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Climate Impacts on Sustainable Natural Resource Management


Climate Impacts on Sustainable Natural Resource Management


1. Aufl.

von: Pavan Kumar, Ram Kumar Singh, Manoj Kumar, Meenu Rani, Pardeep Sharma

168,99 €

Verlag: Wiley-Blackwell
Format: PDF
Veröffentl.: 15.11.2021
ISBN/EAN: 9781119793380
Sprache: englisch
Anzahl Seiten: 384

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Beschreibungen

<b>CLIMATE IMPACTS ON SUSTAINABLE NATURAL RESOURCE MANAGEMENT</b> <p>Climate change has emerged as one of the predominant global concerns of the 21<sup>st</sup> century. Statistics show that the average surface temperature of the Earth has increased by about 1.18°C since the late 19<sup>th</sup> century and the sea levels are rising due to the melting of glaciers. Further rise in the global temperature will have dire consequences for the survival of humans on the planet Earth. There is a need to monitor climatic data and associated drivers of changes to develop sustainable planning. The anthropogenic activities that are linked to climate change need scientific evaluation and must be curtailed before it is too late. <p>This book contributes significantly in the field of sustainable natural resource management linked to climate change. Up to date research findings from developing and developed countries like India, Indonesia, Japan, Malaysia, Sri Lanka and the USA have been presented through selected case studies covering different thematic areas. The book has been organised into six major themes of sustainable natural resource management, determinants of forest productivity, agriculture and climate change, water resource management and riverine health, climate change threat on natural resources, and linkages between natural resources and biotic-abiotic stressors to develop the concept and to present the findings in a way that is useful for a wide range of readers. While the range of applications and innovative techniques is constantly increasing, this book provides a summary of findings to provide the updated information. <p>This book will be of interest to researchers and practitioners in the field of environmental sciences, remote sensing, geographical information system, meteorology, sociology and policy studies related to natural resource management and climate change.
<p>About the Editors xiii</p> <p>List of Contributors xv</p> <p>Foreword xxi</p> <p>Preface xxii</p> <p><b>Section I Sustainable Natural Resource Management 1</b></p> <p><b>1 Impact of Local REDD+ Intervention on Greenhouse Gas Emissions in East Kalimantan Province, Indonesia 3<br /> </b><i>Kiswanto, Martiwi Diah Setiawati, and Satoshi Tsuyuki</i></p> <p>1.1 Introduction 3</p> <p>1.1.1 Tropical Deforestation 3</p> <p>1.1.2 REDD+ 3</p> <p>1.1.3 REDD+ in Indonesia 4</p> <p>1.2 Materials and Methods 5</p> <p>1.2.1 Spatial Dataset 5</p> <p>1.2.2 Carbon Stock in Each Land Cover Class 5</p> <p>1.2.3 Change in Carbon Stock and CO2 Emission 7</p> <p>1.2.4 Historical Baselines and Future Trajectories 7</p> <p>1.3 Results 8</p> <p>1.3.1 Annual GHG Emissions 8</p> <p>1.3.2 Historical Baselines and Future Trajectories 9</p> <p>1.4 Discussion 10</p> <p>1.5 Conclusions 12</p> <p>Acknowledgement 12</p> <p>Author