trees through selective browsing and seed dispersal. In savannah ecosystems, elephants facilitate the turnover of woody vegetation and maintain grassland structure, which can increase albedo and promote carbon sequestration in soil through enhanced grass productivity and fire dynamics. However, the ecological benefits of such behaviours depend on population density and landscape context. While bulldozing vegetation may appear destructive, these behaviours often mimic natural disturbance regimes, promoting biodiversity and landscape heterogeneity, key components of climate-resilient ecosystems. Unlike anthropogenic clearing, elephant-led habitat modification is part of a long-evolved ecological process that supports nutrient cycling and seedling recruitment. Therefore, promoting connectivity through wildlife corridors supports not only elephant movement but also ecosystem functions that enhance resilience to climate variability. Future research should prioritise quantifying the net carbon impact of elephant movement and browsing in different biomes to further clarify their role in mitigating climate change. Conservation strategies informed by their movement patterns, such as wildlife corridors, conflict-reducing infrastructure, and habitat restoration, may enhance human–elephant coexistence while preserving their ecological roles. Protecting older individuals, who may retain critical environmental knowledge, is essential for sustaining elephant populations and the ecosystems they influence. Advancing research on elephant navigation and decision-making can provide valuable insights for biodiversity conservation and conflict mitigation efforts. Full article

As an important component of the global carbon cycle, the variation patterns and driving mechanisms of the productivity and carbon sink capacity of subtropical forest ecosystems urgently need in-depth research. In this study, taking the forest ecosystem in the Ganjiang River Basin as the research object, the Biome-BGC model was used to simulate the forest productivity at different time scales (annual, seasonal, and monthly) from 1970 to 2021, and its spatio-temporal distribution characteristics and responses to climate change were analyzed. The results showed that the interannual net primary productivity (NPP) of evergreen broad-leaved forests was 771.4 g C m⁻² year⁻¹, that of evergreen coniferous forests was 631.6 g C m⁻² year⁻¹, that of deciduous coniferous forests was 610.5 g C m⁻² year⁻¹, and that of shrub forests was 262.8 g C m⁻² year⁻¹. Evergreen broad-leaved forests have greater carbon sink potential under the background of climate change. The forest productivity in the Ganjiang River Basin generally showed an upward trend, but there were obvious differences in spatial distribution, characterized by being higher in the surrounding mountainous areas and lower in the central and northern plains. The methodological framework proposed in this study is beneficial for productivity evaluation and spatio-temporal analysis of carbon balance in subtropical forest ecosystems and provides a scientific reference for model simulation and the application of forest productivity at the regional scale. Full article

Food production’s environmental, economic, and social challenges should be demystified through quantitative data. Therefore, the objective of this paper was to investigate the ecoregional sustainability of the Amazon biome from the perspective of the environmental life cycle, economic feasibility, and social life cycle analysis, emphasizing the pillars of sustainability in the production of three commodities: soybean, beef cattle, and Brazil nuts. Carbon footprint, net present value, and worker endpoint were the metrics evaluated. According to the results found in this study, the livestock presented greater environmental burdens in terms of carbon balance when compared to the production of Brazil nuts and soybean production with carbon balances in the order of 4.75 tCO₂eq/ha, −0.02 tCO₂eq/ha, and −1.20 tCO₂eq/ha, respectively. From an economic viewpoint, the extractive production of Brazil nuts presented the highest net profit per hectare/year (USD 559.21), followed by the agricultural system (USD 533.94) and livestock (USD 146.19). Finally, in relation to the social aspect of the production systems analyzed, the negative impacts linked to beef cattle production are related to the subcategories of forced labor and equal opportunities, and the positive impacts linked to soybean production are related to the subcategories of salary and benefits. The results highlight a genuine and sustainable balance in Brazil nuts extraction, presenting it as an investment for a sustainable future while demystifying the multifaceted information related to food production as a whole, in order to assist in decision-making and the formulation of public policies. Full article

A recently proposed modelling strategy predicts the net primary production (NPP) of forest ecosystems by combining the outputs of a NDVI-driven model, Modified C-Fix, and a bio-geochemical model, BIOME-BGC. This combination strategy takes into account the effects of forest disturbances but still assumes the presence of a mixture of differently aged trees. The application of this strategy to even-aged forests, therefore, requires a methodological advancement aimed at properly modifying the modelling of main ecosystem processes. In particular, the adaptation of the method to even-aged forests is based on the use of high-spatial-resolution airborne laser scanning (ALS) datasets, which yields green and woody biomass estimates that regulate the simulation of photosynthetic and respiratory processes, respectively. This approach was experimented in a Mediterranean study area, San Rossore Regional Park (Central Italy), which is covered by even-aged pine stands in different development phases. The modelling strategy is driven by MODIS NDVI images and meteorological data across five years (2011–2015), which are combined with estimates of forest canopy cover and height obtained from ALS data taken in 2015. This allows the production of stand NPP estimates, which, when converted into respective current annual increment (CAI) values, reasonably reproduce the age dependency of the available ground observations. The CAI estimates also show a highly significant correlation with these observations (r = 0.773) and moderate error levels (RMSE = 2.03 m³ ha⁻¹ year⁻¹, MBE = −0.45 m³ ha⁻¹ year⁻¹). These results confirm the potential of the modified simulation method to yield accurate high-spatial-resolution NPP estimates, which can offer valuable insights into C cycling and storage, in even-aged forests. Full article

