Regional Sustainability ›› 2023, Vol. 4 ›› Issue (4): 425-440.doi: 10.1016/j.regsus.2023.11.005
• Full Length Article • Previous Articles Next Articles
WU Fana, LIANG Youjiaa,*(), LIU Lijunb, YIN Zhangcaia, HUANG Jiejuna
Received:
2023-04-27
Revised:
2023-09-13
Accepted:
2023-11-20
Published:
2023-12-30
Online:
2024-01-09
Contact:
* E-mail address: yjliang@whut.edu.cn (LIANG Y.J.).WU Fan, LIANG Youjia, LIU Lijun, YIN Zhangcai, HUANG Jiejun. Identifying eco-functional zones on the Chinese Loess Plateau using ecosystem service bundles[J]. Regional Sustainability, 2023, 4(4): 425-440.
Table 1
Data sources for the integrated assessment of ecosystem services (ESs) on the Chinese Loess Plateau from 2000 to 2015."
Data | Resolution | Year | Source |
---|---|---|---|
Temperature, sunshine duration, and precipitation | Daily | 2000-2015 | National Meteorological Information Centre ( |
Digital elevation model (DEM) | 90 m×90 m | Geospatial Data Cloud ( | |
Potential evapotranspiration (PET) | 1 km×1 km, yearly | 2000-2015 | Harvard Dataverse V1 ( |
Annual grain yield | 1 km×1 km, yearly | 2000-2015 | Agricultural Survey Division, National Bureau of Statistics ( |
Gross domestic product (GDP) | 1 km×1 km, yearly | 2000-2015 | Resources and Environmental Sciences and Data Centre ( |
Land use/land cover (LULC) | 300 m×300 m, yearly | 2000-2015 | European Space Agency (ESA) Climate Change Initiative (CCI) ( |
Leaf area index (LAI) | 30″×30″ | 2000-2015 | Land-Atmosphere Interaction Research Group, Sun Yat-sen University ( |
Normalized difference vegetation index (NDVI) | 1 km×1 km, monthly | 2000-2015 | Resources and Environmental Sciences and Data Centre ( |
Population map | 1 km×1 km, yearly | 2000-2015 | Resources and Environmental Sciences and Data Centre ( |
Soil data | 1 km×1 km | Harmonized World Soil Database V1.2 ( |
Table 2
Indicators of ES selected in this study."
ES function | ES indicator | Parameters used in the calculation of ES value |
---|---|---|
Provisioning services | Grain production | County grain yield and NDVI |
Raw material provision | Net primary productivity (NPP) and standard coal price | |
Regulating services | Water conservation | Flow velocity coefficient, topographic index, soil saturated hydraulic conductivity, and LULC |
Carbon storage | Carbon density and LULC | |
Soil conservation | Rainfall erosivity, soil erodibility, length-slope factor, vegetation cover, and retention factors | |
Oxygen production | NPP | |
Cultural service | Recreation | Grain production, vegetation coverage, and NPP |
Supporting service | NPP | Photosynthetically available radiation and light energy utilization rate |
Fig. 4.
Spatial distribution of LULC change on the Chinese Loess Plateau from 2000 to 2015. (a), 2000-2005; (b), 2005-2010; (c), 2010-2015. It should be noted that this figure only shows the main LULC changes occurring on the Chinese Loess Plateau from 2000 to 2015, while the minor LULC changes are represented aggregately by “Others” with black block."
Fig. 6.
Spatial distribution of each ES and total ESs on the Chinese Loess Plateau in 2000 and 2015 and the change of total ESs from 2000 to 2015. (a), grain production service in 2000; (b), raw material provision service in 2000; (c), water conservation service in 2000; (d), carbon storage service in 2000; (e), soil conservation service in 2000; (f), oxygen production service in 2000; (g), recreation service in 2000; (h), NPP service in 2015; (i), grain production service in 2015; (j), raw material provision service in 2015; (k), water conservation service in 2015; (l), carbon storage service in 2015; (m), soil conservation service in 2015; (n), oxygen production service in 2015; (o), recreation service in 2015; (p), NPP service in 2015; (q), total ESs in 2000; (r), total ESs in 2015; (s), change of total ESs from 2000 to 2015."
