Identifying the Relative Contributions of Climate and Grazing to Both Direction and Magnitude of Alpine Grassland Productivity Dynamics from 1993 to 2011 on the Northern Tibetan Plateau

Feng, Ying; Wu, Jianshuang; Zhang, Jing; Zhang, Xianzhou; Song, Chunqiao

doi:10.3390/rs9020136

Cited by 26 publications

(18 citation statements)

References 38 publications

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“…() ignored the compensation effect due to grazing. The proportion of grassland productivity consumed by livestock should also be taken into consideration when applying remote sensing‐based models to simulate alpine grassland NPP under the impact of climate change and human activities (Feng et al., ). Based on previous research (Chen et al., ; Haberl et al., ), Pan et al.…”

Section: Causes Of Attribution Differences Across the Tibetan Plateaumentioning

confidence: 99%

“…Based on this fixed framework, Feng et al. () selected the northern Tibetan Plateau as a case study region to evaluate the variation in NPP gap and its positive or negative value to indicate vegetation dynamics, that is, restoration or degradation.…”

Section: Causes Of Attribution Differences Across the Tibetan Plateaumentioning

confidence: 99%

“…However, uncertainties even controversies exist among the conclusions of such studies. Distinguishing the respective impact of climate change and human activities on alpine grassland dynamic remains challenges (Feng, Wu, Zhang, Zhang, & Song, ; Wang, Zhang, et al., ; Zhang, Yang, et al., ), and till date no study has comprehensively reviewed these challenges. In this study, we review the methods for identifying the driving factors in variations of alpine grassland productivity at various scales, and the main conclusions.…”

Section: Introductionmentioning

confidence: 99%

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Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau

Zhang

Liu

et al. 2018

Ecology and Evolution

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Quantifying the impact of climate change and human activities on grassland dynamics is an essential step for developing sustainable grassland ecosystem management strategies. However, the direction and magnitude of climate change and human activities in driving alpine grassland dynamic over the Tibetan Plateau remain under debates. Here, we systematically reviewed the relevant studies on the methods, main conclusions, and causes for the inconsistency in distinguishing the respective contribution of climatic and anthropogenic forces to alpine grassland dynamic. Both manipulative experiments and traditional statistical analysis show that climate warming increase biomass in alpine meadows and decrease in alpine steppes, while both alpine steppes and meadows benefit from an increase in precipitation or soil moisture. Overgrazing is a major factor for the degradation of alpine grassland in local areas with high level of human activity intensity. However, across the entire Tibetan Plateau and its subregions, four views characterize the remaining controversies: alpine grassland changes are primarily due to (1) climatic force, (2) nonclimatic force, (3) combination of anthropogenic and climatic force, or (4) alternation of anthropogenic and climatic force. Furthermore, these views also show spatial inconsistencies. Differences on the source and quality of remote sensing products, the structure and parameter of models, and overlooking the spatiotemporal heterogeneity of human activity intensity contribute to current disagreements. In this review, we highlight the necessity for taking the spatiotemporal heterogeneity of human activity intensity into account in the models of attribution assessment, and the importance for accurate validation of climatic and anthropogenic contribution to alpine grassland variation at multiple scales for future studies.

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Section: Causes Of Attribution Differences Across the Tibetan Plateaumentioning

confidence: 99%

Section: Causes Of Attribution Differences Across the Tibetan Plateaumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau

Zhang

Liu

et al. 2018

Ecology and Evolution

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“…Therefore, the difference between PNPP and ANPP (PNPP-ANPP) is used to define human-induced NPP (HNPP) [28,32]. Thus, vegetation growth variations can be determined at a pixel scale by comparing the temporal variations of PNPP, ANPP, and HNPP [33].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Impacts of Anthropogenic Activities and Climate Variations on Vegetation Productivity Changes in China from 1985 to 2015

