Local soil classification and comparison of indigenous and technical soil maps in a Mesoamerican community using spatial analysis

Barrera‐Bassols, Narciso; Zinck, J. A.; Ranst, Éric Van

doi:10.1016/j.geoderma.2005.11.010

Cited by 43 publications

(44 citation statements)

References 18 publications

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“…Their knowledge can offer many insights to formulate sustainable management of soils [13,16,17]. These days, the value of FSK has received considerable attention by many scientists [7,12,16,17]. Its integration with scientific approach is socially acceptable, ecologically sustainable and economically viable [7,17]; and also it is believed to overcome the shortcomings of scientific intervention while performing under wider ranges [3,17].…”

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“…These days, the value of FSK has received considerable attention by many scientists [7,12,16,17]. Its integration with scientific approach is socially acceptable, ecologically sustainable and economically viable [7,17]; and also it is believed to overcome the shortcomings of scientific intervention while performing under wider ranges [3,17]. The FSK is also referred as local, traditional, folk, native or indigenous soil knowledge [7].…”

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Farmers’ soil knowledge, fertility management logic and its linkage with scientifically analyzed soil properties in southern Ethiopia

2017

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Background: Farmers' locally have acquired knowledge from generations of experience and experimentation that fit local conditions. Yet, the scientific approach less used farmers' soil knowledge (FSK) and site-specific soil information. The objectives of this study were to investigate FSK and rationality; to demonstrate how FSK relates to scientifically analyzed soil properties; and to explore the implemented soil management practices and crop performances in selected districts of Wolaita zone, southern Ethiopia. A total of 789 farmers were included, and their fields were evaluated. Data on farmer's soil nomenclature, soil physicochemical property, soil fertility management practices and crop yield performance were recorded and analyzed.Results: Farmers describe and classify their soils using holistic approach. Soil nomenclature and classification indicators are relatively homogeneous over large area. Accordingly, seven soil types common over large area were identified. Mostly, soil types perceived fertile by farmers (e.g., Arrada bita) were found better in measured physicochemical properties than infertile soil types (e.g., Lada bita, Zo' o bita). Simple regression analysis revealed a declining trends of soil properties with a decrease in fertility of farmers soil types such as soil bulk density (r 2 = 0.78), pH (r 2 = 0.53), available phosphorous (r 2 = 0.83), total exchangeable bases (r 2 = 0.71), copper (r 2 = 0.64) and zinc (r 2 = 0.69). Farmers are rational to allocate the scarce fertilizers. They apply more chemical fertilizer when soil type was getting poor in soil fertility (r 2 = 0.61), whereas it was opposite for manure (r 2 = 0.85). Furthermore, crop response and farmers' soil type also demonstrated an observable relationship where yield was declining with a decrease in fertility level of farmers' soil types. Conclusions:Farmers understand within farm soil variability and exploit soil fertility differences of their field. This is supported with noticeable relationship with scientifically analyzed soil properties, fertility management strategy and crop responses. It suggests that FSK is relevant for site-specific soil management. Yet, FSK is deficient to identify yieldlimiting nutrients, implying it has to be complemented with scientific soil knowledge. Additionally, further investigation to systematically link both approaches is also suggested.

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Farmers’ soil knowledge, fertility management logic and its linkage with scientifically analyzed soil properties in southern Ethiopia

2017

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“…Sugeriram, assim, que o conhecimento científico e o das comunidades locais são complementares. Essa ideia também foi defendida por Barrera-Bassols et al (2006), que fizeram uma sobreposição entre mapas de solos gerados por meio de critérios técnicos e outro gerado pelo conhecimento de uma comunidade indígena mexicana, onde foi verificada uma alta correlação em 25 % das áreas.…”

Section: Sistemática Yanomami Para Classificação Dos Solos E Ambienteunclassified