Fig. 7.
Mean value of each ES on the Chinese Loess Plateau in 2000, 2005, 2010, and 2015. (a), grain production service; (b), raw material provision service; (c), water conservation service; (d), carbon storage service; (e), soil conservation service; (f), oxygen production service; (g), recreation service; (h), NPP service. The red dashed line indicates the trend of variation, the black point represents the mean value of ES of each city (county or banner or district) on the Chinese Loess Plateau. The upper line of green box is the three-quarter quantile, representing 25.0% of data are above this value; while the lower line is the quarter quantile line, representing 25.0% of data are below this value."
Fig. 8.
Variation tendency of each ES and total ESs of different land use types on the Chinese Loess Plateau from 2000 to 2015. (a), grain production service; (b), raw material provision service; (c), water conservation service; (d), carbon storage service; (e), soil conservation service; (f), oxygen production service; (g), recreation service; (h), NPP service; (i), total ESs."
Fig. 9.
Correlation coefficients between ESs on the Chinese Loess Plateau in 2000 (a) and 2015 (b). GP, grain production service; RMP, raw material provision service; WC, water conservation service; CS, carbon storage service; SC, soil conservation service; OP, oxygen production service; REC, recreation service. * represents significance at the P≤0.01 level and ** represents significance at the P≤0.001 level. Blue circle represents synergistic relationship, while orange circle represents trade-off relationship. The size of the circle represents the degree of trade-off or synergy; the larger the circle, the greater the degree."
Fig. 13.
Result of principal component analysis (PCA) on the influencing factors of ESBs. The direction of arrow indicates the orientation of principal component (PC), representing the direction in which the data exhibit the greatest variation. The length of arrow represents the weight or importance of the PC. A longer arrow signifies a stronger explanatory power of the PC."
Table 3
Results of principal component analysis (PCA) for the influencing factors of ecosystem service bundles (ESBs)."
Factor | Factor loading | ||
---|---|---|---|
Principal component 1 (PC1) | Principal component 2 (PC2) | Principal component 3 (PC3) | |
DEM | 0.895 | 0.095 | -0.164 |
Temperature | -0.893 | 0.128 | 0.204 |
Proportion of cropland | -0.717 | 0.299 | 0.038 |
Proportion of ecological land | 0.690 | -0.602 | -0.047 |
Slope | 0.596 | 0.686 | -0.075 |
Sunshine duration | 0.529 | -0.754 | -0.140 |
Precipitation | -0.295 | 0.838 | 0.100 |
Population | -0.256 | 0.142 | 0.912 |
GDP | -0.132 | 0.032 | 0.961 |
Potential evapotranspiration | 0.032 | 0.941 | -0.008 |
Proportion of urban land | -0.002 | -0.037 | 0.958 |
Table 4
Linear combination coefficients and weights of ESB influencing factors."
Factor category | Factor | Eigenvalue | Linear combination coefficient | Weight (%) | ||
---|---|---|---|---|---|---|
PC1 | PC2 | PC3 | ||||
Topography | DEM | 0.417 | 0.059 | 0.115 | 0.249 | 9.9 |
Slope | 0.278 | 0.423 | 0.053 | 0.270 | 10.7 | |
Climate | Sunshine duration | 0.247 | 0.464 | 0.099 | 0.277 | 11.0 |
Temperature | 0.416 | 0.079 | 0.144 | 0.261 | 10.3 | |
Potential evapotranspiration | 0.015 | 0.580 | 0.006 | 0.174 | 6.9 | |
Precipitation | 0.138 | 0.516 | 0.070 | 0.231 | 9.2 | |
Land use | Proportion of cropland | 0.334 | 0.184 | 0.027 | 0.224 | 8.9 |
Proportion of ecological land | 0.322 | 0.371 | 0.033 | 0.273 | 10.8 | |
Proportion of urban land | 0.001 | 0.023 | 0.675 | 0.154 | 6.1 | |
Socioeconomic factor | GDP | 0.062 | 0.020 | 0.677 | 0.183 | 7.3 |
Population | 0.119 | 0.087 | 0.642 | 0.224 | 8.9 |
[1] | Agricultural Survey Division, National Bureau of Statistics, 2000-2015. China County Statistical Yearbook 2000-2015. Beijing: China Statistics Press. (in Chinese) |
[2] |
Bennett, E.M., Peterson, G.D., Gordon, L.J., 2009. Understanding relationships among multiple ecosystem services. Ecol. Lett. 12(12), 1394-1404.