et al. 2020

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Accurate assessment of vegetation dynamics provides important information for ecosystem management. Anthropogenic activities and climate variations are the major factors that primarily influence vegetation ecosystems. This study investigates the spatiotemporal impacts of climate factors and human activities on vegetation productivity changes in China from 1985 to 2015. Actual net primary productivity (ANPP) is used to reflect vegetation dynamics quantitatively. Climate-induced potential net primary productivity (PNPP) is used as an indicator of climate change, whereas the difference between PNPP and ANPP is considered as an indicator of human activities (HNPP). Overall, 91% of the total vegetation cover area shows declining trends for net primary productivity (NPP), while only 9% shows increasing trends before 2000 (base period). However, after 2000 (restoration period), 78.7% of the total vegetation cover area shows increasing trends, whereas 21.3% of the area shows decreasing trends. Moreover, during the base period, the quantitative contribution of climate change to NPP restoration is 0.21 grams carbon per meter square per year (gC m−2 yr−1) and to degradation is 2.41 gC m−2 yr−1, while during the restoration period, climate change contributes 0.56 and 0.29 gC m−2 yr−1 to NPP restoration and degradation, respectively. Human activities contribute 0.36 and 0.72 gC m−2 yr−1 during the base period, and 0.63 and 0.31 gC m−2 yr−1 during the restoration period to NPP restoration and degradation, respectively. The combined effects of climate and human activities restore 0.65 and 1.11 gC m−2 yr−1, and degrade 2.01 and 0.67 gC m−2 yr−1 during the base and restoration periods, respectively. Climate factors affect vegetation cover more than human activities, while precipitation is found to be more sensitive to NPP change than temperature. Unlike the base period, NPP per unit area increases with an increase in the human footprint pressure during the restoration period. Grassland has more variability than other vegetation classes, and the grassland changes are mainly observed in Tibet, Xinjiang, and Inner Mongolia regions. The results may help policy-makers by providing necessary guidelines for the management of forest, grassland, and agricultural activities.

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“…Long term trends in biomass production are also critical in understanding the mechanism, direction and magnitude of climatic effects. Feng et al [59] simulated potential productivity and actual productivity using Remote Sensing as well as climatic and anthropogenic data sets in Northern Tibetan Plateau between 1993 and 2011. Their results showed the importance of precipitation in regulating Net Primary Productivity.…”

Section: Summary Of Papers Published In This Special Issuementioning

confidence: 99%

Remote Sensing of Above-Ground Biomass

2017

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Accurate measurement and mapping of biomass is a critical component of carbon stock quantification, climate change impact assessment, suitability and location of bio-energy processing plants, assessing fuel for forest fires, and assessing merchandisable timber. While above-ground biomass includes both live and dead plant material, most of the recent research effort on biomass estimation has focussed on the 'live' component (live trees) due to the prominence of this component. Accurate estimates of biomass is a prerequisite for better understanding of the impacts of deforestation and environmental degradation on climate change.The Intergovernmental Panel on Climate Change (IPCC) [1] has listed five terrestrial ecosystem carbon pools involving biomass: above-ground biomass, below-ground biomass, litter, woody debris and soil organic matter. Of these five, above-ground biomass is the most visible, dominant, dynamic and important pool of the terrestrial ecosystem, constituting around 30% of the total terrestrial ecosystem carbon pool. Above-ground biomass estimation, and especially forest biomass, has received considerable attention over the last few decades because of increased awareness of climate warming and the role forest biomass plays in carbon sequestration and release of greenhouse gases due to deforestation.Above-ground biomass estimates are the central basis for carbon inventories and most international negotiations in carbon trading schemes. Carbon trading markets require long-term information on carbon stocks, particularly on the above-ground 'live' biomass component as this is the most dynamic, changing and manipulable component of all the biomass pools. This is the 'merchantable' component of biomass.Above-ground forest biomass accounts for between 70% to 90% of total forest biomass [2]. While soil organic matter holds two to three times more carbon than biomass on a global scale, much of the soil carbon is more protected and not easily oxidised [3]. On the other hand, above-ground biomass is in a continuous state of flux due to fire, logging, storms, landuse changes, etc., and thus contributes to atmospheric carbon fluxes to a much greater extent and so is of much greater interest. Due to this dynamism of above-ground biomass, it is necessary to monitor it continuously and not measure once and forget.While detailed estimations of biomass is necessary for accurate carbon accounting, reliable estimation methods are few. Accurate estimates of stored carbon (biomass as dry weight is 50% carbon [4] and understanding sources and sinks can improve the accuracy of carbon flux models and thus lead to better projections of climate change and impacts. Initiatives such as Reducing Emissions from Deforestation and Forest Degradation (REDD) and REDD+ also rely heavily on above-ground biomass estimates [5,6]. REDD+ includes financing schemes and incentives with the aim of mitigating climate change by reducing deforestation and forest degradation through sustainable forest management and conservation, and enhancement...

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Identifying the Relative Contributions of Climate and Grazing to Both Direction and Magnitude of Alpine Grassland Productivity Dynamics from 1993 to 2011 on the Northern Tibetan Plateau

Cited by 26 publications

References 38 publications

Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau

Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau

Quantifying the Impacts of Anthropogenic Activities and Climate Variations on Vegetation Productivity Changes in China from 1985 to 2015

Remote Sensing of Above-Ground Biomass

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