Contribution 12</p> <p>List of Appendix 13</p> <p>References 14</p> <p><b>2 Role of Geospatial Technologies in Natural Resource Management 19</b><i><br /> Abhishek K. Kala and Manoj Kumar</i></p> <p>2.1 Introduction 19</p> <p>2.2 Applications of Geospatial Technology in Natural Resource Management 20</p> <p>2.2.1 Forest Management 20</p> <p>2.2.2 Water Resource Management 21</p> <p>2.2.3 Water Quality Monitoring 22</p> <p>2.2.4 Agriculture 23</p> <p>2.2.5 Combating Desertification 25</p> <p>2.2.6 Biodiversity Management 25</p> <p>2.3 LiDAR Technology 26</p> <p>2.4 Artificial Intelligence and Remote Sensing 26</p> <p>2.5 Machine Learning Tools for Natural Resource Management 27</p> <p>2.6 Applications of Unmanned Aerial Systems in Natural Resource Management 28</p> <p>2.7 Google Earth Engine as a Platform for Environmental Monitoring and NRM 29</p> <p>2.8 Conclusion 29</p> <p>References 30</p> <p><b>3 Estimation of Snow Cover Area Using Microwave SAR Dataset 35</b><i><br /> Shafiyoddin B. Sayyad and Mudassar A. Shaikh</i></p> <p>3.1 Introduction 35</p> <p>3.2 Classification Technique 36</p> <p>3.2.1 Unsupervised Classification 36</p> <p>3.2.1.1 H A Alpha Unsupervised Classification 36</p> <p>3.2.1.2 Wishart H A Alpha Unsupervised Classification 37</p> <p>3.2.2 Supervised Classification 37</p> <p>3.2.2.1 Wishart Supervised Classification 38</p> <p>3.2.2.2 Support Vector Machine (SVM) Supervised Classification 38</p> <p>3.3 Statistical Parameters 39</p> <p>3.3.1 Mean 39</p> <p>3.3.2 Standard Deviation 40</p> <p>3.3.3 Coefficient Variance 40</p> <p>3.3.4 Equivalence Number of Looks (ENL) 40</p> <p>3.4 Error and Accuracy Assessment 40</p> <p>3.4.1 Confusion Matrix 41</p> <p>3.4.2 Commission Error 41</p> <p>3.4.3 Omission Error 42</p> <p>3.5 Study Area 42</p> <p>3.6 Methodology 43</p> <p>3.7 Result and Discussion 44</p> <p>3.8 Conclusion and Future Perspective 52</p> <p>References 52</p> <p><b>Section II Determinants of Forest Productivity 57</b></p> <p><b>4 Forest Cover Change Detection Across Recent Three Decades in Persian Oak<br /> Forests Using Convolutional Neural Network 59<br /> </b><i>Alireza Sharifi, Shilan Felegari, Aqil Tariq, and Saima Siddiqui</i></p> <p>4.1 Introduction 59</p> <p>4.2 Materials and Methods 61</p> <p>4.2.1 Study Area 61</p> <p>4.2.2 Dataset 61</p> <p>4.2.3 Image Pre-processing 64</p> <p>4.2.4 Image Classification 64</p> <p>4.3 Results and Discussion 65</p> <p>4.4 Conclusion and Future Prospects 68</p> <p>References 69</p> <p><b>5 The Interlinked Mechanisms of Productivity for Developing Process-Based<br /> Forest Growth Models 74<br /> </b><i>Keshav Tyagi, Manoj Kumar, Sweta Nisha Phukon, Abhishek Ranjan, Pavan Kumar,</i><i>and Ram Kumar Singh</i></p> <p>5.1 Introduction 74</p> <p>5.2 Productivity: Definition and Associated Components 76</p> <p>5.3 Various Processes and Components Driving Forest Productivity 77</p> <p>5.3.1 Photosynthesis 78</p> <p>5.3.2 Light Interception 79</p> <p>5.3.3 Stomatal Conductance 79</p> <p>5.3.4 Leaf Area Index 79</p> <p>5.3.5 Gas-Exchange 80</p> <p>5.3.6 Plant Respiration 80</p> <p>5.3.7 Hydrology 81</p> <p>5.3.8 Nitrogen Cycle 81</p> <p>5.3.9 Litterfall 81</p> <p>5.4 Different Approaches to Productivity Assessment 82</p> <p>5.5 Evolution of Process-Based Models 