Revisiting the ‘cornerstone of Amazonian conservation’: a socioecological assessment of Brazil nut exploitation

Guariguata, Manuel R.; Cronkleton, P.; Duchelle, A.E.; Zuidema, Pieter A.

doi:10.1007/s10531-017-1355-3

Cited by 64 publications

(67 citation statements)

References 92 publications

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“…Partelow 2015, Partelow and Boda 2015, Guevara et al 2016, Oviedo and Bursztyn 2016, Blythe et al 2017, London et al 2017, Nakandakari et al 2017, Partelow et al 2018a) and forestry (Fleischman et al 2010, Oberlack et al 2015, Davenport et al 2016. However, use of the framework has expanded beyond those resource-use sectors to general food production systems (Marshall 2015), aquaculture systems (Partelow et al 2018b), terrestrial conservation and rangeland management (Falk et al 2012, Risvoll et al 2014, Baur and Binder 2015, Addison and Greiner 2016, Taggart-Hodge and Schoon 2016, Yandle et al 2016, Guariguata et al 2017, watershed management (Madrigal et al 2011, Bal et al 2011, Nagendra and Ostrom 2014, Villamayor-Tomas et al 2014, Bennett and Gosnell 2015, Naiga et al 2015, Silva et al 2015, Falk et al 2016, Hileman et al 2016, marine conservation and marine ecosystem management (Cinner et al 2012, Schlüter et al 2013, Stevenson and Tissot 2014, Ban et al 2015, 2017, Williams and Tai 2016, coastal development (Kanwar et al 2016, Schlüter et al 2019, energy systems …”

Section: Trends and Gaps In The Social-ecological Systems Framework Lmentioning

confidence: 99%

A review of the social-ecological systems framework: applications, methods, modifications, and challenges

Partelow¹

2018

E&S

235

136

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The social-ecological systems framework (SESF) is arguably the most comprehensive conceptual framework for diagnosing interactions and outcomes in social-ecological systems (SES). This article systematically reviews the literature applying and developing the SESF and discusses methodological challenges for its continued use and development. Six types of research approaches using the SESF are identified, as well as the context of application, types of data used, and commonly associated concepts. The frequency of how each second-tier variable is used across articles is analyzed. A summary list of indicators used to measure each second-tier variable is provided. Articles suggesting modifications to the framework are summarized and linked to the specific variables. The discussion reflects on the results and focuses on methodological challenges for applying the framework. First, how the SESF is historically related to commons and collective action research. This affects its continued development in relation to inclusion criteria for variable modification and discourse in the literature. The framework may evolve into separate modified versions for specific resource use sectors (e.g., forestry, fisheries, food production, etc.), and a general framework would aggregate the generalizable commonalities between them. Methodological challenges for applying the SESF are discussed related to research design, transparency, and cross-case comparison. These are referred to as "methodological gaps" that allow the framework to be malleable to context but create transparency, comparability, and data abstraction issues. These include the variable-definition gap, variable-indicator gap, the indicator-measurement gap, and the data transformation gap. A benefit of the framework has been its ability to be malleable and multipurpose, bringing a welcomed pluralism of methods, data, and associated concepts. However, pluralism creates challenges for synthesis, data comparison, and mutually agreed-upon methods for modifications. Databases are a promising direction forward to help solve this problem. In conclusion, future research is discussed by reflecting on the different ways the SESF may continue to be a useful tool through (1) being a general but adaptable framework, (2) enabling comparison, and (3) as a diagnostic tool for theory building.

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Section: Trends and Gaps In The Social-ecological Systems Framework Lmentioning

confidence: 99%

A review of the social-ecological systems framework: applications, methods, modifications, and challenges

Partelow¹

2018

E&S

235

136

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“…excelsa (Guariguata et al 2017). Forest types in the region are diverse because of elevation, geology, and climatic and soil differences, yet most of the region falls in the submontane range of 100-300 masl.…”

Section: Discussionmentioning

confidence: 99%

“…This is an especially important finding because B. excelsa populations are strongly manipulated by humans: positively due to silvicultural management (Kainer et al 2014) and negatively because of potentially unsustainable seed harvesting (Peres et al 2003), and in all likelihood because of illegal logging and fire. As a result, B. excelsa represents a unique case in which the policy and economics of nontimber forest harvests may strongly affect regional carbon stocks (Guariguata et al 2017). …”

Section: Introductionmentioning

confidence: 99%

Economically important species dominate aboveground carbon storage in forests of southwestern Amazonia

