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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. [ABSTRACT FROM AUTHOR]

In the context of strengthening the construction of ecological civilization and accelerating the "carbon peak" in China, the regional ecological pattern and its connection with carbon sink capacity have become an urgent topic. Given that Inner Mongolia is a large carbon emission province and the conflict between economic development and ecological protection is particularly prominent, we took Inner Mongolia as an example to extract its ecospatial network, then calculated the integrity index, topological indices, and recovery robustness of the network and evaluated integrity and other properties of the ecospatial network structure by combining them with the ecological background. In addition, we analyzed the relationship between the topological indices and net primary productivity (NPP). The results showed that the network was scale-free and heterogeneous, with low integrity, connectivity and stability, which were the focus of future optimization. The nodes with important functions were mainly distributed in the farm-forest ecotone, grasslands, and the agro-pastoral ecotone; under the simulation attack, the node recovery robustness was stronger than the corridor recovery robustness, and NPP was negatively and significantly correlated with the woodland nodes and grassland nodes. In terms of ecological restoration, the unused land in the west is a key area, and it is necessary to add new ecological nodes and corridors. In terms of enhancing carbon sequestration capacity, under the premise of ensuring network connectivity, the appropriate and rational merging of ecological nodes and corridors within woodlands and grasslands is a particularly effective means. This study provides a reference for evaluating and optimizing the ecological pattern of areas with prominent ecological problems and improving the carbon sink of ecosystems in terms of their ecospatial network structure. [ABSTRACT FROM AUTHOR]

Vegetation Net Primary Productivity (NPP) plays a crucial role in terrestrial carbon sinks and the global carbon cycle. Investigating the spatiotemporal dynamics and influencing factors in the Yangtze River Delta (YRD) region can furnish a solid scientific foundation for green, low-carbon, and sustainable development in China, as well as a reference for other rapidly urbanizing regions. This study focuses on the YRD region as an illustration and utilizes the Carnegie–Ames–Stanford Approach (CASA model) to quantify NPP in this region from 2000 to 2018. Investigation into the spatiotemporal dynamics and influencing factors was conducted using Theil–Sen median trend analysis and scenario analysis. The results indicate that the NPP in the YRD region from 2000 to 2018 exhibited pronounced spatial differentiation characteristics, typically exhibiting a spatial distribution pattern of being high in the south and low in the north, high in the west and low in the east. Additionally, the expansion of built-up areas and the reduction in cultivated land have the potential to reduce NPP in the YRD region. Moreover, the influence of land-use and land-cover change (LULCC) is anticipated to be relatively limited compared to that of climate change. Furthermore, changes in precipitation were found to be positively correlated with changes in NPP, with the effect being relatively more pronounced. The correlation between temperature and NPP demonstrated spatial differentiation, with a mainly positive correlation in the central and southern parts of the YRD and a mainly negative correlation in the northern part. Changes in solar radiation had a negative correlation with changes in NPP. Based on these results, it is recommended that local governments strictly enforce urban development boundaries and manage the disorderly expansion of built-up areas, enhance the regional irrigation infrastructure, and address air pollution, so as to ensure the necessary conditions for the growth of vegetation, reduce greenhouse gas emissions, and control regional temperature rises. This study can provide stronger evidence for revealing the influencing mechanisms of NPP through the control of impact conditions and the exclusion of confounding factors via scenario analysis. The policy implications can offer insights into NPP enhancement and environmental management for the YRD and other rapidly urbanizing regions. [ABSTRACT FROM AUTHOR]

Accurately estimating vegetation productivity is important in the research of terrestrial ecosystems, carbon cycles and climate change. Although several gross primary production (GPP) and net primary production (NPP) products have been generated and many algorithms developed, advances are still needed to exploit multi-scale data streams for producing GPP and NPP with higher spatial and temporal resolution. In this paper, a method to generate high spatial resolution (30 m) GPP and NPP products was developed based on multi-scale remote sensing data and a downscaling method. First, high resolution fraction photosynthetically active radiation (FPAR) and leaf area index (LAI) were obtained by using a regression tree approach and the spatial and temporal adaptive reflectance fusion model (STARFM). Second, the GPP and NPP were estimated from a multi-source data synergized quantitative algorithm. Finally, the vegetation productivity estimates were validated with the ground-based field data, and were compared with MODerate Resolution Imaging Spectroradiometer (MODIS) and estimated Global LAnd Surface Satellite (GLASS) products. Results of this paper indicated that downscaling methods have great potential in generating high resolution GPP and NPP. [ABSTRACT FROM AUTHOR]

