CoChat
Sign Up
Cited by 3,123Conservation, Biodiversity, and Resource ManagementLand Use and Ecosystem ServicesAgriculture, Land Use, Rural Development

Proximate Causes and Underlying Driving Forces of Tropical Deforestation

Open access
GEIST, HELMUT J., LAMBIN, ERIC F.·2002·BioScience
DOI 10.1641/0006-3568(2002)052[0143:pcaudf]2.0.co;2
Open this paper in CoChat — free accountOpen PDF

Abstract

One of the primary causes of global environmental change is tropical deforestation, but the question of what factors drive deforestation remains largely unanswered (NRC 1999). Various hypotheses have produced rich arguments, but empirical evidence on the causes of deforestation continues to be largely based on cross-national statistical analyses (Bilsborrow 1994, Brown and Pearce 1994, Williams 1994, Painter and Durham 1995, Sponsel et al. 1996, Murali and Hedge 1997, Rudel and Roper 1997, Fairhead and Leach 1998). In some cases, these analyses are based on debatable data on rates of forest cover change (Palo 1999). The two major, mutually exclusive—and still unsatisfactory—explanations for tropical deforestation are single-factor causation and irreducible complexity. On the one hand, proponents of single-factor causation suggest various primary causes, such as shifting cultivation (Amelung and Diehl 1992, Myers 1993, Rerkasem 1996, Ranjan and Upadhyay 1999) and population growth (Allen and Barnes 1985, Amelung and Diehl 1992, Cropper and Griffiths 1994, Ehrhardt-Martinez 1998, Mather and Needle 2000). On the other hand, correlations between deforestation and multiple causative factors are many and varied, revealing no distinct pattern (Rudel and Roper 1996, Bawa and Dayanandan 1997, Mather et al. 1998, Angelsen and Kaimowitz 1999). In addition to chronicling these attempts to identify general causes of deforestation through global-scale statistical analyses, the literature is rich in local-scale case studies investigating the causes and processes of forest cover change in specific localities. Our aim with this study is to generate from local-scale case studies a general understanding of the proximate causes and underlying driving forces of tropical deforestation while preserving the descriptive richness of these studies. Proximate causes are human activities or immediate actions at the local level, such as agricultural expansion, that originate from intended land use and directly impact forest cover. Underlying driving forces are fundamental social processes, such as human population dynamics or agricultural policies, that underpin the proximate causes and either operate at the local level or have an indirect impact from the national or global level. We analyzed the frequency of proximate causes and underlying driving forces of deforestation, including their interactions, as reported in 152 subnational case studies. We show that tropical deforestation is driven by identifiable regional patterns of causal factor synergies, of which the most prominent are economic factors, institutions, national policies, and remote influences (at the underlying level) driving agricultural expansion, wood extraction, and infrastructure extension (at the proximate level). Our findings reveal that prior studies have given too much emphasis to population growth and shifting cultivation as primary causes of deforestation. Data analysis Case studies of net losses of tropical forest cover (n = 152) were analyzed to determine whether the proximate causes and underlying driving forces of tropical deforestation fall into any patterns. Study areas range from a community to a multiprovince area, and cases span time periods from 1880 to 1996, with 1940 to 1990 being the most frequently covered period. The 152 cases of tropical deforestation were taken from 95 articles published in 40 journals covered by the citation index of the Institute for Scientific Information (Geist and Lambin 2001). The criteria for selecting studies were the following: quantification of the rates of forest-cover change; net loss of forest cover during at least part of the study period; investigation method based on quantitative data or in-depth field investigations; consideration of clearly named factors as potential causes of deforestation, including basic features of the socioeconomic setting and the natural resource endowment; and absence of obvious disciplinary bias. We assumed that each study revealed the actual causes of deforestation in the study area. Therefore, our comparative analysis of case studies evaluates which causal patterns leading to deforestation are most often found in different tropical regions. Four broad clusters of proximate causes were identified: agricultural expansion, wood extraction, infrastructure extension, and other factors. Each land use category was further subdivided; for example, agricultural expansion was divided into permanent cultivation, shifting cultivation, cattle ranching, and colonization (Figure 1). Underlying driving forces were categorized into five broad clusters: demographic, economic, technological, policy and institutional, and cultural factors. Each was further subdivided into specific factors; for example, cultural or sociopolitical factors were partitioned into public attitudes, values and beliefs, and individual or household behavior (Figure 1; Ledec 1985, Lambin 1994, Ojima et al. 1994, Turner et al. 1995,

Integrity signals

Registry

Crossref · 10.1641/0006-3568(2002)052[0143:pcaudf]2.0.co;2

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Causes for land use and land cover changes are multifactorial, with underlying political, institutional and economic factors driving agricultural expansion, resource extraction and infrastructure development.

    “The causes for LULCC are multifactorial, with underlying political, institutional and economic factors driving agricultural expansion, resource extraction and infrastructure development [22].”

    From Achieving global malaria eradication in changing landscapes (2021) · cites this paper as [22]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
GEIST, H. J., & LAMBIN, E. F.
Affiliations
UCLouvain (BE)
Venue
BioScience
Publisher
Oxford University Press (OUP)
Published
2002
Volume
52
Issue
2
Pages
143
ISSN
0006-3568 (ISSN-L)
DOI
10.1641/0006-3568(2002)052[0143:pcaudf]2.0.co;2
OpenAlex
W1918072595
Cited by
3,123
References
29
Citations by year
2026: 105 · 2025: 119 · 2024: 131 · 2023: 155 · 2022: 142 · 2021: 168 · 2020: 176 · 2019: 173 · 2018: 160 · 2017: 167 · 2016: 184 · 2015: 179 · 2014: 168 · 2013: 151 · 2012: 162
FWCI
40.43
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • BioScience (publishedVersion, other-oa)
  • BioOne Complete (BioOne) (submittedVersion)
  • DIAL (Catholic University of Leuven) (submittedVersion)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Conservation, Biodiversity, and Resource Management
  • Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
  • Life Sciences › Agricultural and Biological Sciences › General Agricultural and Biological Sciences › Agriculture, Land Use, Rural Development
Keywords
tropical deforestation, proximate cause, forest cover change, agricultural expansion, shifting cultivation, population growth, land use change, agricultural policy, social processes, deforestation drivers, tropical forests, population dynamics, agricultural intensification, rural livelihoods, rural-urban migration

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review