doi: 10.1111/j.1461-0248.2009.01387.x pmid: 19845725 |
[3] |
Bennett, E.M., Cramer, W., Begossi, A., et al., 2015. Linking biodiversity, ecosystem services, and human well-being: three challenges for designing research for sustainability. Curr. Opin. Environ. Sustain. 14, 76-85.
doi: 10.1016/j.cosust.2015.03.007 |
[4] | Cai, C.F., Ding, S.W., Shi, Z.H., et al., 2000. Study of applying USLE and geographical information system IDRISI to predict soil erosion in small watershed. Journal of Soil and Water Conservation. 14(2), 19-24. (in Chinese) |
[5] | Chen, T.Q., Feng, Z., Zhao, H.F., et al., 2020. Identification of ecosystem service bundles and driving factors in Beijing and its surrounding areas. Sci. Total Environ. 711, 134687, doi: 10.1016/j.scitotenv.2019.134687. |
[6] | Choi, C.S., Berry, P., Smith, A., 2021. The climate benefits, co-benefits, and trade-offs of green infrastructure: A systematic literature review. J. Environ. Manage. 291, 112583, doi: 10.1016/j.jenvman.2021.112583. |
[7] |
Costanza, R., de Groot, R., Braat, L., et al., 2017. Twenty years of ecosystem services: How far have we come and how far do we still need to go? Ecosyst. Serv. 28(Part A), 1-16.
doi: 10.1016/j.ecoser.2017.09.008 |
[8] | Guevara-Ochoa, C., Medina-Sierra, A., Vives, L., 2020. Spatio-temporal effect of climate change on water balance and interactions between groundwater and surface water in plains. Sci. Total Environ. 722, 137886, doi: 10.1016/j.scitotenv.2020.137886. |
[9] | Jafarzadeh, A.A., Mahdavi, A., Shamsi, S.R.F., et al., 2021. Assessing synergies and trade-offs between ecosystem services in forest landscape management. Land Use Pol. 111, 105741, doi: 10.1016/j.landusepol.2021.105741. |
[10] |
Jiang, B., Bai, Y., Wong, C.P., et al., 2019. China’s ecological civilization program-Implementing ecological redline policy. Land Use Pol. 81, 111-114.
doi: 10.1016/j.landusepol.2018.10.031 |
[11] | Jiang, S., Cheng, X., Yu, S., et al., 2022. Elevation dependency of ecosystem services supply efficiency in great lake watershed. J. Environ. Manage. 318, 115476, doi: 10.1016/j.jenvman.2022.115476. |
[12] | Kou, P.L., Xu, Q., Jin, Z., et al., 2021. Complex anthropogenic interaction on vegetation greening in the Chinese Loess Plateau. Sci. Total Environ. 778, 146065, doi: 10.1016/j.scitotenv.2021.146065. |
[13] |
Li, J.J., Peng, S.Z., Li, Z., 2017. Detecting and attributing vegetation changes on China’s Loess Plateau. Agric. For. Meteorol. 247, 260-270.
doi: 10.1016/j.agrformet.2017.08.005 |
[14] | Li, K., Hou, Y., Andersen, P.S., et al., 2022. An ecological perspective for understanding regional integration based on ecosystem service budgets, bundles, and flows: A case study of the Jinan metropolitan area in China. J. Environ. Manage. 305, 114371, doi: 10.1016/j.jenvman.2021.114371. |
[15] |
Li, T., Lü, Y.H., Fu, B.J., et al., 2019. Bundling ecosystem services for detecting their interactions driven by large-scale vegetation restoration: Enhanced services while depressed synergies. Ecol. Indic. 99, 332-342.