Unveiling the variation mechanism of vegetation net primary productivity (NPP) and elucidating the underlying drivers of these changes is highly necessitated for terrestrial carbon cycle research and global carbon emission control. Taking Henan Province, renowned as the anciently central China and current China's foremost grain producer, as an example, this study employed the Theil–Sen Median Trend Analysis to evaluate the spatiotemporal characteristics and trends of NPP. Correlation Analysis and Residual Analysis were used to explain the drivers of NPP dynamics. To deepen the inquiry, the Geodetector method was employed to scrutinize the multifaceted effects and interplay among diverse variables influencing NPP. The result showed demonstrated that approximately 85.72% of the area showed an increase in NPP, covering a broad geographical distribution. Notably, 89.31% of the province has witnessed a positive human-driven NPP change. It means human activities emerged as a driving force with a positive effect on vegetation NPP, consequently fostering an increasing trend of NPP. Among climatic factors, the correlation between NPP and precipitation was stronger than that between the temperature and NPP, the determined power of factors in Henan Province was population density, (0.341) > GDP (0.326) > precipitation (0.255) > elevation (0.167) > slope (0.136) > temperature (0.109), and a single factor had a lesser interaction effect than two factors. The implications of these findings extend beyond the realms of research, potentially offering valuable insights into the formulation of targeted ecosystem restoration measures tailored to the distinct context of Henan Province, and also expect to provide crucial references for carbon emission control in China and across the world. [ABSTRACT FROM AUTHOR]

Vegetation net primary productivity (NPP) is critical to maintaining and enhancing the carbon sink of vegetation. Shaoguan is a characteristic forest city in the subtropical region of South China and an ecological barrier in the Guangdong–Hong Kong–Macau Greater Bay Area (GBA), playing an instrumental role in protecting water resources, purifying air, and maintaining ecological balance. However, studies that quantify subtropical vegetation NPP dynamics in Shaoguan under the influence of climate and human drivers are still incomplete. In this research, vegetation NPP at 30 m resolution was estimated from 2001 to 2020 using the enhanced CASA model based on the GF-SG algorithm in Shaoguan. The RESTREND method was then utilized to quantify climatic and human effects on NPP. The results indicated that the vegetation NPP in Shaoguan increased rapidly (4.09 g C/m2/yr, p < 0.001) over the past 20 years. Climate and human drivers contributed 0.948 g C/m2/yr and 3.137 g C/m2/yr to vegetation NPP, respectively. Human activity plays a major role in vegetation restoration through ecological projects, whereas vegetation deterioration is primarily attributable to the combined action of climate change and human activity, such as urban expansion, deforestation, and meteorological disasters. The results emphasize the importance of ecological projects for the restoration of vegetated ecosystems and ecological construction in Shaoguan. [ABSTRACT FROM AUTHOR]

Background: Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types. Results: Continental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship. Conclusion: Observed significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available. [ABSTRACT FROM AUTHOR]

Urbanization has profoundly altered the terrestrial ecosystem carbon cycle, especially the net primary productivity (NPP). Many attempts have been made to assess the influence of urbanization on NPP at coarse resolutions (e.g., 250 m or larger), which may ignore many smaller and highly fragmented urban lands, and to a large extent, underestimate the NPP variations induced by urban sprawl. Hence, we attempted to analyze the NPP variations influenced by urban sprawl at a fine resolution (e.g., 30 m), toward which the accuracy of NPP was improved using remotely sensed data fusion algorithm. In this paper, this assumption was tested in the Pearl River Delta of China. The land cover datasets from the Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM +) were acquired to quantify the urban sprawl. The synthetic Normal Differential Vegetation Index (NDVI) data was obtained by fusing Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI via spatiotemporal fusion algorithm. The Carnegie-Ames-Stanford Approach (CASA) model was driven by land cover map, synthetic NDVI and meteorological data to estimate the 30-m resolution NPP. Then, we analyzed the influence of urban sprawl on 30-m resolution NPP during the period of 2001–2009. Additionally, we also simulated the spatiotemporal change of future urban sprawl under different scenarios using the Future Land Use Simulation (FLUS) model, and further analyzed its influence on 30-m resolution NPP. Our results showed that the accuracy of 30-m resolution NPP from synthetic NDVI is better than 500-m resolution NPP from MODIS NDVI. The loss in 30-m resolution NPP due to urban sprawl was much higher than 500-m resolution NPP. Moreover, the harmonious development scenario, characterized by a reasonable size of urban sprawl and a corresponding lower NPP loss from 2009 to 2050, would be considered as a more human-oriented and sustainable development strategy. [ABSTRACT FROM AUTHOR]