83</p> <p>5.6 Conclusion 84</p> <p>References 84</p> <p><b>6 Allometric Equations for the Estimation of Biomass and Carbon in the Sub- tropical Pine Forests of India 89<br /> </b><i>Harshi Jain, Keshav Tyagi, Akshay Paygude, Pavan Kumar, Ram Kumar Singh, and</i><i>Manoj Kumar</i></p> <p>6.1 Introduction 89</p> <p>6.1.1 Species of Pine in India and its Associates 91</p> <p>6.1.2 Uses of Chirpine 91</p> <p>6.2 Chir Pine – a Boon or Bane? 92</p> <p>6.3 Forest Carbon and Forest Biomass 93</p> <p>6.4 Composition of Forest Biomass 94</p> <p>6.4.1 Indian Forest Biomass and Carbon Estimates 94</p> <p>6.4.2 Importance of Forest Biomass Estimation 95</p> <p>6.5 Allometric Equations for Biomass Estimation 96</p> <p>6.5.1 How Are Allometric Equations Developed? 96</p> <p>6.6 Biomass and Carbon Stock Estimation in Chir Pine Forests of India Using Allometric Equations 97</p> <p>6.7 Conclusion 101</p> <p>References 102</p> <p><b>Section III Agriculture and Climate Change 109</b></p> <p><b>7 Characterization of Stress-Prone Areas for Dissemination of Suitable Rice Varieties and their Adoption in Eastern India: An Integrated Approach toward Food Security 111<br /> </b><i>Sk Mosharaf Hossain, Devi Dayal Sinha, and Swati Nayak</i></p> <p>7.1 Introduction 111</p> <p>7.1.1 Characterization of Stress-Prone (Flood and Drought) Areas in Eastern India: Geo-Spatial Based Studies (Submergence and Drought) 112</p> <p>7.1.2 Eastern India (Submergence Study – Assam) 114</p> <p>7.1.3 Eastern India (Drought Study – Uttar Pradesh) 115</p> <p>7.1.4 Rice-Growing Environments in India and Constraints 116</p> <p>7.1.5 Abiotic Stress in the Context of Rice Production 117</p> <p>7.2 Materials and Method (for Submergence-prone: Assam) 118</p> <p>7.3 Results and Discussion 120</p> <p>7.4 Conclusions 127</p> <p>References 128</p> <p><b>8 Farmers’ Perspective and Adaptation Efforts to Tackle the Impacts of Climate Change 132<br /> </b><i>Shivani Mehta and Shridhar Samant</i></p> <p>8.1 Introduction 132</p> <p>8.2 Methodology 135</p> <p>8.3 Results and Analysis 137</p> <p>8.3.1 Trends in Rainfall Patterns 137</p> <p>8.3.1.1 Trends in Annual Rainfall 137</p> <p>8.3.1.2 Trends in Rainy Days 140</p> <p>8.3.1.3 Trends in Actual and Normal (Expected) Rainfall for Every Month 144</p> <p>8.3.2 Impact of Climate Change on Farmers 148</p> <p>8.3.2.1 Demographic Profile of the Respondents 148</p> <p>8.3.2.2 Livelihood 148</p> <p>8.3.2.3 Pests and Diseases 149</p> <p>8.4 Understanding the Farmer’s Perception of Climate Change 149</p> <p>8.5 Adaptation Efforts 150</p> <p>8.6 Conclusion 151</p> <p>References 152</p> <p><b>Section IV Water Resource Management and Riverine Health 157</b></p> <p><b>9 Multicriteria Drought Severity Analysis in Monaragala District Sri Lanka by Utilizing Remote Sensing and GIS 159<br /> </b><i>K.U.J. Sandamali, K.A.M. Chathuranga, B.A.S.C. Kumara, and D.K.D.A. Ranaweera</i></p> <p>9.1 Introduction 159</p> <p>9.2 Methodology 162</p> <p>9.2.1 Study Area 162</p> <p>9.2.2 Data Sources and Data Collection Techniques 163</p> <p>9.3 Meteorological Drought of Monaragala District 164</p> <p>9.4 Agricultural Drought of Monaragala District 167</p> <p>9.4.1 Normalized Difference Vegetation Index (NDVI) 167</p> <p>9.4.2 Vegetation Condition Index (VCI) 