doi: 10.1016/j.ecolind.2018.12.041 |
[16] | Li, Z.H., Xia, J., Deng, X.Z., et al., 2021. Multilevel modelling of impacts of human and natural factors on ecosystem services change in an oasis, Northwest China. Resour. Conserv. Recycl. 169, 105474, doi: 10.1016/j.resconrec.2021.105474. |
[17] | Liang, Y.J., Hashimoto, S., Liu, L.J., 2021. Integrated assessment of land-use/land-cover dynamics on carbon storage services in the Loess Plateau of China from 1995 to 2050. Ecol. Indic. 120, 106939, doi: 10.1016/j.ecolind.2020.106939. |
[18] |
Lin, S.W., Wu, R.D., Yang, F.L., et al., 2018. Spatial trade-offs and synergies among ecosystem services within a global biodiversity hotspot. Ecol. Indic. 84, 371-381.
doi: 10.1016/j.ecolind.2017.09.007 |
[19] |
Liu, B.Y., Nearing, M.A., Shi, P.J., et al., 2000. Slope length effects on soil loss for steep slopes. Soil Sci. Soc. Am. J. 64(5), 1759-1763.
doi: 10.2136/sssaj2000.6451759x |
[20] | Liu, H.J., Yan, F.Y., Tian, H., 2022a. Towards low-carbon cities: Patch-based multi-objective optimization of land use allocation using an improved non-dominated sorting genetic algorithm-II. Ecol. Indic. 134, 108455, doi: 10.1016/j.ecolind.2021.108455. |
[21] | Liu, Y.X., Li, T., Zhao, W.W., et al., 2019. Landscape functional zoning at a county level based on ecosystem services bundle: Methods comparison and management indication. J. Environ. Manage. 249, 109315, doi: 10.1016/j.jenvman.2019.109315. |
[22] | Liu, Z.H., Huang, Q.D., Zhou, Y., et al., 2022b. Spatial identification of restored priority areas based on ecosystem service bundles and urbanization effects in a megalopolis area. J. Environ. Manage. 308, 114627, doi: 10.1016/j.jenvman.2022.114627. |
[23] | Ma, S., Li, Y., Zhang, Y.H., et al., 2022. Distinguishing the relative contributions of climate and land use/cover changes to ecosystem services from a geospatial perspective. Ecol. Indic. 136, 108645, doi: 10.1016/j.ecolind.2022.108645. |
[24] | Mashizi, A.K., Sharafatmandrad, M., 2021. Investigating tradeoffs between supply, use and demand of ecosystem services and their effective drivers for sustainable environmental management. J. Environ. Manage. 289, 112534, doi: 10.1016/j.jenvman.2021.112534. |
[25] | Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-Being: Synthesis Report. [2023-02-16]. https://doi.org/10.1016/j.ecolind.2022.108645.10.1119/1.2344558. |
[26] |
Mouchet, M.A., Paracchini, M.L., Schulp, C.J.E., et al., 2017. Bundles of ecosystem (dis) services and multifunctionality across European landscapes. Ecol. Indic. 73, 23-28.
doi: 10.1016/j.ecolind.2016.09.026 |
[27] | Peng, J., Hu, X.X., Wang, X.Y., et al., 2019. Simulating the impact of Grain-for-Green Programme on ecosystem services trade-offs in Northwestern Yunnan, China. Ecosyst. Serv. 39, 100998, doi: 10.1016/j.ecoser.2019.100998. |
[28] | Qiu, L.J., Wu, Y.P., Shi, Z.Y., et al., 2021. Quantifying spatiotemporal variations in soil moisture driven by vegetation restoration on the Loess Plateau of China. J. Hydrol. 600, 126580, doi: 10.1016/j.jhydrol.2021.126580. |
[29] | Raudsepp-Hearne, C., Peterson, G.D., Bennett, E.M., 2010. Ecosystem service bundles for analyzing tradeoffs in diverse landscapes. Proc. Natl. Acad. Sci. U. S. A. 107(11), 5242-5247. |
[30] | Saidi, N., Spray, C., 2018. Ecosystem services bundles: challenges and opportunities for implementation and further research. Environ. Res. Lett. 13(11), 113001, doi:10.1088/1748-9326/aae5e0. |
[31] | Shen, J.S., Li, S.C., Liang, Z., et al., 2020. Exploring the heterogeneity and nonlinearity of trade-offs and synergies among ecosystem services bundles in the Beijing-Tianjin-Hebei urban agglomeration. Ecosyst. Serv. 43, 101103, doi: 10.1016/j.ecoser.2020.101103. |
[32] |
Song, W., Deng, X.Z., Yuan, Y.W., et al., 2015. Impacts of land-use change on valued ecosystem service in rapidly urbanized North China Plain. Ecol. Model. 318, 245-253.