Monitoring changes in the terrestrial carbon cycle and vegetation health can only be undertaken over large areas and on a regular basis using ecological indicators derived from satellite-based sensors. Climate conditions in Mediterranean ecosystems have undergone, and are projected to undergo, significant change in the future with marked impacts on forest and shrubland vegetation. In the southwest of Australia (SWAU), endemic tree species have experienced significant declines in health and mortality since the early 1990s primarily due to these climatic changes. In this paper we examine trends in Net Primary Production (NPP) from 2000 to 2011 as an indicator of productivity and health condition of the woody vegetation across the SWAU region. To do so, we examine NPP estimates derived from satellite imagery and climate data to answer the questions: (1) what is the extent and rate of change in NPP for the SWAU region over the study period, and (2) how important is fire as a contributing factor in the observed trends? Our results suggest that, similar to the global trend in Mediterranean ecosystems, between 2000 and 2011, overall NPP declined across the study region, with the majority of declines occurring in the ecological transition zone between trees and shrubs. Twenty-six percent of the 37,042 square kilometre of woody vegetation that showed a declining NPP trend, was affected by fire. The overall rate of NPP decline for the region was estimated to be −0.38 megaton C per year since 2000, indicating a reduction in the capacity of the region to act as a carbon sink. Under climate change projections, the observed decline trends are likely to continue and our results suggest that the carbon storage potential in this region is gradually decreasing following an ecological shift from tall tree-dominated to lower shrub-dominated vegetation. [ABSTRACT FROM AUTHOR]

The terrestrial ecosystem carbon cycle is essential to the global carbon cycle. Mining activities have seriously damaged the terrestrial ecosystem and destroyed the carbon sequestration ability of vegetation, which is of great significance to studying the effect of coal mining on land structure change and carbon sink function in cities and mining areas. However, the existing research lacks the targeted analysis of the carbon sink level of the mining area combined with the mining data. Based on the coal-mining information, land-use data, and MODIS NPP data, this study analyzed the spatio-temporal change characteristics of land use and NPP in Huainan City and its mining areas from 2001 to 2020. The results showed that: (1) 22.5% of the land types in the mining area have changed, much higher than 3.2% in Huainan; 40.08 km2 of the cropland in the mining area has been transformed into waterbodies, seriously affecting regional food security. (2) NPP fluctuates with rainfall, has a weak correlation with temperature, and is restricted by coal-mining factors. The average NPP of most coal mines is significantly lower than that of non-mining areas. The NPP of Huainan City showed an overall growth trend of 2.20 g/(m2 × a), which was much higher than the average value of 0.43 g/(m2 × a) in the mining area. Especially in the Guqiao mine, the difference in NPPslope before and after mining was as high as 16.92 g/(m2 × a). (3) The probability integral method was used to estimate that 195.16 km2 of land in Huainan would be damaged by mining in 2020. The distribution of damage degree was negatively correlated with NPPslope, which meant the more serious the damage was, the less NPPslope was. This study revealed the characteristics of land-use change and NPP spatio-temporal response in resource-based cities and mining-disturbed areas. It quantitatively estimated the impact of mining activities on regional carbon sink function. It can provide theory and data support for mining areas to carry out ecological protection and restoration, improve the environmental service function of resource-based cities, and formulate sustainable development strategies. [ABSTRACT FROM AUTHOR]

• The net primary productivity (NPP) significantly increased in marshes of study area. • Summer daytime and nighttime temperatures had an asymmetric effect on marsh NPP. • Increased precipitation in summer and autumn can enhance the NPP of marsh vegetation. The western Songnen Plain has a large area of marshes that are able to modulate the regional carbon cycle. Net primary productivity (NPP) is an important ecological indicator of carbon storage within the marsh ecosystems. Although climate change could have significantly changed marsh vegetation NPP during the past decades, the spatiotemporal variation in marsh vegetation NPP and how climate change affects marsh vegetation NPP remain unclear in the western Songnen Plain. In this paper, we assessed the spatiotemporal variation in the NPP of marshes at the western Songnen Plain and evaluated its response to climate change from 2000 to 2020. The NPP of marshes over the western Songnen Plain increased significantly at a rate of 5.69 g C/m2/a during 2000 to 2020, with an average value of about 273.62 g C/m2/a. The largest increase of the NPP of marshes was mainly distributed in the northwest part of the Songnen Plain. Correlation analysis results showed that the increased precipitation in summer and autumn could enhance the NPP of marsh vegetation. By contrast, the increase of mean temperature in summer reduced the NPP of marshes. In addition, we first found the asymmetric impacts of summer minimum temperature (T min) and maximum temperature (T max) on marsh vegetation NPP. Notably, the increase in summer T max could significantly reduce NPP, while the increase in T min could increase NPP. Under the background of global asymmetric warming of daytime and nighttime temperatures, more attention should be paid to the different effects of T max and T min on marsh NPP in the western Sonegnen Plain. The findings of this study can provide theoretical guidance for ecological protection and the adaptive management of marsh vegetation at the western Songnen Plain. [ABSTRACT FROM AUTHOR]

