Socioeconomic and fishery factors in small-scale inland fishery patterns in the Usumacinta basin, Mexico
Socioemvironmental factors and inland fisheries
DOI:
https://doi.org/10.24275/uam/izt/dcbs/hidro/2021v31n2/MendozaKeywords:
conditional inference tree, inland fisheries, socio-environmental systemsAbstract
The objective of this research was to infer what are the potential socioeconomic and fishery factors that generate differences in small-scale fisheries at the local level, using as model communities of Chiapas (Benemérito de las Américas-BAM and Frontera Corozal, jungle area) and Tabasco (San Pedro, Balancán and Tenosique, floodplain area) in the Usumacinta basin, Mexico. Recognizing the influence and interaction of local socioeconomic factors within fishery models will allow a management considering the particularities of each region or community. The data were obtained through fisheries surveys and sampling surveys, carried out in 2015 and 2017-2018. Data were analyzed with conditional inference trees (AIC). Due to the socio-ecological nature of fisheries, which includes many factors, two AIC were used, one to analyze socio-economic aspects and the other to analyze fisheries aspects. The socioeconomic AIC indicated that the most important variable of division between communities was the destination of the fishery product, where BAM is separated, with most of the catches for self-consumption; the age of the fishermen, schooling and marital status were also important to separate the communities. The accuracy of the socioeconomic AIC was 61.0±7.0% (95% confidence). The fishery AIC also indicated that BAM was different, obtaining the highest average catch rate (61.76±95.83 kg/day of fishing) in 2015, without distinction of species. The catches were composed of 23 species of fish and two of crustaceans, caught with seven fishing gear, the gillnet was the most frequent. Our results highlight the complexity and diversity of small-scale freshwater fisheries on local geographical scales and the importance of applying complex analysis methods to identify patterns and differences that explain the behavior of socioeconomic processes.
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