IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i11p6738-d828828.html
   My bibliography  Save this article

Spatial Vegetation Patch Patterns and Their Relation to Environmental Factors in the Alpine Grasslands of the Qilian Mountains

Author

Listed:
  • Theophilus Atio Abalori

    (Grassland Ecosystem Key Laboratory of Ministry of Education, Sino-US Research Centre for Sustainable Grassland and Livestock Management, Grassland Science College of Gansu Agricultural University, Lanzhou 730070, China)

  • Wenxia Cao

    (Grassland Ecosystem Key Laboratory of Ministry of Education, Sino-US Research Centre for Sustainable Grassland and Livestock Management, Grassland Science College of Gansu Agricultural University, Lanzhou 730070, China)

  • Conrad Atogi-Akwoa Weobong

    (Faculty of Natural Resources and Environment, University for Development Studies, Tamale P.O. Box 1882, Ghana)

  • Wen Li

    (Key Laboratory of Development of Forage Germplasm in the Qinghai-Tibetan Plateau of Qinghai Province, Qinghai Academy of Animal Science and Veterinary Medicine of Qinghai University, Xining 810003, China)

  • Shilin Wang

    (Grassland Ecosystem Key Laboratory of Ministry of Education, Sino-US Research Centre for Sustainable Grassland and Livestock Management, Grassland Science College of Gansu Agricultural University, Lanzhou 730070, China)

  • Xiuxia Deng

    (Grassland Ecosystem Key Laboratory of Ministry of Education, Sino-US Research Centre for Sustainable Grassland and Livestock Management, Grassland Science College of Gansu Agricultural University, Lanzhou 730070, China)

Abstract

Globally, grasslands are affected by climate change and unsustainable management practices which usually leads to transitions from stable, degraded and then to desertification. Spatial vegetation patch configurations are regarded as key indicators of such transitions. Understanding the relationships between this grass-land vegetation and its environment is key to vegetation restoration projects. Spatial vegetation patch patterns were chosen across different soil and topographic conditions. Patch numbers, perimeter, and cover of each patch were measured along transects of each patch type. Using field surveys and multivariate statistical analysis, we investigated the differences in vegetation biomass and distribution and soil properties of four typical alpine plant species patches along with a range of environmental and topographic conditions. It was found that topographic conditions and soil properties, particularly soil moisture explained most of the variation in spatial patch vegetation characteristics and thus control vegetation restoration in the alpine grassland. The Kobresia humilis , Blysmus sinocompressus and Iris lactea patches under the drylands recorded small patch sizes, large patch numbers, low connectivity, and large total perimeter per unit area. Generally, species within the high moisture sites recorded small patch numbers, a large fraction of vegetation cover and a small total perimeter per m 2 . Patches in limited soil moisture areas recorded patch configurations indicating they are unstable and undergoing degradation and therefore need urgent restoration attention to forestall their further degradation and its resultant effect of desertification. These results would provide quantitative easy-to-use indicators for vegetation degradation and help in vegetation restoration projects.

