Land Cover Change in Agroforestry: Shade Coffee in El Salvador

Blackman, Allen; Ávalos-Sartorio, Beatriz; Chow, Jeffrey

doi:10.3368/le.88.1.75

Cited by 22 publications

(17 citation statements)

References 31 publications

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“…Proximity to roads and cities decreases forest cover consistently, but not universally. In contrast to natural forests, proximity to cities has been found to increase the presence of shade-grown coffee in Mexico (Blackman 2008) and El Salvador (Blackman 2012) and green space for urban residents in China (Gong 2013). Getahun (2013) found that regions in Ethiopia that are more integrated with cities are less reliant on clearing for subsistence agriculture as they have more economic alternatives.…”

Section: Resultsmentioning

confidence: 99%

What Drives Deforestation and What Stops it? A Meta-Analysis of Spatially Explicit Econometric Studies

Ferretti-Gallon

Busch

2014

SSRN Journal

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We have constructed a comprehensive database of 117 spatially explicit econometric studies of deforestation published in peer-reviewed academic journals from 1996-2013. We present a metaanalysis of what drives deforestation and what stops it, based on the signs and significance of 5909 coefficients in 554 multivariate analyses. We find that forests are more likely to be cleared where economic returns to agriculture and pasture are higher, either due to more favorable climatological and topographic conditions, or due to lower costs of clearing forest and transporting products to market. Timber activity, land tenure security, and community demographics do not show a consistent association with either higher or lower deforestation. Population is consistently associated with greater deforestation, and poverty is consistently associated with lower deforestation, but in both cases endogeneity makes a causal link difficult to infer. Promising approaches for stopping deforestation include reducing the intrusion of road networks into remote forested areas; targeting protected areas to regions where forests face higher threat; tying rural income support to the maintenance of forest resources through payments for ecosystem services; and insulating the forest frontier from the price effects of demand for agricultural commodities.JEL Codes: Q15,Q23,Q24

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Section: Resultsmentioning

confidence: 99%

What Drives Deforestation and What Stops it? A Meta-Analysis of Spatially Explicit Econometric Studies

Ferretti-Gallon

Busch

2014

SSRN Journal

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“…Reported values for ρ ranging from 0.112 to 0.328 depending on areas sampled [43]. Differences in approaches, including the fact that we looked at WTH, as compared to drivers of land clearing [43], prevent direct comparisons with our results (0.167–0.168). In our study average distances from the Delaunay triangulation ranged from 2.6 km to 42.8km.…”

Section: Discussionmentioning

confidence: 99%

“…The spatial dependence matrix W was derived d first in order to estimate model parameters β. W was computationally estimated following a Delaunay triangularization scheme with row standardization [78]. Delaunay triangularization has been used in spatial autoregressive models of land uses to help identify nearby owners [43]. Parcel centroids served as points in a two-dimensional latitude-longitude space with Delaunay neighbors identified as two vertex points of the same triangle.…”

Section: Methodsmentioning

confidence: 99%

“…However, for this stream of studies, researchers seldom incorporated both social and economic factors in their models of management behavior (see [42] for an exception). Some [43] have modeled land cover changes in managed forest ecosystems incorporating socio-economic variables including travel distance to markets, land enrolled in a farming cooperative and a measure of ownership size but did not identify actual decision-makers behind land use choices. The second line of research has focused on modeling landowners’ management preferences under the theoretical framework of random utility theory [44].…”

Section: Literature Reviewmentioning

confidence: 99%

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Proximal Association of Land Management Preferences: Evidence from Family Forest Owners

2017

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Individual behavior is influenced by factors intrinsic to the decision-maker but also associated with other individuals and their ownerships with such relationship intensified by geographic proximity. The land management literature is scarce in the spatially integrated analysis of biophysical and socio-economic data. Localized land management decisions are likely driven by spatially-explicit but often unobserved resource conditions, influenced by an individual’s own characteristics, proximal lands and fellow owners. This study examined stated choices over the management of family-owned forests as an example of a resource that captures strong pecuniary and non-pecuniary values with identifiable decision makers. An autoregressive model controlled for spatially autocorrelated willingness-to-harvest (WTH) responses using a sample of residential and absentee family forest owners from the U.S. State of Missouri. WTH responses were largely explained by affective, cognitive and experience variables including timber production objectives and past harvest experience. Demographic variables, including income and age, were associated with WTH and helped define socially-proximal groups. The group of closest identity was comprised of resident males over 55 years of age with annual income of at least $50,000. Spatially-explicit models showed that indirect impacts, capturing spillover associations, on average accounted for 14% of total marginal impacts among statistically significant explanatory variables. We argue that not all proximal family forest owners are equal and owners-in-absentia have discernible differences in WTH preferences with important implications for public policy and future research.

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“…Among them are (1) difficult application of machinery for harvesting and planting, (2) greater requirement for technical knowledge, and (3) less benefits from Beconomy of scale^effects [75,76], e.g., in processing, transporting, and harvesting harvests. Furthermore, whether yields actually do increase, or possibly even decrease, is far from certain and requires quantitative study.…”

Section: Costsmentioning

confidence: 99%

Biodiversity Function and Resilience in Tropical Agroforestry Systems Including Shifting Cultivation

Norgrove

Beck

2016

Curr Forestry Rep

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Agroforestry systems potentially deliver win-win solutions to production and biodiversity conservation in the tropics, but they need to be adapted to farmers' needs. We reviewed the literature on functional roles of biodiversity and resilience in tropical agroforestry systems, and we evaluated the evidence base for the beneficial role of biodiversity on yield, and effects of farmer management practices. Most studies investigated the biodiversity of taxa assumed to have positive functions for farmers. Shaded commodities and shifting cultivation were the systems most frequently assessed. Half of studies investigated plants, while Hymenoptera and birds were other major groups. Many agroforests had lower diversity than forest, while less than half had higher diversity than agriculture. The effects of management within systems were rarely addressed, with shade level the most frequent factor. Papers on resilience, mainly from shifting cultivation systems, showed the positive influence of adjacent old-growth forest to biodiversity, and the negative effects of tillage. Better reporting of results for meta-analyses, and long-term experiments on key questions are needed to evaluate the potential of agroforestry more thoroughly.

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Land Cover Change in Agroforestry: Shade Coffee in El Salvador

Cited by 22 publications

References 31 publications

What Drives Deforestation and What Stops it? A Meta-Analysis of Spatially Explicit Econometric Studies

What Drives Deforestation and What Stops it? A Meta-Analysis of Spatially Explicit Econometric Studies

Proximal Association of Land Management Preferences: Evidence from Family Forest Owners

Biodiversity Function and Resilience in Tropical Agroforestry Systems Including Shifting Cultivation

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