Data from: Consensus forecasting of intertidal seagrass habitat in the Wadden Sea

After the dramatic eutrophication-induced decline of intertidal seagrasses in the 1970s, the Wadden Sea has shown diverging developments. In the northern Wadden Sea, seagrass beds have expanded and become denser, while in the southern Wadden Sea, only small beds with low shoot densities are found. A lack of documentation of historical distributions hampers conservation management. Yet, the recovery in the northern Wadden Sea provides opportunity to construct robust habitat suitability models to support management. We tuned habitat distribution models based on 17 years of seagrass surveys in the northern Wadden Sea and high-resolution hydrodynamics and geomorphology for the entire Wadden Sea using five machine learning approaches. To obtain geographically transferable models, hyperparameters were tuned on the basis of prediction accuracy assessed by non-random, spatial cross-validation. The spatial cross-validation methodology was combined with a consensus modelling approach. The predicted suitability scores correlated amongst each other and with the hold-out observations in the training area indicating that the models converged and were transferable across space. Prediction accuracy was improved by averaging the predictions of the best models. We graphically examined the relationship between the consensus suitability score and independent presence-only data from outside the training area using the area-adjusted seagrass frequency per suitability class (continuous Boyce index). The Boyce index was positively correlated with the suitability score indicating the adequacy of the prediction methodology. We used the plot of the continuous Boyce index against habitat suitability score to demarcate three habitat classes – unsuitable, marginal and suitable – for the entire international Wadden Sea. This information is valuable for habitat conservation and restoration management. Divergence between predicted suitability and actual distributions from the recent past indicates that unaccounted factors limit seagrass development in the southern Wadden Sea. Synthesis and applications. Our methodology and data enabled us to produce a robust and validated consensus habitat suitability model. We identified highly suitable areas where intertidal seagrass meadows may establish and persist. Our work provides scientific underpinning for effective conservation planning in a dynamic landscape and sets monitoring priorities.20世纪70年代，富营养化引发潮间带海草大规模衰退后，瓦登海（Wadden Sea）的海草群落呈现出分化的发展态势。在北瓦登海，海草床面积不断扩张且株丛愈发密集；而南瓦登海仅分布有少量株丛密度较低的小型海草床。历史分布记录的缺失，阻碍了海草的保护管理工作。不过，北瓦登海的海草恢复为构建可靠的生境适宜性模型（habitat suitability models）以支撑管理实践提供了契机。 我们基于北瓦登海17年的海草调查数据，结合整个瓦登海的高分辨率水动力与地貌数据，采用5种机器学习方法（machine learning approaches）校准了生境分布模型。为获取具备地理迁移性的模型，我们通过非随机空间交叉验证（spatial cross-validation）评估的预测精度来调整超参数（hyperparameters），并将空间交叉验证方法与集成建模思路相结合。 预测得到的适宜性得分彼此间存在显著相关，且与训练区域内的预留观测样本（hold-out observations）呈正相关关系，这表明模型实现了收敛且具备跨空间迁移能力。通过对最优模型的预测结果取平均，进一步提升了模型的预测精度。 我们针对训练区域外的独立仅存在数据（presence-only data），以各适宜性等级下经面积校正的海草频率（area-adjusted seagrass frequency）为指标，通过图形化方式分析了集成适宜性得分与该数据间的关联，即采用连续型博伊斯指数（continuous Boyce index）进行评估。博伊斯指数（Boyce index）与适宜性得分呈正相关，这证明了本次预测方法的合理性。 我们借助连续型博伊斯指数与生境适宜性得分的散点图，为整个跨国瓦登海划定了三类生境等级——不适宜、边缘适宜与适宜。该研究结果对于生境保护与修复管理具有重要的应用价值。 预测得到的适宜性分布与近期实际分布之间存在差异，这表明尚有未被纳入考量的因素限制了南瓦登海的海草生长与存续。 综合与应用。我们的研究方法与数据支撑我们构建了可靠且经过验证的集成生境适宜性模型。我们识别出了潮间带海草草甸能够定植并持续存活的高适宜区域。本研究为动态景观下的高效保护规划提供了科学依据，并确立了相应的监测优先级。