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Open AccessFeature PaperArticle

A Conceptual Model for Land System Dynamics as a Coupled Human–Environment System

by

Richard Aspinall

and

Michele Staiano

Land 2017, 6(4), 81; https://doi.org/10.3390/land6040081 - 16 Nov 2017

Cited by 25 | Viewed by 5241

Abstract

This paper presents a conceptual model of land as a coupled human–environment system. Land use and land cover are incorporated as elements of the human and environment system respectively. Drivers and associated processes that influence land use, land cover, and land system dynamics [...] Read more.

This paper presents a conceptual model of land as a coupled human–environment system. Land use and land cover are incorporated as elements of the human and environment system respectively. Drivers and associated processes that influence land use, land cover, and land system dynamics are incorporated within a set of sub-systems. The model includes consideration of driving sub-systems as a set of capital funds and flows, and how these are influenced by linkages between processes in the human (socio-economic) and environment systems and sub-systems. The model is consistent with existing models of the biophysical earth system used by the land change, earth system sciences, and socio-ecological systems communities. The purposes of the model are to provide (i) a holistic framework within which descriptions, models and analyses that focus on various components of land can be placed to describe and explain land systems and land system changes; and (ii) a guide for the development of more fully integrated and interdisciplinary understanding, analysis and study of land use and land cover dynamics, with explicit focus on relationships between human and natural systems. Full article

(This article belongs to the Special Issue Land System Science)

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Open AccessArticle

Typologies and Spatialization of Agricultural Production Systems in Rondônia, Brazil: Linking Land Use, Socioeconomics and Territorial Configuration

by

Cláudio Almeida

,

Moisés Mourão

,

Nadine Dessay

,

Anne-Elisabeth Lacques

,

,

,

and

Land 2016, 5(2), 18; https://doi.org/10.3390/land5020018 - 22 Jun 2016

Cited by 6 | Viewed by 6038

Abstract

The current Amazon landscape consists of heterogeneous mosaics formed by interactions between the original forest and productive activities. Recognizing and quantifying the characteristics of these landscapes is essential for understanding agricultural production chains, assessing the impact of policies, and in planning future actions. [...] Read more.

The current Amazon landscape consists of heterogeneous mosaics formed by interactions between the original forest and productive activities. Recognizing and quantifying the characteristics of these landscapes is essential for understanding agricultural production chains, assessing the impact of policies, and in planning future actions. Our main objective was to construct the regionalization of agricultural production for Rondônia State (Brazilian Amazon) at the municipal level. We adopted a decision tree approach, using land use maps derived from remote sensing data (PRODES and TerraClass) combined with socioeconomic data. The decision trees allowed us to allocate municipalities to one of five agricultural production systems: (i) coexistence of livestock production and intensive agriculture; (ii) semi-intensive beef and milk production; (iii) semi-intensive beef production; (iv) intensive beef and milk production, and; (v) intensive beef production. These production systems are, respectively, linked to mechanized agriculture (i), traditional cattle farming with low management, with (ii) or without (iii) a significant presence of dairy farming, and to more intensive livestock farming with (iv) or without (v) a significant presence of dairy farming. The municipalities and associated production systems were then characterized using a wide variety of quantitative metrics grouped into four dimensions: (i) agricultural production; (ii) economics; (iii) territorial configuration, and; (iv) social characteristics. We found that production systems linked to mechanized agriculture predominate in the south of the state, while intensive farming is mainly found in the center of the state. Semi-intensive livestock farming is mainly located close to the southwest frontier and in the north of the state, where human occupation of the territory is not fully consolidated. This distributional pattern reflects the origins of the agricultural production system of Rondônia. Moreover, the characterization of the production systems provides insights into the pattern of occupation of the Amazon and the socioeconomic consequences of continuing agricultural expansion. Full article

(This article belongs to the Special Issue Land System Science)

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Open AccessReview

How Are Feedbacks Represented in Land Models?

by

,

,

and

Land 2016, 5(3), 29; https://doi.org/10.3390/land5030029 - 11 Sep 2016

Cited by 9 | Viewed by 6253

Abstract

Land systems are characterised by many feedbacks that can result in complex system behaviour. We defined feedbacks as the two-way influences between the land use system and a related system (e.g., climate, soils and markets), both of which are encompassed by the land [...] Read more.

Land systems are characterised by many feedbacks that can result in complex system behaviour. We defined feedbacks as the two-way influences between the land use system and a related system (e.g., climate, soils and markets), both of which are encompassed by the land system. Land models that include feedbacks thus probably more accurately mimic how land systems respond to, e.g., policy or climate change. However, representing feedbacks in land models is a challenge. We reviewed articles incorporating feedbacks into land models and analysed each with predefined indicators. We found that (1) most modelled feedbacks couple land use systems with transport, soil and market systems, while only a few include feedbacks between land use and social systems or climate systems; (2) equation-based land use models that follow a top-down approach prevail; and (3) feedbacks’ effects on system behaviour remain relatively unexplored. We recommend that land system modellers (1) consider feedbacks between land use systems and social systems; (2) adopt (bottom-up) approaches suited to incorporating spatial heterogeneity and better representing land use decision-making; and (3) pay more attention to nonlinear system behaviour and its implications for land system management and policy. Full article

(This article belongs to the Special Issue Land System Science)

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