Phenology-informed decline risk of estuarine fishes and their prey suggests potential for future trophic mismatches

Conservation scientists have long used population viability analysis (PVA)
on species count data to quantify trends and critical decline risk,
thereby informing conservation actions. These assessments typically focus
on single species rather than assemblages and assume that risk is
consistent within a given life stage (e.g., across the different seasons
or months of a year). However, assessing risk at overly broad temporal or
spatial scales may obscure diverging population declines between predators
and prey, potentially disrupting biotic interactions. In this study, we
used time-series-based PVA for age-0 forage fishes and their potential
zooplankton prey for each month of the year in the San Francisco Estuary,
over 1995-2023 (N = 175 time series). We used Multivariate Autoregressive
(MAR) models that estimate long-term population trends and variability
(i.e., process error) for each population. We found widespread negative
population trends across fish species (56.8%) and observed that critical
decline risk is often higher in months when species abundances peak
compared to ‘shoulder’ months. Although current decline risk is somewhat
balanced between predators and their prey (mean 23.7% for fish and 21.1%
for zooplankton), our time-series models indicate trophic levels are
poised to diverge over the next 10 years, with fish generally accumulating
risk faster than their prey. Additionally, zooplankton showed 11.2% higher
uncertainty about their near-term critical decline risk relative to fish.
These observations suggest strong, previously unreported potential for
future trophic mismatches. Our results underscore the need to assess risk
over finer temporal scales within and across trophic levels to better
understand vulnerability, and thus inform conservation of imperiled
species. Our approach is transferable and highlights the benefits of
time-series-based PVA to understand the risk of food-web collapse in the
face of climate-induced phenological shifts.

保护科学家长期以来借助种群生存力分析（population viability analysis, PVA）处理物种计数数据，以量化种群变化趋势与严重衰退风险，进而为保护行动提供决策依据。此类评估通常聚焦于单一物种种群，而非物种群落，且假设同一生活史阶段（如一年中的不同季节或月份）内的衰退风险保持一致。然而，在过于宽泛的时间或空间尺度下开展风险评估，可能会掩盖捕食者与猎物之间分化的种群衰退趋势，进而破坏生物间的相互作用。本研究以旧金山河口（San Francisco Estuary）1995年至2023年的数据集为基础（共包含175条时间序列），针对全年各月份的0龄饵料鱼类及其潜在浮游动物猎物，采用基于时间序列的种群生存力分析开展研究；我们使用多元自回归（Multivariate Autoregressive, MAR）模型，估算各物种种群的长期变化趋势与种群动态变异性（即过程误差）。研究发现，占比56.8%的鱼类类群存在广泛的种群负增长趋势；同时观察到，相较于过渡平季月份，种群丰度达到峰值的月份往往具有更高的严重衰退风险。尽管当前捕食者与猎物间的衰退风险大致均衡（鱼类平均风险为23.7%，浮游动物为21.1%），但基于时间序列的模型结果显示，未来10年内各营养级的衰退风险即将出现分化，鱼类的风险累积速率普遍快于其猎物。此外，相较于鱼类，浮游动物的近期严重衰退风险不确定性高出11.2%。上述研究结果表明，未来可能出现此前未被报道过的强烈营养级错配风险。本研究结果强调，需在营养级内部及跨营养级层面采用更精细的时间尺度开展风险评估，以更好地理解物种的脆弱性，进而为濒危物种的保护工作提供支撑。本研究方法具备可推广性，同时凸显了基于时间序列的种群生存力分析在理解气候诱导物候变化背景下食物网崩溃风险方面的应用价值。