Fishing sustainably is a fundamental problem in tropical regions where diverse fisheries and scarce fisheries information challenges efforts to make reliable estimates and associated policies. To improve evaluations and decisions, we compared the predictions of six surplus production models calibrated using various permutations of fisheries‐dependent data with a benchmark model. The benchmark model was built from fisheries‐independent estimates of r and K, tested against rates of change in Kenyan reef fisheries and found to be accurate. Comparisons with the benchmark model were made with fisheries‐dependent equilibrium and non‐equilibrium models, fixing or not fixing r and K, pooled versus site averaged solutions, and rising, falling, and pooled fishing effort over time. Evaluations indicate high variability in MMSY predictions and notable overestimates of MMSY (~75%) and effort (~210%) for Fox and Schaefer equilibrium models. Non‐equilibrium models had high failure rates (~25%) but successful fits performed better and indicated smaller overestimates (16%) for site‐level evaluations. The Pella–Tomlinson model was most accurate (MMSY = 5.6 ± 0.60 (SD) tonnes/km²/year) and best‐fit r‐K relationships also aligned well with ecoregional data on K and short‐term yields. Future efforts are advised to pool site data, use conservative recruitment values (z = 0.8), and collect data across times of both rising and falling effort. Recommended methods and subsequent adjustments of the benchmark model should improve local and ecoregional scale MMSYs. The benchmark model was calibrated to estimate MMSY in fished seascapes, but to conserve species with slower life histories, we suggest modifications to limit MMSYs to between 1.8 and 3.2 tonnes/km²/year.

中文翻译：

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改善热带珊瑚礁渔业的可持续产量估计

可持续捕鱼是热带地区的一个基本问题，在热带地区，多样化的渔业和稀缺的渔业信息挑战了做出可靠估计和相关政策的努力。为了改进评估和决策，我们将使用渔业相关数据的各种排列校正的六个过剩生产模型的预测与基准模型进行了比较。该基准模型是根据独立于渔业的r和K估计值建立的，并根据肯尼亚礁石渔业的变化率进行了测试，发现是准确的。与基准模型的比较是通过渔业依赖的均衡模型和非均衡模型进行的，固定或不固定r和K，汇总与现场平均解决方案之间的关系，以及随着时间的推移而上升，下降和汇总捕鱼的工作量。评估表明，对于Fox和Schaefer平衡模型，MMSY预测存在较大差异，并且MMSY（〜75％）和工作量（〜210％）明显过高。非平衡模型的失效率很高（〜25％），但成功拟合的效果更好，并且对站点级评估的过高估计值较小（16％）。在佩拉-汤姆林森模型是最准确的（MMSY = 5.6±0.60（SD）吨/公里² /年）和最佳拟合[R - ķ关系，也与生态区的数据排列以及ķ和短期收益率。建议未来的工作是合并站点数据，使用保守的招聘值（z = 0.8），并在上升和下降时间之间收集数据。建议的方法和对基准模型的后续调整应改善地方和生态区域的MMSY。已对基准模型进行了校准，以估计捕鱼海景中的MMSY，但是为了保护具有较慢生命历史的物种，我们建议进行修改以将MMSY限制在1.8至3.2吨/ km ² /年之间。