Yearly changes in tropical carbon‐cycling have been a major biotic determinant of the interannual variation in the rise of atmospheric carbon dioxide ([CO2]). The environmental responses underlying these changes remain poorly understood. A 21‐year field study (1997–2018) in a Costa Rican rainforest has produced the first multi‐decade record of landscape‐scale annual aboveground productivity for a tropical ecosystem. While none of the four production components (wood production; leaf‐, twig‐, and reproductive litterfall) increased over two decades, all significantly varied among years. Multi‐factor environmental models explained a large fraction of the inter‐year changes in two production components. Annual changes in three climatic factors and [CO2] jointly accounted for 84% of the variation in annual wood production. While the strongest response of wood production was to decline in years of slightly warmer nights, it also significantly declined in years with more dry‐season hours hotter than 28°C. The yearly changes in reproductive litterfall were largely (52%) determined by the combined effects of increasing [CO2] and declining annual radiation. Twig litterfall declined over the 21 years. Annual leaf litterfall, the largest component of field‐assessed aboveground production, showed no significant environmental responses. An extreme storm in the study's final year disrupted the environmental controls on production that prevailed through the prior 20 years. While important uncertainties are introduced by some of the field methods for assessing aboveground forest production, the findings of this first long‐term field study of annual landscape‐scale productivity raise deep concerns for the future of tropical forests as global warming proceeds. Plain Language Summary: The rate at which carbon dioxide (CO2) is increasing in the atmosphere is determined both by humans (fossil‐fuel emissions, deforestation) and by how the natural world processes CO2. The yearly increases in atmospheric CO2 have been significantly affected by tropical ecosystems. Changes in the balance between their uptake of huge amounts of CO2 through photosynthesis and their also very large CO2 emissions through respiration have been affecting the rate of accumulation of atmospheric CO2. Through two decades we studied annual plant productivity, the net result of photosynthesis and plant respiration, in a tropical rainforest. We found that tree growth (=wood production) declined with slightly hotter nights and when more daytime hours were above the optimum temperature for photosynthesis. Also, the expected benefits for forest productivity from the increase in atmospheric CO2 were quite limited. While both wood production and tree reproductive litterfall positively responded to the increase in atmospheric CO2, most of aboveground productivity did not. No productivity component increased over the two decades. Together these findings raise the prospect of declining tropical‐forest productivity as global warming intensifies. This would in turn speed up the rate of increase of CO2 in our atmosphere, a positive feedback to warming. Key Points: Interannual productivity changes dominated by negative temperature impactsMost of aboveground productivity unresponsive to increasing carbon dioxideDisruption of environmental controls by an extreme storm [ABSTRACT FROM AUTHOR]

Changes to the carbon cycle in tropical forests could affect global climate, but predicting such changes has been previously limited by lack of field-based data. Here we show seasonal cycles of the complete carbon cycle for 14, 1 ha intensive carbon cycling plots which we separate into three regions: humid lowland, highlands, and dry lowlands. Our data highlight three trends: (1) there is differing seasonality of total net primary productivity (NPP) with the highlands and dry lowlands peaking in the dry season and the humid lowland sites peaking in the wet season, (2) seasonal reductions in wood NPP are not driven by reductions in total NPP but by carbon during the dry season being preferentially allocated toward either roots or canopy NPP, and (3) there is a temporal decoupling between total photosynthesis and total carbon usage (plant carbon expenditure). This decoupling indicates the presence of nonstructural carbohydrates which may allow growth and carbon to be allocated when it is most ecologically beneficial rather than when it is most environmentally available. [ABSTRACT FROM AUTHOR]

