Jones Benjamin L H, Santos Rolando O, James W Ryan, Shephard Samuel, Adams Aaron J, Boucek Ross E, Coals Lucy, Costa Sophia V, Cullen-Unsworth Leanne C, Rehage Jennifer S
Project Seagrass, Bridgend, UK.
Department of Earth and Environment, Institute of Environment, Florida International University, Miami, FL, USA.
Sci Rep. 2025 Jan 2;15(1):440. doi: 10.1038/s41598-024-84970-4.
Embracing local knowledge is vital to conserve and manage biodiversity, yet frameworks to do so are lacking. We need to understand which, and how many knowledge holders are needed to ensure that management recommendations arising from local knowledge are not skewed towards the most vocal individuals. Here, we apply a Wisdom of Crowds framework to a data-poor recreational catch-and-release fishery, where individuals interact with natural resources in different ways. We aimed to test whether estimates of fishing quality from diverse groups (multiple ages and years of experience), were better than estimates provided by homogenous groups and whether thresholds exist for the number of individuals needed to capture estimates. We found that diversity matters; by using random subsampling combined with saturation principles, we determine that targeting 31% of the survey sample size captured 75% of unique responses. Estimates from small diverse subsets of this size outperformed most estimates from homogenous groups; sufficiently diverse small crowds are just as effective as large crowds in estimating ecological state. We advocate for more diverse knowledge holders in local knowledge research and application.
接纳当地知识对于保护和管理生物多样性至关重要，但目前缺乏这样做的框架。我们需要了解需要哪些知识持有者以及多少知识持有者，以确保源自当地知识的管理建议不会偏向于最直言不讳的个体。在此，我们将群体智慧框架应用于一个数据匮乏的休闲钓放渔业，在该渔业中，个体以不同方式与自然资源相互作用。我们旨在测试来自不同群体（多个年龄和多年经验）的捕鱼质量估计是否优于同质群体提供的估计，以及获取估计所需的个体数量是否存在阈值。我们发现多样性很重要；通过将随机子抽样与饱和度原则相结合，我们确定以调查样本量的31%为目标可获取75%的独特回答。来自这种规模的小型多样化子集的估计优于大多数同质群体的估计；足够多样化的小群体在估计生态状态方面与大群体同样有效。我们主张在当地知识研究和应用中纳入更多样化的知识持有者。