doi: 10.1016/j.ecolmodel.2015.01.029 |
[33] |
Sun, D.Z., Liang, Y.J., Peng, S.Z., 2022. Scenario simulation of water retention services under land use/cover and climate changes: a case study of the Loess Plateau, China. J. Arid Land. 14(4), 390-410.
doi: 10.1007/s40333-022-0054-4 |
[34] | Sun, W.Y., Shao, Q.Q., Liu, J.Y., 2014. Assessment of soil conservation function of the ecosystem services on the Loess Plateau. Journal of Natural Resources. 29(3), 365-376. (in Chinese) |
[35] | Sun, Y., Hao, R.F., Qiao, J.M., et al., 2020. Function zoning and spatial management of small watersheds based on ecosystem disservice bundles. J. Clean Prod. 255, 120285, doi: 10.1016/j.jclepro.2020.120285. |
[36] |
Vallet, A., Locatelli, B., Levrel, H., et al., 2018. Relationships between ecosystem services: comparing methods for assessing tradeoffs and synergies. Ecol. Econ. 150, 96-106.
doi: 10.1016/j.ecolecon.2018.04.002 |
[37] | Wang, B., Liang, Y.J., Peng, S.Z., 2022a. Harnessing the indirect effect of urban expansion for mitigating agriculture-environment trade-offs in the Loess Plateau. Land Use Pol. 122, 106395, doi: 10.1016/j.landusepol.2022.106395. |
[38] |
Wang, C.D., Li, X., Yu, H.J., et al., 2019. Tracing the spatial variation and value change of ecosystem services in Yellow River Delta, China. Ecol. Indic. 96, 270-277.
doi: 10.1016/j.ecolind.2018.09.015 |
[39] | Wang, D., Liang, Y.J., Peng, S.Z., et al., 2022b. Integrated assessment of the supply-demand relationship of ecosystem services in the Loess Plateau during 1992-2015. Ecosyst. Health Sustain. 8(1), 2130093, doi: 10.1080/20964129.2022.2130093. |
[40] | Wang, H., Huang, J.J., Zhou, H., et al., 2020. Analysis of sustainable utilization of water resources based on the improved water resources ecological footprint model: A case study of Hubei Province, China. J. Environ. Manage. 262, 110331, doi: 10.1016/j.jenvman.2020.110331. |
[41] |
Wang, J.T., Peng, J., Zhao, M.Y., et al., 2017. Significant trade-off for the impact of Grain-for-Green Programme on ecosystem services in North-western Yunnan, China. Sci. Total Environ. 574, 57-64.
doi: 10.1016/j.scitotenv.2016.09.026 |
[42] | Wang, W.L., Jiao, L.M., Jia, Q.Q., et al., 2021. Land use optimization modelling with ecological priority perspective for large-scale spatial planning. Sust. Cities Soc. 65, 102575, doi: 10.1016/j.scs.2020.102575. |
[43] | Wang, X.Z., Wu, J.Z., Liu, Y.L., et al., 2022c. Driving factors of ecosystem services and their spatiotemporal change assessment based on land use types in the Loess Plateau. J. Environ. Manage. 311, 114835, doi: 10.1016/j.jenvman.2022.114835. |
[44] |
Williams, J.R., Jones, C.A., Dyke, P.T., 1984. A modeling approach to determining the relationship between erosion and soil productivity. Trans. ASAE. 27(1), 129-144.
