Despite declines in numerous migratory bird populations due to global climate and landscape changes, the Pacific Flyway population of Greater White‐fronted Geese Anser albifrons frontalis in North America has flourished over recent decades. However, the demographic foundations of the population increase remain unclear, largely due to sparse data. In this study, we used a Bayesian integrated population model (IPM) to maximize information from multiple data sources including coordinated population survey, ring‐recovery and hunter‐harvested goose tail data. We estimated demographic parameters and assessed the role of several possible drivers of the observed population increase, including density‐dependent processes, agricultural land use change and climate conditions in both the wintering and the breeding season, while also accounting for the impacts of harvest. Non‐harvest survival of all geese was 0.83 (95% credible interval (CRI): 0.70–0.96) before legislation restricted post‐harvest rice field burning, and 0.98 (95% CRI: 0.94–1.0) afterwards. We detected a negative effect of density‐dependent processes and a positive effect of El Niño‐Southern Oscillation on non‐harvest survival with high certainty. Kill rates were 0.11 (95% CRI: 0.09–0.12) for adults (after hatch year) and 0.26 (95% CRI 0.21–0.31) for juveniles (hatch year), resulting in annual survival rates of 0.81 (95% CRI: 0.69–0.89) for adults and 0.67 (95% CRI: 0.56–0.76) for juveniles. The ratio of juvenile birds to adults in the population was on average 0.36 (95% CRI: 0.29–0.45) and was driven by negative density‐dependent processes with high certainty. Our results suggest that the ban on rice field burning and subsequent high frequency of flooding as an alternative rice decomposition practice was the primary driver of the Pacific white‐fronted Goose population increase. The effects of climate change and density dependence were not strong enough to suppress the benefit of flooded rice. Given sparse demographic data for Pacific white‐fronted Geese, we were only able to uncover drivers of demography using IPMs. We encourage practitioners with sparse data similarly to consider forming IPMs to determine the drivers and mechanisms for population change and to prioritize future data collection.

中文翻译：

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冬季稻米泛滥的现象说明了北美北美地区的太平洋飞鹅白额雁大白额额最近增加

尽管由于全球气候和景观变化导致许多候鸟数量下降，但大白额雁雁白lb的太平洋飞道种群近几十年来，北美市场蓬勃发展。但是，人口增长的人口基础仍然不清楚，这主要是由于数据稀疏。在这项研究中，我们使用贝叶斯综合人口模型（IPM）来最大化来自多个数据源的信息，包括协调人口调查，环恢复和猎人收获的鹅尾数据。我们估算了人口参数并评估了所观察到的人口增长的几种可能的驱动因素，包括依赖密度的过程，农业用地变化以及越冬和繁殖季节的气候条件，同时也考虑了收获的影响。在立法限制收割后稻田燃烧之前，所有鹅的非收成存活率为0.83（95％可信区间（CRI）：0.70-0.96），为0.98（95％CRI：0.94-1）。0）之后。我们以高确定性检测到密度依赖性过程的负面影响，以及厄尔尼诺-南方涛动对非收获存活的积极影响。成人（孵化年后）的杀灭率为0.11（95％CRI：0.09–0.12），而少年（孵化年）为0.26（95％CRI 0.21–0.31），因此年存活率为0.81（95％CRI：0.69）成人为–0.89），青少年为0.67（95％CRI：0.56-0.76）。种群中幼鸟与成年鸟的比例平均为0.36（95％CRI：0.29–0.45），并受到高度依赖于负密度的过程的影响。我们的结果表明，禁止稻田燃烧和随后的高洪灾作为一种替代性的稻米分解做法，是太平洋白额鹅种群增加的主要驱动力。气候变化和密度依赖性的影响不足以抑制水淹稻米的利益。鉴于太平洋白雁的人口统计数据稀少，我们只能使用IPM来发现人口统计学的驱动因素。我们鼓励拥有稀疏数据的从业者同样考虑考虑建立IPM，以确定人口变化的驱动因素和机制，并优先考虑未来的数据收集。