Predicting animal abundance through local ecological knowledge: An internal validation using consensus analysis

Given the ongoing environmental degradation from local to global scales, it is fundamental to develop more efficient means of gathering data on species and ecosystems. Local ecological knowledge, in which local communities can consistently provide information on the status of animal species over time, has been shown to be effective. Several studies demonstrate that data gathered using local ecological knowledge (LEK)-based methods are comparable with data obtained from conventional methods (such as line transects and camera traps). Here, we employ a consensus analysis to validate and evaluate the accuracy of interview data on LEK. Additionally, we investigate the influence of social and bioecological variables on enhancing data quality. We interviewed 323 persons in 19 villages in the Western and Central Amazon to determine the level of consensus on the abundance of hunted and non-hunted forest species. These villages varied in size, socio-economic characteristics and in the experience with wildlife of their dwellers. Interviewees estimated the relative abundance of 101 species with a broad spectrum of bioecological characteristics using a four-point Likert scale. High consensus was found for species population abundance in all sampled villages and for 79.6% of interviewees. The village consensus of all species abundance pooled was negatively correlated with village population size. The consensus level was high regardless of the interviewees' hunting experience. Species that are more frequently hunted or are more apparent had greater consensus values; only two species presented a low consensus level, which are rare and solitary species. We show in our study in the Amazon that information gathered by local peoples, Indigenous as well as non-Indigenous, can be useful in understanding the status of animal species found within their environment. The high level of cultural consensus we describe likely arises from knowledge sharing and the strong connection between the persons interviewed and the forest. We suggest that consensus analysis can be used to validate LEK-generated data instead of comparing these types of data with information obtained by conventional methods

Congruence of local ecological knowledge (LEK)-based methods and line-transect surveys in estimating wildlife abundance in tropical forests

Effective estimation of wildlife population abundance is an important component of population monitoring, and ultimately essential for the development of conservation actions. Diurnal line-transect surveys are one of the most applied methods for abundance estimations. Local ecological knowledge (LEK) is empirically acquired through the observation of ecological processes by local people. LEK-based methods have only been recognized as valid scientific methods for surveying fauna abundance in the last three decades. However, the agreement between both methods has not been extensively analysed. We compared concomitant abundance data for 91 wild species (mammals, birds and tortoises) from diurnal line transects (9,221 km of trails) and a LEK-based method (291 structured interviews) at 18 sites in Central and Western Amazonia. We used biological and socioecological factors to assess the agreements and divergences between abundance indices obtained from both methods. We found a significant agreement of population abundance indices for diurnal and game species. This relationship was also positive regardless of species sociality (solitary or social), body size and locomotion mode (terrestrial and arboreal); and of sampled forest type (upland and flooded forests). Conversely, we did not find significant abundance covariances for nocturnal and non-game species. Despite the general agreement between methods, line transects were not effective at surveying many species occurring in the area, with 40.2% and 39.8% of all species being rarely and never detected in at least one of the survey sites. On the other hand, these species were widely reported by local informants to occur at intermediate to high abundances. Although LEK-based methods have been long neglected by ecologists, our comparative study demonstrated their effectiveness for estimating vertebrate abundance of a wide diversity of taxa and forest environments. This can be used simultaneously with line-transect surveys to calibrate abundance estimates and record species that are rarely sighted during surveys on foot, but that are often observed by local people during their daily extractive activities. Thus, the combination of local and scientific knowledge is a potential tool to improve our knowledge of tropical forest species and foster the development of effective strategies to meet biodiversity conservation goals

Predicting animal abundance through local ecological knowledge: An internal validation using consensus analysis

Given the ongoing environmental degradation from local to global scales, it is fundamental to develop more efficient means of gathering data on species and ecosystems. Local ecological knowledge, in which local communities can consistently provide information on the status of animal species over time, has been shown to be effective. Several studies demonstrate that data gathered using local ecological knowledge (LEK)‐based methods are comparable with data obtained from conventional methods (such as line transects and camera traps). Here, we employ a consensus analysis to validate and evaluate the accuracy of interview data on LEK. Additionally, we investigate the influence of social and bioecological variables on enhancing data quality. We interviewed 323 persons in 19 villages in the Western and Central Amazon to determine the level of consensus on the abundance of hunted and non‐hunted forest species. These villages varied in size, socio‐economic characteristics and in the experience with wildlife of their dwellers. Interviewees estimated the relative abundance of 101 species with a broad spectrum of bioecological characteristics using a four‐point Likert scale. High consensus was found for species population abundance in all sampled villages and for 79.6% of interviewees. The village consensus of all species abundance pooled was negatively correlated with village population size. The consensus level was high regardless of the interviewees' hunting experience. Species that are more frequently hunted or are more apparent had greater consensus values; only two species presented a low consensus level, which are rare and solitary species. We show in our study in the Amazon that information gathered by local peoples, Indigenous as well as non‐Indigenous, can be useful in understanding the status of animal species found within their environment. The high level of cultural consensus we describe likely arises from knowledge sharing and the strong connection between the persons interviewed and the forest. We suggest that consensus analysis can be used to validate LEK‐generated data instead of comparing these types of data with information obtained by conventional methods. Read the free Plain Language Summary for this article on the Journal blog