167</p> <p>9.5 Hydrological Drought of Monaragala District 169</p> <p>9.6 Drought Risk Area Map of Monaragala District 173</p> <p>9.7 Conclusion and Recommendations 177</p> <p>9.8 Conclusion 177</p> <p>9.9 Recommendation 179</p> <p>References 180</p> <p><b>10 Comparative Evaluation of Predicted Hydrologic Response Under Two Extremities of Sustainability Using Transformed Landuse-Landcover and CORDEX-Based Climatic Scenarios: A Case Study of Kangshabati River Basin, West Bengal 183<br /> </b><i>Shreyashi Santra Mitra, Akhilesh Kumar, Abhisek Santra, and Shidharth Routh</i></p> <p>10.1 Introduction 183</p> <p>10.2 A Brief Account of the Kangshabati River Basin, the Study Area 185</p> <p>10.3 Data and Methodological Description 187</p> <p>10.3.1 Model Data Input 187</p> <p>10.3.2 Land Change Scenarios Using Idrisi Land Change Modeler (LCM) 190</p> <p>10.3.3 SWAT Model Setup for Simulating Hydrologic Responses 194</p> <p>10.4 Results and Observations 195</p> <p>10.4.1 Trends in Climatic Indicators 195</p> <p>10.4.2 Trends in Land Use and Land Cover Change Scenarios 198</p> <p>10.4.3 Trends in Volumetric Runoff 204</p> <p>10.4.4 Trends in Surface Runoff 209</p> <p>10.5 Conclusion 214</p> <p>References 215</p> <p><b>11 Riverine Health a Function of Riverscape Variable: A Case Study of the River Ganga in Varanasi 219<br /> </b><i>Shikha Sharma, Harshith Clifford Prince, Arijit Roy, and Madhoolika Agarwal</i></p> <p>11.1 Introduction 219</p> <p>11.2 Material and Methods 222</p> <p>11.2.1 Study Area 222</p> <p>11.2.1.1 Sampling Zones 222</p> <p>11.2.1.2 Survey Sites 222</p> <p>11.2.2 Data Collection 223</p> <p>11.2.2.1 Water Sample Collection and Analysis 223</p> <p>11.2.2.2 Survey Method 224</p> <p>11.2.3 Statistical Analysis 224</p> <p>11.2.3.1 Cluster Analysis 224</p> <p>11.2.3.2 Correlations Between Land Use Classes and Water Quality Parameters 225</p> <p>11.3 Result and Discussion 225</p> <p>11.3.1 Land Use and Water Quality 225</p> <p>11.3.2 Land Use and Biodiversity 227</p> <p>11.3.3 Land Use and Societal Perceptions 228</p> <p>11.3.3.1 Livelihood Earners Perceptions 228</p> <p>11.3.3.2 Tourists’ Perception 229</p> <p>11.4 Conclusions 231</p> <p>References 231</p> <p><b>Section V Climate Change Threat on Natural Resources 237</b></p> <p><b>12 Socio-Economic Impacts of Climate Change 239<br /> </b><i>Shubhi Patel, Anwesha Dey, Shani Kumar Singh, Rakesh Singh, and H.P. Singh</i></p> <p>12.1 Introduction 239</p> <p>12.2 Trends in Climate Variables 240</p> <p>12.3 Welfare Impact of Climate Change 242</p> <p>12.4 Impact on Agriculture 244</p> <p>12.5 Impact of Climate Change on Society 246</p> <p>12.5.1 Food Security 246</p> <p>12.5.2 Labor Productivity 247</p> <p>12.5.3 Health and Nutrition 248</p> <p>12.5.4 Adaptation Risk and Potential 248</p> <p>12.6 Conclusion 262</p> <p>References 263</p> <p><b>13 The Political Economy of Vulnerable Environment in the Age of Climate Change: A Kerala Experience 268<br /> </b><i>P. RatheeshMon</i></p> <p>13.1 Introduction 268</p> <p>13.2 Climate Change in Kerala 269</p> <p>13.3 Climate and Sea Level Change Projections 270</p> <p>13.4 Natural Disasters Associated with Climate Change 270</p> <p>13.5 The Political Economy of Climate Change and Associated Disasters 273</p> <p>13.6 Who Are the Affected? 