Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Essential fragmentation metrics for agricultural policies : Linking landscape pattern, ecosystem service and land use management in urbanizing China

Wei, Lai ; Luo, Yun ; Wang, Miao ; Su, Shiliang ; Pi, Jianhua and Li, Guie (2020) In Agricultural Systems 182.
Abstract

Fragmentation, as one of the most distinct characteristics of agricultural landscapes worldwide, has resulted in a diversity of ecological consequences. It remains as a gap in the literature on how provisioning service changes in association with agricultural fragmentation and land use management. Addressing such a gap at a national level should provide essential insights for policymakers. This paper identifies the essential metrics from a set of landscape metrics for describing agricultural fragmentation and further develops an integrated fragmentation index (IFI). Using the IFI, spatiotemporal dynamics of agricultural fragmentation across Chinese cities from 2010 to 2017 are captured. In particular, an increasing trend of... (More)

Fragmentation, as one of the most distinct characteristics of agricultural landscapes worldwide, has resulted in a diversity of ecological consequences. It remains as a gap in the literature on how provisioning service changes in association with agricultural fragmentation and land use management. Addressing such a gap at a national level should provide essential insights for policymakers. This paper identifies the essential metrics from a set of landscape metrics for describing agricultural fragmentation and further develops an integrated fragmentation index (IFI). Using the IFI, spatiotemporal dynamics of agricultural fragmentation across Chinese cities from 2010 to 2017 are captured. In particular, an increasing trend of fragmentation is identified and southern China is characterized by more fragmented agricultural landscapes than the other parts. Spatial regression, with the Cobb-Douglas Production Function as the theoretical basis, is employed to quantify the relationships among provisioning service, agricultural fragmentation, and land use management. It is discovered that landscape fragmentation would impair the supply of the provisioning service and sustainable land use management regulates the provisioning service in a positive way. We argue that alleviating the landscape fragmentation issue would not be achieved with simple measurement. Cooperation of a series of administrative acts, such as land reclamation, land use transfer, household registration system reform and improvement of employment and welfare system, should be fundamental and practical approaches. The present study demonstrates a novel methodological framework to unravel the effect of agricultural fragmentation on provisioning services, which should be useful for understanding the complex human-ecosystem interactions.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Agricultural management, Cobb-Douglas production function, Landscape fragmentation, Landscape metrics, Provisioning services
in
Agricultural Systems
volume
182
article number
102833
publisher
Elsevier
external identifiers
  • scopus:85083017300
ISSN
0308-521X
DOI
10.1016/j.agsy.2020.102833
language
English
LU publication?
no
id
46e49400-54a7-411e-b070-2a742b6b2a73
date added to LUP
2021-01-04 14:52:27
date last changed
2022-04-26 23:03:17
@article{46e49400-54a7-411e-b070-2a742b6b2a73,
  abstract     = {{<p>Fragmentation, as one of the most distinct characteristics of agricultural landscapes worldwide, has resulted in a diversity of ecological consequences. It remains as a gap in the literature on how provisioning service changes in association with agricultural fragmentation and land use management. Addressing such a gap at a national level should provide essential insights for policymakers. This paper identifies the essential metrics from a set of landscape metrics for describing agricultural fragmentation and further develops an integrated fragmentation index (IFI). Using the IFI, spatiotemporal dynamics of agricultural fragmentation across Chinese cities from 2010 to 2017 are captured. In particular, an increasing trend of fragmentation is identified and southern China is characterized by more fragmented agricultural landscapes than the other parts. Spatial regression, with the Cobb-Douglas Production Function as the theoretical basis, is employed to quantify the relationships among provisioning service, agricultural fragmentation, and land use management. It is discovered that landscape fragmentation would impair the supply of the provisioning service and sustainable land use management regulates the provisioning service in a positive way. We argue that alleviating the landscape fragmentation issue would not be achieved with simple measurement. Cooperation of a series of administrative acts, such as land reclamation, land use transfer, household registration system reform and improvement of employment and welfare system, should be fundamental and practical approaches. The present study demonstrates a novel methodological framework to unravel the effect of agricultural fragmentation on provisioning services, which should be useful for understanding the complex human-ecosystem interactions.</p>}},
  author       = {{Wei, Lai and Luo, Yun and Wang, Miao and Su, Shiliang and Pi, Jianhua and Li, Guie}},
  issn         = {{0308-521X}},
  keywords     = {{Agricultural management; Cobb-Douglas production function; Landscape fragmentation; Landscape metrics; Provisioning services}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Agricultural Systems}},
  title        = {{Essential fragmentation metrics for agricultural policies : Linking landscape pattern, ecosystem service and land use management in urbanizing China}},
  url          = {{http://dx.doi.org/10.1016/j.agsy.2020.102833}},
  doi          = {{10.1016/j.agsy.2020.102833}},
  volume       = {{182}},
  year         = {{2020}},
}