The analysis of grassland carrying capacity and its impact factors in typical mountain areas in Central Asia—A case of Kyrgyzstan and Tajikistan

Umuhoza, Jeanine; Jiapaer, Guli; Yin, Hanmin; Mind’je, Richard; Gasirabo, Aboubakar; Nzabarinda, Vincent; Umwali, Edovia Dufatanye

doi:10.1016/j.ecolind.2021.108129

Cited by 23 publications

(10 citation statements)

References 63 publications

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“…This study indicates that over the past 39 years, the livestock carrying capacity in Xinjiang has been fluctuating and closely correlated with factors such as annual rainfall, altitude, and soil conditions ( Cheng et al., 2017 ). This corresponds with Umuhoza’s research findings ( Umuhoza et al., 2021 ), which state that climate, soil types, topography plays a crucial role in shaping the composition and projected distribution of grassland carrying capacity. Luo also pointed out that the degradation of grassland could be caused by factors like small mammals, climate change, challenging environments, weak soil, and over-grazing ( Luo et al., 2021 ).…”

Section: Discussionsupporting

confidence: 90%

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

Ma,

Zheng,

Pen

et al. 2024

Front. Plant Sci.

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It is crucial to estimate the theoretical carrying capacity of grasslands in Xinjiang to attain a harmonious balance between grassland and livestock, thereby fostering sustainable development in the livestock industry. However, there has been a lack of quantitative assessments that consider long-term, multi-scale grass-livestock balance and its impacts in the region. This study utilized remote sensing and empirical models to assess the theoretical livestock carrying capacity of grasslands. The multi-scale spatiotemporal variations of the theoretical carrying capacity in Xinjiang from 1982 to 2020 were analyzed using the Sen and Mann-Kendall tests, as well as the Hurst index. The study also examined the county-level grass-livestock balance and inter-annual trends. Additionally, the study employed the geographic detector method to explore the influencing factors. The results showed that: (1) The overall theoretical livestock carrying capacity showed an upward trend from 1982 to 2020; The spatial distribution gradually decreased from north to south and from east to west. In seasonal scale from large to small is: growing season > summer > spring > autumn > winter; at the monthly scale, the strongest livestock carrying capacity is in July. The different grassland types from largest to smallest are: meadow > alpine subalpine meadow > plain steppe > desert steppe > alpine subalpine steppe. In the future, the theoretical livestock carrying capacity of grassland will decrease. (2) From 1988 to 2020, the average grass-livestock balance index in Xinjiang was 2.61%, showing an overall increase. At the county level, the number of overloaded counties showed an overall increasing trend, rising from 46 in 1988 to 58 in 2020. (3) Both single and interaction factors of geographic detectors showed that annual precipitation, altitude and soil organic matter were the main drivers of spatiotemporal dynamics of grassland load in Xinjiang. The results of this study can provide scientific guidance and decision-making basis for achieving coordinated and sustainable development of grassland resources and animal husbandry in the region.

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Section: Discussionsupporting

confidence: 90%

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

Ma,

Zheng,

Pen

et al. 2024

Front. Plant Sci.

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“…Considering comprehensively, this topic introduces multisource data fusion technology into grassland environment monitoring and deeply studies the relevant theories and key technologies of multisource data fusion in grassland environment monitoring. The final results can accurately reflect the situation of grassland environment; this is a reference to pastureland science management and governance measures [4].…”

Section: Introductionmentioning

confidence: 97%

[Retracted] Application of Multisource Data Fusion Technology in the Construction of Land Ecological Index

et al. 2023

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In order to control the grassland ecological environment, an application method of multisource data fusion technology in the construction of land ecological index is proposed. Due to the high requirements for grassland environmental monitoring, the use of traditional technologies to monitor grassland environmental conditions lacks certain effectiveness, has high investment costs, and consumes a lot of manpower and material resources. The use of sensors to dynamically monitor the grassland environment is conducive to monitoring the environment from a scientific and technological level. By understanding the fusion principle and process of three fusion methods, adaptive weighted average, BP neural network, and D-S evidence theory, the construction of Bashang grassland ecological energy big data platform based on multisource data fusion is proposed. A two-level data fusion model based on grassland environmental monitoring is proposed. Several environmental parameters in the experimental environment were monitored, and the validity of the two-level fusion model was verified by two evaluation indicators, the mean absolute percentage error and the corrosion error. This suggests that a combination of BP neural network and D-S proof theory improves system performance. It provides the possibility for more comprehensive monitoring of grassland ecological environment in the future.

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“…Important archaeological sites classified as UNESCO heritage sites are located in mountain areas, such as Historic Sanctuary of Machu Picchu (Peru), Phnom Kulen (Cambodia), Prehistoric Rock Art Sites in the Côa Valley and Siega Verde (Portugal), Sacri Monti of Piedmont and Lombardy (Italy) and Archaeological Site of Delphi (Greece) (https:// whc.unesco.org/en/list/). Finally, mountain areas are excellent laboratories to develop cutting edge research and to understand important phenomena such as climate change (e.g., glacier dynamics, Bach et al, 2018;vegetation pro-cesses, García-Ruiz et al, 2015), pre-historical human development (e.g., Dreslerová et al, 2020), the interaction between past climate change and human expansion, i.e., agriculture and mining (e.g., lake sediments/pollen, Rey et al, 2017), land degradation (e.g., overgrazing, Umuhoza et al, 2021) or land abandonment (e.g., rural exodus/vegetation encroachment, Nadal-Romero et al, 2021) (Figure 1).…”

Section: Cultural Ecosystem Servicesmentioning

confidence: 99%

Servicios ecosistémicos en áreas de montaña: beneficios y amenazas

et al. 2022

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Las áreas de montaña tienen un impacto importante en las dinámicas climáticas y son una de las fuentes de agua con condiciones más críticas. Las montañas fueron claves en la evolución histórica del ser humano y suministraron servicios ecosistémicos (SE) bióticos y abióticos esenciales para la vida humana. Este artículo de perspectiva estudiará la importancia de las montañas para el suministro de SE y los impactos de los diferentes factores de cambio, a saber, cambios en el hábitat, el cambio climático, la sobreexplotación, la contaminación y las especies invasoras. Las zonas de montaña tienen una gran capacidad para suministrar un número importante de recursos reguladores (regulación del clima global y local, regulación de la calidad del aire, regulación de los riesgos naturales, polinización), de aprovisionamiento (cultivos, ganado, alimentos y pesca silvestre, biomasa para energía y madera, energía renovable de agua dulce -hidroeléctrica, eólica, solar y geotérmica- y recursos minerales) y culturales (ocio y turismo, estética e inspiración del paisaje, patrimonio cultural y diversidad cultural y sistemas de conocimiento). Sin embargo, los cambios impuestos por la modificación del hábitat, el cambio climático, la sobreexplotación, la contaminación y las especies invasoras pueden aumentar los intercambios entre los SE y desencadenar la degradación del medio ambiente. En general, es necesario equilibrar la utilización de los SE de montaña y reducir los efectos de los distintos factores de cambio.

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The analysis of grassland carrying capacity and its impact factors in typical mountain areas in Central Asia—A case of Kyrgyzstan and Tajikistan

Cited by 23 publications

References 63 publications

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

Monitoring and influencing factors of grassland livestock overload in Xinjiang from 1982 to 2020

[Retracted] Application of Multisource Data Fusion Technology in the Construction of Land Ecological Index

Servicios ecosistémicos en áreas de montaña: beneficios y amenazas

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