doi: 10.13031/2013.32748 |
[45] | Wischmeier, W.H., Smith, D.D., 1978. Predicting Rainfall Erosion Losses - A Guide to Conservation Planning. Hyattsville: United States Department of Agriculture, Science and Education Administration, 62. |
[46] | Wu, F., Liang, Y.J., Peng, S.Z., et al., 2022. Challenges in trade-off governance of ecosystem services: Evidence from the Loess Plateau in China. Ecol. Indic. 145, 109686, doi: 10.1016/j.ecolind.2022.109686. |
[47] |
Wu, X.T., Wang, S., Fu, B.J., et al., 2018. Land use optimization based on ecosystem service assessment: A case study in the Yanhe watershed. Land Use Pol. 72, 303-312.
doi: 10.1016/j.landusepol.2018.01.003 |
[48] |
Xie, G.D., Zhang, C.X., Zhen, L., et al., 2017. Dynamic changes in the value of China’s ecosystem services. Ecosyst. Serv. 26(Part A), 146-154.
doi: 10.1016/j.ecoser.2017.06.010 |
[49] | Xu, H.J., Zhao, C.Y., Chen, S.Y., et al., 2022. Spatial relationships among regulating ecosystem services in mountainous regions: Nonlinear and elevation-dependent. J. Clean Prod. 380, 135050, doi: 10.1016/j.jclepro.2022.135050. |
[50] |
Xu, X.B., Yang, G.S., Tan, Y., et al., 2018. Ecosystem services trade-offs and determinants in China’s Yangtze River Economic Belt from 2000 to 2015. Sci. Total Environ. 634, 1601-1614.
doi: 10.1016/j.scitotenv.2018.04.046 |
[51] | Yang, S.Q., Zhao, W.W., Liu, Y.X., et al., 2020. Prioritizing sustainable development goals and linking them to ecosystem services: A global expert’s knowledge evaluation. Geogr. Sustain. 1(4), 321-330. |
[52] |
Yang, Y.Y., Zheng, H., Kong, L.Q., et al., 2019. Mapping ecosystem services bundles to detect high- and low-value ecosystem services areas for land use management. J. Clean Prod. 225, 11-17.
doi: 10.1016/j.jclepro.2019.03.242 |
[53] | Yin, S.Q., Xue, X.C., Yue, T.Y., et al., 2019. Spatiotemporal distribution and return period of rainfall erosivity in China. Transactions of the Chinese Society of Agricultural Engineering. 35(9), 105-113. (in Chinese) |
[54] | Zhang, Y., Zhao, X.L., Zuo, L.J., et al., 2018. Dynamic evaluation and analysis on ecosystem service value in the Loess Plateau. Research of Soil and Water Conservation. 25(3), 170-176. (in Chinese) |
[55] | Zhang, Z.Y., Liu, Y.F., Wang, Y.H., et al., 2020. What factors affect the synergy and tradeoff between ecosystem services, and how, from a geospatial perspective? J. Clean Prod. 257, 120454, doi: 10.1016/j.jclepro.2020.120454. |
[56] | Zhao, L., Yuan, G.L., Zhang, Y., et al., 2007. The amount of soil erosion in Baoxiang Watershed of Dianchi Lake based on GIS and USLE. Bulletin Soil and Water Conservation. 27(3), 42-46. (in Chinese) |
[57] |
Zhu, W.Q., Pan, Y.Z., He, H., et al., 2006. Simulation of maximum light use efficiency for some typical vegetation types in China. Chin. Sci. Bull. 51(4), 457-463.