Biotic stress in cotton plants caused by the phytopathogenic fungus Colletotrichum gossypii var. cephalosporioides triggers symptoms of ramulosis, a disease characterized by necrotic spots on young leaves, followed by death of the affected branch’s apical meristem, plant growth paralysis, and stimulation of lateral bud production. Severe cases of ramulosis can cause up to 85% yield losses in cotton plantations. Currently, this disease is controlled exclusively by using fungicides. However, few studies have focused on biological alternatives for mitigating the effects of contamination by C. gossypii var. cephalosporioides on cotton plants. Thus, the hypothesis raised is that endophytic fungi isolated from an Arecaceae species (Butia purpurascens), endemic to the Cerrado biome, have the potential to reduce physiological damage caused by ramulosis, decreasing its severity in these plants. This hypothesis was tested using plants grown from seeds contaminated with the pathogen and inoculated with strains of Gibberella moniliformis (BP10EF), Hamigera insecticola (BP33EF), Codinaeopsis sp. (BP328EF), G. moniliformis (BP335EF), and Aspergillus sp. (BP340EF). C. gossypii var. cephalosporioides is a leaf pathogen; thus, the evaluations were focused on leaf parameters: gas exchange, chlorophyll a fluorescence, and oxidative metabolism. The hypothesis that inoculation with endophytic strains can mitigate physiological and photochemical damage caused by ramulosis in cotton was confirmed, as the fungi improved plant growth and stomatal index and density, increased net photosynthetic rate (A) and carboxylation efficiency (A/Ci), and decreased photochemical stress (ABS/RC and DI₀/RC) and oxidative stress by reducing enzyme activity (CAT, SOD, and APX) and the synthesis of malondialdehyde (MDA). Control plants developed leaves with a low adaxial stomatal index and density to reduce colonization of leaf tissues by C. gossypii var. cephalosporioides due to the absence of fungal antagonism. The Codinaeopsis sp. strain BP328EF can efficiently inhibit C. gossypii var. cephalosporioides in vitro (81.11% relative inhibition), improve gas exchange parameters, reduce photochemical stress of chlorophyll-a, and decrease lipid peroxidation in attacked leaves. Thus, BP328EF should be further evaluated for its potential effect as a biological alternative for enhancing the resistance of G. hirsutum plants and minimizing yield losses caused by C. gossypii var. cephalosporioides. Full article

The Brazilian Pampa biome has natural pastures that have been used for centuries for cattle grazing. This is considered a sustainable system because it combines the conservation of natural vegetation and high-quality meat production, protecting the biome from commercial agriculture’s advances. However, whether it is a source or a sink of carbon dioxide (CO₂) has yet to be evaluated. Hence, this study aimed to quantify the net ecosystem exchange (NEE) of the CO₂ of a natural pasture of the Pampa biome used for livestock production. The experimental area is located in a subtropical region of southern Brazil, where eddy covariance (EC) measurements were conducted from 2015 to 2021 in a rotational cattle grazing system. The seven months of the warm season (September to March) were characterized as CO₂ absorbers, while the five months of the cold season (April to August) were CO₂ emitters. Throughout the six years and with complete data, the ecosystem was an absorber of atmospheric CO₂, with an average value of −207.6 g C m⁻² year⁻¹. However, the significant interannual variability in NEE was observed, with cumulative values ranging from −82.0 to −385.3 g C m⁻² year⁻¹. The results suggest the coupling of climatic conditions to pasture management can be the factor that modulated the NEE interannual variability. The cattle raising system on the natural pastures of the Pampa absorbs CO₂, which is further evidence of its sustainability and need for conservation. Full article

Subtropical forests have strong carbon sequestration potential; however, the spatiotemporal patterns of their carbon sink are unclear. The BIOME-BGC model is a powerful tool for forest carbon sink estimation while the numerous parameters, as well as the localization, limit their application. This study takes three typical subtropical forests (evergreen broadleaf forest, EBF; evergreen needleleaf forest, ENF; and bamboo forest, BF) in China as examples, assesses the sensitivity of 43 ecophysiological parameters in the BIOME-BGC model both by the Morris method and the extended Fourier amplitude sensitivity test (EFAST), and then evaluates the net ecosystem productivity (NEP) estimation accuracy based on the dataset of the fiveFi long-term carbon flux sites of those three typical forests from 2000 to 2015. The results showed that (1) both sensitivity analysis methods can effectively screen out important parameters affecting NEP simulation while the Morris method is more computationally efficient and the EFAST is better in the quantitative evaluation of sensitivity. (2) The highly sensitive parameters obtained using the two methods are basically the same; however, their importance varies across sites and vegetation types, e.g., the most sensitive parameters are k for the EBF and ENF and R_act25 for the BF, respectively. (3) The optimized parameters successfully improved the NEP simulation accuracy in subtropical forests, with average correlation coefficients increased by 25.19% and normalized root mean square error reduced by 21.74% compared with those simulated by original parameters. This study provides a theoretical basis for the optimization of process model parameters and important technical support for accurate NEP simulations of subtropical forest ecosystems. Full article