Suggested Citation

  • Theophilus Atio Abalori & Wenxia Cao & Conrad Atogi-Akwoa Weobong & Wen Li & Shilin Wang & Xiuxia Deng, 2022. "Spatial Vegetation Patch Patterns and Their Relation to Environmental Factors in the Alpine Grasslands of the Qilian Mountains," Sustainability, MDPI, vol. 14(11), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6738-:d:828828
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/11/6738/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/11/6738/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xinxin Guo & Qiang Fu & Yanhong Hang & He Lu & Fengjie Gao & Jingbo Si, 2020. "Spatial Variability of Soil Moisture in Relation to Land Use Types and Topographic Features on Hillslopes in the Black Soil (Mollisols) Area of Northeast China," Sustainability, MDPI, vol. 12(9), pages 1-21, April.
    2. Jun Pei & Wei Yang & Yangpeng Cai & Yujun Yi & Xiaoxiao Li, 2018. "Relationship between Vegetation and Environment in an Arid-Hot Valley in Southwestern China," Sustainability, MDPI, vol. 10(12), pages 1-14, December.
    3. Runhong Liu & Yuanfang Pan & Han Bao & Shichu Liang & Yong Jiang & Hongrun Tu & Juanli Nong & Wanqing Huang, 2020. "Variations in Soil Physico-Chemical Properties along Slope Position Gradient in Secondary Vegetation of the Hilly Region, Guilin, Southwest China," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    4. Sonia Kéfi & Max Rietkerk & Concepción L. Alados & Yolanda Pueyo & Vasilios P. Papanastasis & Ahmed ElAich & Peter C. de Ruiter, 2007. "Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems," Nature, Nature, vol. 449(7159), pages 213-217, September.
    5. Alados, C.L. & Aich, A. El & Komac, B. & Pueyo, Y. & García-Gonzalez, R., 2007. "Self-organized spatial patterns of vegetation in alpine grasslands," Ecological Modelling, Elsevier, vol. 201(2), pages 233-242.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ferreira, A.S. & Raposo, E.P. & Viswanathan, G.M. & da Luz, M.G.E., 2012. "The influence of the environment on Lévy random search efficiency: Fractality and memory effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3234-3246.
    2. Marina E Wosniack & Marcos C Santos & Ernesto P Raposo & Gandhi M Viswanathan & Marcos G E da Luz, 2017. "The evolutionary origins of Lévy walk foraging," PLOS Computational Biology, Public Library of Science, vol. 13(10), pages 1-31, October.
    3. Mohamed A. E. AbdelRahman & Yasser M. Zakarya & Mohamed M. Metwaly & Georgios Koubouris, 2020. "Deciphering Soil Spatial Variability through Geostatistics and Interpolation Techniques," Sustainability, MDPI, vol. 13(1), pages 1-13, December.
    4. van den Berg, J. & Björnberg, J.E. & Heydenreich, M., 2015. "Sharpness versus robustness of the percolation transition in 2d contact processes," Stochastic Processes and their Applications, Elsevier, vol. 125(2), pages 513-537.
    5. Salvati, Luca & Carlucci, Margherita, 2015. "Towards sustainability in agro-forest systems? Grazing intensity, soil degradation and the socioeconomic profile of rural communities in Italy," Ecological Economics, Elsevier, vol. 112(C), pages 1-13.
    6. Fabio Recanatesi & Matteo Clemente & Efstathios Grigoriadis & Flavia Ranalli & Marco Zitti & Luca Salvati, 2015. "A Fifty-Year Sustainability Assessment of Italian Agro-Forest Districts," Sustainability, MDPI, vol. 8(1), pages 1-13, December.
    7. Muhammad Waseem Rasheed & Jialiang Tang & Abid Sarwar & Suraj Shah & Naeem Saddique & Muhammad Usman Khan & Muhammad Imran Khan & Shah Nawaz & Redmond R. Shamshiri & Marjan Aziz & Muhammad Sultan, 2022. "Soil Moisture Measuring Techniques and Factors Affecting the Moisture Dynamics: A Comprehensive Review," Sustainability, MDPI, vol. 14(18), pages 1-23, September.
    8. Martinez-Garcia, Ricardo & Cabal, Ciro & Calabrese, Justin M. & Hernández-García, Emilio & Tarnita, Corina E. & López, Cristóbal & Bonachela, Juan A., 2023. "Integrating theory and experiments to link local mechanisms and ecosystem-level consequences of vegetation patterns in drylands," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    9. Convertino, M., 2011. "Neutral metacommunity clustering and SAR: River basin vs. 2-D landscape biodiversity patterns," Ecological Modelling, Elsevier, vol. 222(11), pages 1863-1879.
    10. Baeza, Andres, 2018. "Modelling the critical transition from Chilean evergreen forest to savanna: Early warning signals and livestock management," Ecological Modelling, Elsevier, vol. 388(C), pages 115-123.
    11. Jerome R. Mayaud & Nicholas P. Webb, 2017. "Vegetation in Drylands: Effects on Wind Flow and Aeolian Sediment Transport," Land, MDPI, vol. 6(3), pages 1-24, September.
    12. Nguyen Duc Luong & Nguyen Hoang Hiep & Thi Hieu Bui, 2021. "Investigating the Spatio-Temporal Variation of Soil Moisture and Agricultural Drought towards Supporting Water Resources Management in the Red River Basin of Vietnam," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    13. Nauta, Johannes & Simoens, Pieter & Khaluf, Yara, 2022. "Group size and resource fractality drive multimodal search strategies: A quantitative analysis on group foraging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    14. Tlidi, M. & Messaoudi, M. & Makhoute, A. & Pinto-Ramos, D. & Clerc, M.G., 2024. "Non-linear and non-local plant–plant interactions in arid climate: Allometry, criticality and desertification," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    15. Meron, Ehud, 2012. "Pattern-formation approach to modelling spatially extended ecosystems," Ecological Modelling, Elsevier, vol. 234(C), pages 70-82.
    16. Lijun Liu & Guanglin Gou & Jinxia Liu & Xuebin Zhang & Qilin Zhu & Jinxia Mou & Ruoyan Yang & Yunxing Wan & Lei Meng & Shuirong Tang & Yanzheng Wu & Qiuxiang He, 2022. "Effects of Dodonaea viscosa Afforestation on Soil Nutrients and Aggregate Stability in Karst Graben Basin," Land, MDPI, vol. 11(8), pages 1-12, July.
    17. Prabhavathy Settu & Mangayarkarasi Ramaiah, 2024. "Estimation of Sentinel-1 derived soil moisture using modified Dubois model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(11), pages 29677-29693, November.
    18. Pliscoff, Patricio & Luebert, Federico & Hilger, Hartmut H. & Guisan, Antoine, 2014. "Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: A test with plants in an arid environment," Ecological Modelling, Elsevier, vol. 288(C), pages 166-177.
    19. Tekwa, Edward W. & Gonzalez, Andrew & Loreau, Michel, 2019. "Spatial evolutionary dynamics produce a negative cooperation–population size relationship," Theoretical Population Biology, Elsevier, vol. 125(C), pages 94-101.
    20. Diaf Imene & Pierre Pech & Touati Bouzid, 2019. "What strategies make compatible the stakes of nature conservation and the stakes of economic growth in protected area? Example of El Kala National Park, Algeria," Post-Print halshs-02188250, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6738-:d:828828. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.