Selaya¹,

Zuidema²,

Baraloto³

et al. 2017

E&S

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ABSTRACT. Tree species in tropical forests provide economically important goods and ecosystem services. In submontane forests of southwestern Amazonia, we investigated the degree to which tree species important for subsistence and trade contribute to aboveground carbon storage (AGC). We used 41 1-hectare plots to determine the species abundance, basal area, and AGC of stems > 10 cm diameter at breast height (dbh). Economically important taxa were classified using ethnobotanical studies and according to their stem density. These taxa (n = 263) accounted for 45% of total stems, 53% of total basal area, and 56% of total AGC, significantly more than taxa with minor or unknown uses (Welch test at p < 0.05). Taxa with 1-2 stems per hectare, or with fewer than 1 stem per hectare (common and rare) accounted for 35% of total AGC, more than the 22% accounted for by dominant taxa. High basal area had a greater impact on AGC than abundance in economic taxa because their populations are skewed to adult trees. Size in these taxa had a median dbh > 40 cm and few stems in regeneration classes of dbh < 10 to 20 cm (e.g., Bertholletia excelsa, Cariniana spp., Cedrelinga spp., Ceiba spp., Dipteryx spp.), whereas dominant Tetragastris spp., and Pseudolmedia spp. had most stems in low diameter classes and a median diameter of < 30 cm. Bertholletia excelsa, with 1.5 stems per hectare, showed the highest basal area of any species and accounted for 9% of AGC (11 Mg/ha), twice that of the second-ranking species. Our study shows that economic importance and carbon stocks in trees are closely linked in southwestern Amazonia. Unplanned harvests can disrupt synergistic dual roles altering carbon stocks temporally or permanently. Precautionary measures based on species ecology, demography, and regeneration traits should be at the forefront of REDD+ to reconcile maximum harvesting limits, biodiversity conservation, and sustainable forest management.

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“…Amazon-nut is legally protected and one of the most important nontimber forest product (NTFP), on which tens of thousands of local people depend, mainly in Brazil, Bolivia, and Peru (Guariguata, Cronkleton, Duchelle, & Zuidema, 2017). The fruit's success is recently attributed to health benefits offered by the seeds rich in selenium and other micronutrients (Cardoso, Duarte, Reis, & Cozzolino, 2017).…”

Section: Amazon-nut Modeling Distributionmentioning

confidence: 99%

Strategies to optimize modeling habitat suitability of Bertholletia excelsa in the Pan‐Amazonia

Tourne

Ballester

James

et al. 2019

Ecology and Evolution

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AimAmazon‐nut (Bertholletia excelsa) is a hyperdominant and protected tree species, playing a keystone role in nutrient cycling and ecosystem service provision in Amazonia. Our main goal was to develop a robust habitat suitability model of Amazon‐nut and to identify the most important predictor variables to support conservation and tree planting decisions.LocalizationAmazon region, South America.MethodsWe collected 3,325 unique Amazon‐nut records and assembled >100 spatial predictor variables organized across climatic, edaphic, and geophysical categories. We compared suitability models using variables (a) selected through statistical techniques; (b) recommended by experts; and (c) integrating both approaches (a and b). We applied different spatial filtering scenarios to reduce overfitting. We additionally fine‐tuned MAXENT settings to our data. The best model was selected through quantitative and qualitative assessments.ResultsPrincipal component analysis based on expert recommendations was the most appropriate method for predictor selection. Elevation, coarse soil fragments, clay, slope, and annual potential evapotranspiration were the most important predictors. Their relative contribution to the best model amounted to 75%. Filtering of the presences within a radius of 10 km displayed lowest overfitting, a satisfactory omission rate and the most symmetric distribution curve. Our findings suggest that under current environmental conditions, suitable habitat for Amazon‐nut is found across 2.3 million km2, that is, 32% of the Amazon Biome.Main conclusionThe combination of statistical techniques with expert knowledge improved the quality of our suitability model. Topographic and soil variables were the most important predictors. The combination of predictor variable selection, fine‐tuning of model parameters and spatial filtering was critical for the construction of a reliable habitat suitability model.

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Revisiting the ‘cornerstone of Amazonian conservation’: a socioecological assessment of Brazil nut exploitation

Cited by 64 publications

References 92 publications

A review of the social-ecological systems framework: applications, methods, modifications, and challenges

A review of the social-ecological systems framework: applications, methods, modifications, and challenges

Economically important species dominate aboveground carbon storage in forests of southwestern Amazonia

Strategies to optimize modeling habitat suitability of Bertholletia excelsa in the Pan‐Amazonia

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