doi: 10.1007/s11434-006-0457-1 |
[58] |
Zhu, W.Q., Pan, Y.Z., Zhang, J.S., 2007. Estimation of net primary productivity of Chinese terrestrial vegetation based on remote sensing. Chinese Journal of Plant Ecology. 31(3), 413-424. (in Chinese)
doi: 10.17521/cjpe.2007.0050 |
[1] | Camillus Abawiera WONGNAA, Alex Amoah SEYRAM, Suresh BABU. A systematic review of climate change impacts, adaptation strategies, and policy development in West Africa [J]. Regional Sustainability, 2024, 5(2): 100137-. |
[2] | Bubun MAHATA, Siba Sankar SAHU, Archishman SARDAR, Laxmikanta RANA, Mukul MAITY. Spatiotemporal dynamics of land use/land cover (LULC) changes and its impact on land surface temperature: A case study in New Town Kolkata, eastern India [J]. Regional Sustainability, 2024, 5(2): 100138-. |
[3] | Suchitra PANDEY, Geetilaxmi MOHAPATRA, Rahul ARORA. Spatio-temporal variation of depth to groundwater level and its driving factors in arid and semi-arid regions of India [J]. Regional Sustainability, 2024, 5(2): 100143-. |
[4] | Ramya Kundayi RAVI, Priya BABY, Nidhin ELIAS, Jisa George THOMAS, Kathyayani Bidadi VEERABHADRAIAH, Bharat PAREEK. Preparedness, knowledge, and perception of nursing students about climate change and its impact on human health in India [J]. Regional Sustainability, 2024, 5(1): 100116-. |
[5] | Ashma SUBEDI, Nani RAUT, Smriti GURUNG. How Himalayan communities are changing cultivation practices in the context of climate change [J]. Regional Sustainability, 2023, 4(4): 378-389. |
[6] | Liton Chandra VOUMIK, Md. Hasanur RAHMAN, Md. Maznur RAHMAN, Mohammad RIDWAN, Salma AKTER, Asif RAIHAN. Toward a sustainable future: Examining the interconnectedness among Foreign Direct Investment (FDI), urbanization, trade openness, economic growth, and energy usage in Australia [J]. Regional Sustainability, 2023, 4(4): 405-415. |
[7] | Rula AWAD, Hosam TITI, Aziza MOHAMED-BRAHMI, Mohamed JAOUAD, Aziza GASMI-BOUBAKER. Small ruminant value chain in Al-Ruwaished District, Jordan [J]. Regional Sustainability, 2023, 4(4): 416-424. |
[8] | Girma TILAHUN, Amare BANTIDER, Desalegn YAYEH. Synergies and trade-offs of climate-smart agriculture (CSA) practices selected by smallholder farmers in Geshy watershed, Southwest Ethiopia [J]. Regional Sustainability, 2023, 4(2): 129-138. |
[9] | Enoch YELELIERE, Philip ANTWI-AGYEI, Frank BAFFOUR-ATA. Impacts of climate change on the yields of leguminous crops in the Guinea Savanna agroecological zone of Ghana [J]. Regional Sustainability, 2023, 4(2): 139-149. |
[10] | Subrata HALDAR, Somnath MANDAL, Subhasis BHATTACHARYA, Suman PAUL. Dynamicity of Land Use/Land Cover (LULC): An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation (DMC) in India [J]. Regional Sustainability, 2023, 4(2): 150-172. |
[11] | Tobias ACKERL, Lemlem Fitwi WELDEMARIAM, Mary NYASIMI, Ayansina AYANLADE. Climate change risk, resilience, and adaptation among rural farmers in East Africa: A literature review [J]. Regional Sustainability, 2023, 4(2): 185-193. |
[12] | Arifah , Darmawan SALMAN, Amir YASSI, Eymal Bahsar DEMMALLINO. Knowledge flow analysis of knowledge co-production-based climate change adaptation for lowland rice farmers in Bulukumba Regency, Indonesia [J]. Regional Sustainability, 2023, 4(2): 194-202. |
[13] | Isaac Ayo OLUWATIMILEHIN, Joseph Omojesu AKERELE, Tolulope Adedoyin OLADEJI, Mojisola Hannah OMOGBEHIN, Godwin ATAI. Assessment of the impact of climate change on the occurrences of malaria, pneumonia, meningitis, and cholera in Lokoja City, Nigeria [J]. Regional Sustainability, 2022, 3(4): 309-318. |
[14] | Enoch YELELIERE, Thomas YEBOAH, Philip ANTWI-AGYEI, Prince PEPRAH. Traditional agroecological knowledge and practices: The drivers and opportunities for adaptation actions in the northern region of Ghana [J]. Regional Sustainability, 2022, 3(4): 294-308. |
[15] | Firoz AHMAD, Nazimur Rahman TALUKDAR, Laxmi GOPARAJU, Chandrashekhar BIRADAR, Shiv Kumar DHYANI, Javed RIZVI. GIS-based assessment of land-agroforestry potentiality of Jharkhand State, India [J]. Regional Sustainability, 2022, 3(3): 254-268. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||