Vegetation is an important part of the environment but may be subjected to disturbance in areas close to coal mines. This results in a slowing of the rate of biomass growth, which is caused by fading of vegetation. Simultaneously, carbon stored in vegetation is constantly released, weakening vegetation ability to act as a carbon sink. Indirect release of carbon during coal mining processes is difficult to measure and is often neglected in carbon accounting. In this work, these measurements are performed for a real case study. Within the study area, factors that affect vegetation were divided into: natural factors; human surface activities; and coal mining, with each of these directly reflected in the spatial and temporal variation of the Normalized Difference Vegetation Index (NDVI). To clarify the relationship between coal mining and local vegetation damage, high spatial-temporal resolution remote sensing images were created using the spatial and temporal adaptive reflectance fusion model. Data showing the mine coalface and the variation of vegetation at Xinzhouyao coal mine allowed identification of influential factors. Quantized synthetic effect values of NDVI from coal mining and changes in local climate were then evaluated. Using a theoretical analysis of carbon released from vegetation, the net primary productivity (NPP) and biomass loss of vegetation were calculated. Results showed that fluctuations in vegetation NDVI as a response to changes in local climate were positively correlated with the average NDVI value. Vegetation disturbance caused by coal mining leads to loss of biomass and decreases the ability of vegetation to absorb atmospheric CO. From 2001 to 2010, loss of vegetation biomass owing to coal mining was 2,608.48 t with annual rates of biomass loss of 33.48 gC/m year. Over the same period, the amount of atmospheric carbon absorbed by vegetation was reduced by 1,925.23 t with annual vegetation NPP loss of 24.71 gC/m year. Comparing these figures with the amount of coal produced, this calculates the carbon release from vegetation owing to coal mining at Xinzhouyao coal mine as 77.568 g/t. Because much of the carbon in lost biomass is recycled to the soil, the biggest impact on the carbon balance of vegetation near coal mines may be attributed to a reduced ability to absorb atmospheric CO. These results may be useful for further analysis of the impact of mining on local environments and for the calculation of appropriate ecological compensation. [ABSTRACT FROM AUTHOR]

This study compares different approaches to quantifying the carbon cycle in a temperate deciduous forest at Wytham Woods in England, which is unusual in its maritime climate and mixed age structure, reflecting low levels of past management. We tested whether eddy covariance and biometric measurements gave consistent estimates of woodland productivity and ecosystem respiration at monthly and annual timescales. Biometric methods estimated gross primary productivity (GPP) as 22.0 ± 1.6 Mg C ha y, close to the eddy covariance GPP value of 21.1 Mg C ha y. Annual ecosystem respiration ( R) was similar, at 20.3 ± 1.5 Mg C ha y for biometric and 19.8 Mg C ha yfor eddy covariance. The seasonal cycle of monthly biometric and eddy covariance R estimates also closely matched. Net primary productivity (NPP) was 7.0 ± 0.8 Mg C ha y, 37% of which was allocated below ground. Leaf fluxes were the greatest component of NPP and R. Ecosystem carbon-use efficiency (CUE = NPP/GPP) was 0.32 ± 0.04; low compared to many temperate broadleaved sites but close to values for old-growth sites. This may reflect the age of some trees, and/or the oceanic climate with relatively mild winters during which there can be substantial autotrophic maintenance respiration in winter but negligible growth. This study demonstrates that biometric measurements can provide robust estimates of site productivity and respiration and that eddy covariance and bottom-up measurements can be combined on seasonal and interannual timescales to enable a detailed understanding of the forest carbon cycle. [ABSTRACT FROM AUTHOR]

Land cover is a crucial component in assessment of biodiversity and ecosystem services. In arid regions, land cover is mostly composed of aeolian structures which exhibit fragile environmental scenario. The major challenge in this highly dynamic landscape was conversion of desertic land to intensive land use such as agricultural farmlands. To overcome this challenge Indira Gandhi Canal (IGC) and its branches were extended over this district. The main interest of this research was to investigate net primary productivity (NPP) changes using multi-temporal satellite imagery and meteorological datasets within the timeframe of 30 years from 1982 to 2012 over this region. This study was taken up to assess the impact of canal in and around IGC command area in Jaisalmer District to understand the consequence on desertic environment. Analysis of three decades terrestrial NPP over IGC command area in Jaisalmer District, India, shows significant increase in NPP. The satellite data-based analysis of NPP as well as validation with the optical data in the study region revealed that this increasing trend in NPP is basically associated to increase in canal networks. The water supply from the canal gradually led to expansion of irrigation in the agricultural fields leading to change in dynamics of the area. This systematic and long-term NPP analysis will be useful to strengthen our understanding for the role of regional land cover types and impact of their change in the national and global carbon cycle for understanding land degradation and desertification scenario in the study area. [ABSTRACT FROM AUTHOR]