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<p>Reliable methods for tracking changes in population abundance are crucial for effective wildlife management. We monitored a population of Alpine marmots (<i>Marmota marmota</i>) in Stelvio National Park (Italian Alps) over an 8-year period, from 2017 to 2024. Absolute abundance estimates were obtained by analyzing 180 individual capture histories using robust-design CMR models. Each year, six Independent Double Observer (IDO) sessions were conducted shortly after capture to obtain session-specific abundance estimates using Chapman’s estimator, which were averaged in each year using Cochran’s method. In addition, the IDO raw data were used to derive the average and maximum number of marmots counted by both observers within each year. We then evaluated the performance of IDO and simple combinations of independent counts against benchmark CMR estimates. The average IDO obtained using Cochran’s method underestimated population size by 55% (95% CI: 53–58%) compared to CMR estimates, likely reflecting availability bias, as the marmot’s burrowing behavior limits their exposure to detection during sampling. Despite this, IDO and CMR were strongly and positively correlated (r = 0.88; rho = 0.90), and their relationship, modeled through a log–log regression, explained about 80% of the variance. In contrast, simple counts correlated only moderately (averaged counts: r = 0.74; rho = 0.88) or weakly (maximum counts: r = 0.39; rho = 0.33) with CMR estimates. Their corresponding log–log models explained substantially less variation (51% and 8% respectively). Our findings suggest that IDO is a reliable method for tracking numerical variation in marmot populations, although it revealed a modest&#xa0;tendency toward saturation, with increasing underestimation of relative abundance at higher densities. IDO outperformed non-probabilistic methods in detecting population trends, likely due to its ability to adjust for detection probability – though some assumptions may not have been fully met. Replicating this study in other species within the Marmotini tribe is needed to assess IDO’s performance across different ecological contexts.</p>

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A double observer approach for tracking the abundance of Alpine marmot

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Luca Corlatti,
  • Filippo Zibordi,
  • Franco Rizzolli,
  • Marta Gandolfi,
  • Elena Morocutti,
  • Luca Pedrotti

摘要

Reliable methods for tracking changes in population abundance are crucial for effective wildlife management. We monitored a population of Alpine marmots (Marmota marmota) in Stelvio National Park (Italian Alps) over an 8-year period, from 2017 to 2024. Absolute abundance estimates were obtained by analyzing 180 individual capture histories using robust-design CMR models. Each year, six Independent Double Observer (IDO) sessions were conducted shortly after capture to obtain session-specific abundance estimates using Chapman’s estimator, which were averaged in each year using Cochran’s method. In addition, the IDO raw data were used to derive the average and maximum number of marmots counted by both observers within each year. We then evaluated the performance of IDO and simple combinations of independent counts against benchmark CMR estimates. The average IDO obtained using Cochran’s method underestimated population size by 55% (95% CI: 53–58%) compared to CMR estimates, likely reflecting availability bias, as the marmot’s burrowing behavior limits their exposure to detection during sampling. Despite this, IDO and CMR were strongly and positively correlated (r = 0.88; rho = 0.90), and their relationship, modeled through a log–log regression, explained about 80% of the variance. In contrast, simple counts correlated only moderately (averaged counts: r = 0.74; rho = 0.88) or weakly (maximum counts: r = 0.39; rho = 0.33) with CMR estimates. Their corresponding log–log models explained substantially less variation (51% and 8% respectively). Our findings suggest that IDO is a reliable method for tracking numerical variation in marmot populations, although it revealed a modest tendency toward saturation, with increasing underestimation of relative abundance at higher densities. IDO outperformed non-probabilistic methods in detecting population trends, likely due to its ability to adjust for detection probability – though some assumptions may not have been fully met. Replicating this study in other species within the Marmotini tribe is needed to assess IDO’s performance across different ecological contexts.