275</p> <p>13.7 Conclusion and Suggestions 276</p> <p>References 276</p> <p><b>14 Land Use/Land Cover (LULC) Changes in Cameron Highlands, Malaysia: Explore the Impact of the LULC Changes on Land Surface Temperature (LST) Using Remote Sensing 279<br /> </b><i>Mohd Hasmadi Ismail, Darren How Jin Aik, Mohamad Azani Alias, Farrah Melissa</i><i>Muharam, and Pakhriazad Hassan Zaki</i></p> <p>14.1 Introduction 279</p> <p>14.2 Effectiveness of Usage of Satellite Imagery in Land Use/Land Cover (LULC) Change 281</p> <p>14.3 The Impact of LULC Changes on Land Surface Temperature (LST) 282</p> <p>14.4 Methodology 283</p> <p>14.4.1 Cameron Highlands 283</p> <p>14.4.2 Data Collection 284</p> <p>14.4.3 Field Verification 284</p> <p>14.4.4 Image Processing 285</p> <p>14.5 Land Use/Cover Changes in Cameron Highland from 2009 to 2019 287</p> <p>14.5.1 Accuracy Assessment 290</p> <p>14.6 Land Surface Temperature Analysis of Comparative Sensors between Landsat Satellite Data and MODIS 291</p> <p>14.7 The LULC Effect on LST in Cameron Highlands 292</p> <p>14.8 Conclusions 296</p> <p>References 297</p> <p><b>Section VI Linkages between Natural Resources and Biotic-Abiotic Stressors 303</b></p> <p><b>15 Emerging Roles of Osmoprotectants in Alleviating Abiotic Stress Response Under Changing Climatic Conditions 305<br /> </b><i>Debasish Pattnaik, Deepali Dash, Ankita Mishra, Aditya Kiran Padhiary, Prajjal Dey,</i><i>and Goutam Kumar Dash</i></p> <p>15.1 Introduction 305</p> <p>15.2 Role of Osmoprotectant Under Abiotic Stress 306</p> <p>15.3 Role of Osmoprotectants Under Drought Stress 306</p> <p>15.4 Role of Osmoprotectants Under Salinity Stress 307</p> <p>15.5 Role of Osmoprotectants Under Cold Stress 307</p> <p>15.6 Role of Osmoprotectants Under Submergence Stress 308</p> <p>15.7 Role of Osmoprotectants Under Low Light Stress 308</p> <p>15.8 Mechanisms of Osmoprotectants Under Multiple Abiotic Stress 309</p> <p>15.9 Approaches to Improve Osmoprotectants to Confer Abiotic Stress Tolerance 313</p> <p>15.10 Metabolic Engineering Approach 315</p> <p>15.11 Future Prospect for Osmoprotectants Under Changing Climatic Conditions 316</p> <p>References 316</p> <p><b>16 Growth Variability of Conifers in Temperate Region of Western Himalayas 325</b><i><br /> Ufaid Mehraj, Akhlaq Amin Wani, Aasif Ali Gatoo, Mohammd Ajaz-ul-Islam, Shah Murtaza Mushtaq, Amir Farooq, Immad Ahmad Shah, and Tariq Hussain Masoodi</i></p> <p>16.1 Introduction 325</p> <p>16.2 Material and Methods 326</p> <p>16.2.1 Study Area 326</p> <p>16.2.2 Collection of Core Samples 326</p> <p>16.3 Results 328</p> <p>16.4 Discussion 332</p> <p>16.4.1 Species-Wise 332</p> <p>16.4.2 Site-Wise 332</p> <p>16.4.3 Diameter Class-Wise 333</p> <p>16.5 Conclusion 333</p> <p>References 334</p> <p><b>17 Process-Based Carbon Sequestration Study with Reference to the Energy-Water-Carbon Flux in a Forest Ecosystem 336<br /> </b><i>Hukum Singh</i></p> <p>17.1 Introduction 336</p> <p>17.2 Concept of Soil-Vegetation-Atmosphere- Transfer (SVAT) 338</p> <p>17.3 History of Flux Measurements and Recent Advances-Different Methods 339</p> <p>17.4 Exchange Flux Measurements over Forest Ecosystems 340</p> <p>17.4.1 Fast Response System: Eddy Covariance or Eddy Correlation Measurements 341</p> <p>17.4.2 