Involving local communities for effective citizen science: determining game species' reproductive status to assess hunting effects in tropical forests

These three datasets are related to the analyses conducted in the article "Involving local communities for effective citizen science: determining game species' reproductive status to assess hunting effects in tropical forests". The first dataset (1_Archive_Interviews_Pregnancy_Diagnoses_Final) consists of interviews through which diagnoses of reproductive status of lowland paca (Cuniculus paca) were performed by local people in the Amazon. The second dataset (2_Archive_Hunting_Registers_Pregnancy_Immatures) consists of all records of pacas hunted voluntarily collected by local people over a 17-years citizen science project in one of the study sites. The third dataset (3_Archive_Hunting_Registers_CPUE) consists of data on the catch-per-unit-effort of lowland paca hunting events in the same site over 17 years. Specific explanations of columns' attributes are presented in the sheet "Explanations" within each dataset. The study areas and the coordinates related to the dataset are: Amanã Sustainable Development Reserve: -64.538 W; -2,492 S Yavarí-Mirín River:-71,958 W; - 4,357 S Juruá River: -67,659 W; -5,517

Widespread use of traditional techniques by local people for hunting the yellow-footed tortoise (Chelonoidis denticulatus) across the Amazon

Understanding the repertoire of hunting techniques used by traditional peoples in tropical forests is crucial for recognizing the role of traditional knowledge in hunting activities, as well as assessing the impact of harvests on game species. We describe the hunting techniques used across Amazonia by Indigenous and non-Indigenous peoples for hunting yellow-footed tortoises (Chelonoidis denticulatus), one of the most consumed species in the biome. We interviewed 178 local people in 25 communities living in seven study areas in the Peruvian and Brazilian Amazon. We used a Principal Coordinate Analysis (PCoA) and Analysis of Similarity (ANOSIM) to compare the hunting techniques between ethnic groups and the ages of the interviewees. Four different techniques were reported: (1) trapping with bait (46%; n = 122); (2) hunting with dogs (35%; n = 92); (3) active searching (14 %; n = 37); and (4) visiting fruiting trees (5%; n = 14). Trapping with bait was alleged to be the most cost-effective technique by 67% of the interviewees. Among the baits used, 93% involved the use of wild species as rotten meat. Hunting with dogs was also frequently cited and involved eight different methods of training. The hunting techniques recorded were not significantly different among ethnic groups or generations. The consonance among the technique repertoire likely reflects a shared knowledge still in use across different cultural groups. There is a potential for applying the hunting techniques to large scale community-based monitoring and management programs, but the impact on additional species affected, such as species intentionally captured to be used as bait, should be considered. Local assessments and community-based management plans that incorporate traditional ecological knowledge are recommended to guarantee the maintenance of livelihoods and ensure the species' conservation in Amazonia

Predicting animal abundance through local ecological knowledge : An internal validation using consensus analysis

Given the ongoing environmental degradation from local to global scales, it is fundamental to develop more efficient means of gathering data on species and ecosystems. Local ecological knowledge, in which local communities can consistently provide information on the status of animal species over time, has been shown to be effective. Several studies demonstrate that data gathered using local ecological knowledge (LEK)-based methods are comparable with data obtained from conventional methods (such as line transects and camera traps). Here, we employ a consensus analysis to validate and evaluate the accuracy of interview data on LEK. Additionally, we investigate the influence of social and bioecological variables on enhancing data quality. We interviewed 323 persons in 19 villages in the Western and Central Amazon to determine the level of consensus on the abundance of hunted and non-hunted forest species. These villages varied in size, socio-economic characteristics and in the experience with wildlife of their dwellers. Interviewees estimated the relative abundance of 101 species with a broad spectrum of bioecological characteristics using a four-point Likert scale. High consensus was found for species population abundance in all sampled villages and for 79.6% of interviewees. The village consensus of all species abundance pooled was negatively correlated with village population size. The consensus level was high regardless of the interviewees' hunting experience. Species that are more frequently hunted or are more apparent had greater consensus values; only two species presented a low consensus level, which are rare and solitary species. We show in our study in the Amazon that information gathered by local peoples, Indigenous as well as non-Indigenous, can be useful in understanding the status of animal species found within their environment. The high level of cultural consensus we describe likely arises from knowledge sharing and the strong connection between the persons interviewed and the forest. We suggest that consensus analysis can be used to validate LEK-generated data instead of comparing these types of data with information obtained by conventional methods. Read the free Plain Language Summary for this article on the Journal blog