Divisions of Biostatistics and Epidemiology, School of Public Health, University of California, Berkeley, California, United States of America.
Department of Mathematics and Statistics, University of Victoria, Victoria, British Columbia, Canada.
PLoS Comput Biol. 2022 Dec 12;18(12):e1010755. doi: 10.1371/journal.pcbi.1010755. eCollection 2022 Dec.
Close-kin mark-recapture (CKMR) methods have recently been used to infer demographic parameters such as census population size and survival for fish of interest to fisheries and conservation. These methods have advantages over traditional mark-recapture methods as the mark is genetic, removing the need for physical marking and recapturing that may interfere with parameter estimation. For mosquitoes, the spatial distribution of close-kin pairs has been used to estimate mean dispersal distance, of relevance to vector-borne disease transmission and novel biocontrol strategies. Here, we extend CKMR methods to the life history of mosquitoes and comparable insects. We derive kinship probabilities for mother-offspring, father-offspring, full-sibling and half-sibling pairs, where an individual in each pair may be a larva, pupa or adult. A pseudo-likelihood approach is used to combine the marginal probabilities of all kinship pairs. To test the effectiveness of this approach at estimating mosquito demographic parameters, we develop an individual-based model of mosquito life history incorporating egg, larva, pupa and adult life stages. The simulation labels each individual with a unique identification number, enabling close-kin relationships to be inferred for sampled individuals. Using the dengue vector Aedes aegypti as a case study, we find the CKMR approach provides unbiased estimates of adult census population size, adult and larval mortality rates, and larval life stage duration for logistically feasible sampling schemes. Considering a simulated population of 3,000 adult mosquitoes, estimation of adult parameters is accurate when ca. 40 adult females are sampled biweekly over a three month period. Estimation of larval parameters is accurate when adult sampling is supplemented with ca. 120 larvae sampled biweekly over the same period. The methods are also effective at detecting intervention-induced increases in adult mortality and decreases in population size. As the cost of genome sequencing declines, CKMR holds great promise for characterizing the demography of mosquitoes and comparable insects of epidemiological and agricultural significance.
近亲标记重捕 (CKMR) 方法最近被用于推断鱼类种群数量和生存等渔业和保护相关的种群参数。这些方法相对于传统的标记重捕方法具有优势，因为标记是遗传的，不需要进行物理标记和重捕，这可能会干扰参数估计。对于蚊子，近亲对的空间分布已被用于估计平均扩散距离，这对于媒介传播疾病的传播和新型生物防治策略很重要。在这里，我们将 CKMR 方法扩展到蚊子和类似昆虫的生活史中。我们推导了亲代 - 子代、父代 - 子代、全同胞和半同胞对的亲缘关系概率，其中每对个体可以是幼虫、蛹或成虫。使用拟似然方法组合所有亲缘关系对的边际概率。为了测试这种方法在估计蚊子种群参数方面的有效性，我们开发了一个基于个体的蚊子生活史模型，其中包含卵、幼虫、蛹和成虫阶段。该模拟为每个个体分配一个唯一的识别号码，以便推断抽样个体的近亲关系。以登革热媒介埃及伊蚊为例，我们发现 CKMR 方法为逻辑上可行的抽样方案提供了成虫种群数量、成虫和幼虫死亡率以及幼虫生活阶段持续时间的无偏估计。对于 3000 只成年蚊子的模拟种群，当每两周在三个月内对大约 40 只成年雌性蚊子进行抽样时，对成年参数的估计是准确的。当在同一时期内每两周对大约 120 只幼虫进行抽样来补充成虫抽样时，对幼虫参数的估计是准确的。该方法还可以有效地检测干预引起的成虫死亡率增加和种群数量减少。随着基因组测序成本的降低，CKMR 有望用于描述蚊子和具有流行病学和农业意义的类似昆虫的种群动态。