Slow-Response System 341</p> <p>17.4.2.1 Bowen Ratio Measurements 341</p> <p>17.4.2.2 Aerodynamic Flux Profile Method 342</p> <p>17.5 Ecosystem Flux Measurements Network Worldwide and Indian Scenario 343</p> <p>17.5.1 The Worldwide Network: The FLUXNET 343</p> <p>17.5.2 Scenario in India and Prospects 344</p> <p>17.5.3 The Proposed Concept of IndoFlux 345</p> <p>17.6 State of the Current Knowledge at Forest Research Institute, Dehradun 345</p> <p>17.7 Research Gaps and Future Needs 346</p> <p>17.8 Conclusion 347</p> <p>References 347</p> <p>Index 352</p>
<p>About the Editors</p> <p><b>Dr Pavan Kumar</b> has more than 7 years’ experience in the field of remote sensing, forest monitoring, agricultural resource management and climate change. <p><b>Dr Ram Kumar Singh</b> has more than 12 years of experience in the field of remote sensing, data dynamic modelling, machine learning for various applications related to natural resource management. <p><b>Dr Manoj Kumar</b> is a senior scientist working in the field of forestry, environment and climate change to test and apply the computational tools and techniques of simulation, modelling, remote sensing and GIS. <p><b>Dr Meenu Rani </b>is a research scholar working in the field of remote sensing and water resource management. <p><b>Dr Pardeep Sharma</b> has more than 5 years’ experience in the field of climate change.
<p>Climate change has emerged as one of the predominant global concerns of the 21<sup>st</sup> century. Statistics show that the average surface temperature of the Earth has increased by about 1.18°C since the late 19<sup>th</sup> century and the sea levels are rising due to the melting of glaciers. Further rise in the global temperature will have dire consequences for the survival of humans on the planet Earth. There is a need to monitor climatic data and associated drivers of changes to develop sustainable planning. The anthropogenic activities that are linked to climate change need scientific evaluation and must be curtailed before it is too late.</p> <p>This book contributes significantly in the field of sustainable natural resource management linked to climate change. Up to date research findings from developing and developed countries like India, Indonesia, Japan, Malaysia, Sri Lanka and the USA have been presented through selected case studies covering different thematic areas. The book has been organised into six major themes of sustainable natural resource management, determinants of forest productivity, agriculture and climate change, water resource management and riverine health, climate change threat on natural resources, and linkages between natural resources and biotic-abiotic stressors to develop the concept and to present the findings in a way that is useful for a wide range of readers. While the range of applications and innovative techniques is constantly increasing, this book provides a summary of findings to provide the updated information. <p>This book will be of interest to researchers and practitioners in the field of environmental sciences, remote sensing, geographical information system, meteorology, sociology and policy studies related to natural resource management and climate change.

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