Solos da área indígena Yanomami no médio Rio Catrimani, Roraima

Melo

Francelino

Uchôa³

et al. 2010

Rev. Bras. Ciênc. Solo

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Vieira dos Santos (6) RESUMOEm Roraima, a distribuição espacial das populações indígenas identifica um cenário de busca constante de solos capazes de sustentar uma agricultura itinerante. Este trabalho teve como objetivo estabelecer relação entre a compreensão dos solos por parte dos Yanomami da região do médio Catrimani e o Sistema Brasileiro de Classificação de Solos, bem como avaliar o seu tipo de uso em função de análises químicas para diagnóstico da fertilidade do solo. O trabalho foi executado em duas etapas. A primeira consistiu em visitas a oito malocas para estudar os solos. Foram coletadas amostras em trincheiras até 1,50 m de profundidade para análise e classificação dos solos e (em prospecções com o trado) nas profundidades de 0-10 a 10-30 cm, em 21 tipos de uso agrícola, e da área de floresta para análises químicas de fertilidade. A segunda fase foi uma oficina, abordando os sistemas de exploração agrícola, com duração de 20 h. Focalizou-se a discussão sobre a compreensão do meio ambiente (Urihi) ( 7) e sistemas de produção agrícolas e sobre a importância do uso correto do conhecimento dos solos. Os solos são denominados pelos Yanomami em função das características morfológicas, pelos teores de matéria orgânica e pela presença de minhocas, e da posição na paisagem -a escolha para agricultura é fundamentada nessas características. As práticas agrícolas consistem da derrubada da mata nativa, queima e plantio das culturas em separado. Os solos descritos na área foram: Argissolo Vermelho-Amarelo (Maxita a uuxi wakë axi), Argissolo Amarelo (Maxita a axi), Latossolo Amarelo (Maxita a axi) e Plintossolo (Maxita a axi a maamaxipë).(1) Recebido para publicação em julho de 2009 e aprovado em fevereiro de 2010.(2) Professor Adjunto, Departamento de Solos e Engenharia Agrícola, Programa de Pós-Graduação em Agronomia (POSAGRO), Universidade Federal de Roraima -UFRR. CEP 60310-250 Boa Vista (RR). E-mail: valdinar@yahoo.com.br (3) Professor Adjunto, Departamento de Silvicultura, Universidade Federal Rural do Rio de Janeiro -UFRRJ. BR 465, Km 7, CEP 23890-000 Seropédica (RJ). E-mail: marciorocha@ufrrj.br (4) Professora Associada, Departamento de Solos e Engenharia Agrícola, POSAGRO-UFRR. E-mail: scpuchoa@click21.com.br (5) Doutoranda em Ciências Ambientais, Instituto de Floresta, UFRRJ. E-mail: salamene@yahoo.com.br (6) Professora Associada, Departamento de Fitotecnia, UFRR. E-mail: celidasocorro@uol.com.br (7) Os termos em itálico são escritos na linguagem yanomami.

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“…Diverse studies on FLC have shown that it is a good alternative to relate them to physical and chemical soil properties (technical concept) and their formation factors, as well as color, texture, drainage, agricultural practices, type of vegetation, and crop (Ericksen and Ardon, 2003;Barrera-Bassols et al, 2006;LiconaVargas et al, 2006;Cruz et al, 2008). Also, it is a rapid, inexpensive methodology which does not require high specialization of the personnel in cartography, as opposed to technical soil surveys (Ortiz, 1999).…”

Section: Introductionmentioning

confidence: 99%

Digital Mapping of Farmland Classes in Three Landscape in Mexico

Cruz-Cárdenas

Solorio

Trejo

et al. 2010

J. Soil Sci. Plant Nutr.

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The cartography of farmland classes allows generating land maps, using a methodology based on local knowledge, rapidly and at low cost, and with a greater number of cartographic units than conventional soil surveys maps. However, the results found when producing these maps with automated cartography techniques are contrasting. Precision and accuracy were evaluated in 324 computer generated farmland class (FLC) maps by applying the Inverse Distance Weighted (IDW) interpolation model. These maps were obtained by varying the sample size for the training, its spatial design, and the Power value of the interpolator. Moreover, the effort needed to obtain maps with acceptable reliability was quantified. The procedure was applied to FLC maps obtained from surveys with producers from three contrasting environmental zones in Mexico. The results show that the best sampling scheme in the three areas is the systematic sampling, and Power 8, giving the maps with the highest reliability. Through the criterion of map reliability and effort needed for sampling, the recommended sample size is 10% to 25% of the total plots.

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Local soil classification and comparison of indigenous and technical soil maps in a Mesoamerican community using spatial analysis

Cited by 43 publications

References 18 publications

Farmers’ soil knowledge, fertility management logic and its linkage with scientifically analyzed soil properties in southern Ethiopia

Farmers’ soil knowledge, fertility management logic and its linkage with scientifically analyzed soil properties in southern Ethiopia

Solos da área indígena Yanomami no médio Rio Catrimani, Roraima

Digital Mapping of Farmland Classes in Three Landscape in Mexico

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