Scalability and performance tradeoffs in quantifying relationships between elevation and tidal wetland plant communities

Elevation is a major driver of plant ecology and sediment dynamics in tidal wetlands, so accurate and precise spatial data are essential for assessing wetland vulnerability to sea-level rise and making forecasts. We performed survey-grade elevation and vegetation surveys of the Global Change Research Wetland, a brackish microtidal wetland in the Chesapeake Bay estuary, Maryland (USA), to both intercompare unbiased digital elevation model (DEM) creation techniques and to describe niche partitioning of several common tidal wetland plant species. We identified a tradeoff between scalability and performance in creating unbiased DEMs, with more data-intensive methods such as kriging performing better than 3 more scalable methods involving post-processing of light detection and ranging (LiDAR)-based DEMs. The LiDAR Elevation Correction with Normalized Difference Vegetation Index (LEAN) method provided a compromise between scalability and performance, although it underpredicted variability in elevation. In areas where native plants dominated, the sedge Schoenoplectus americanus occupied more frequently flooded areas (median: 0.22, 95% range: 0.09 to 0.31 m relative to North America Vertical Datum of 1988 [NAVD88]) and the grass Spartina patens, less frequently flooded (0.27, 0.1 to 0.35 m NAVD88). Non-native Phragmites australis dominated at lower elevations more than the native graminoids, but had a wide flooding tolerance, encompassing both their ranges (0.19, -0.05 to 0.36 m NAVD88). The native shrub Iva frutescens also dominated at lower elevations (0.20, 0.04 to 0.30 m NAVD88), despite being previously described as a high marsh species. These analyses not only provide valuable context for the temporally rich but spatially restricted data collected at a single well-studied site, but also provide broad insight into mapping techniques and species zonation.

高程是潮汐湿地植物生态和沉积物动态的主要驱动因素，因此准确和精确的空间数据对于评估湿地对海平面上升的脆弱性以及进行预测至关重要。我们对美国马里兰州切萨皮克湾河口的一个半咸水微潮汐湿地——全球变化研究湿地进行了测量级别的高程和植被调查，目的是对无偏差数字高程模型（DEM）创建技术进行相互比较，并描述几种常见潮汐湿地植物物种的生态位分化。我们发现了在创建无偏差DEM时可扩展性和性能之间的权衡，像克里金插值这样数据密集型的方法比另外3种涉及对基于激光雷达（LiDAR）的DEM进行后处理的更具可扩展性的方法表现更好。利用归一化植被指数（LEAN）进行激光雷达高程校正的方法在可扩展性和性能之间提供了一种折衷，尽管它低估了高程的变化性。在本地植物占主导的区域，莎草（Schoenoplectus americanus）占据更频繁被水淹的区域（中位数：相对于1988年北美垂直基准面[NAVD88]为0.22米，95%范围：0.09米到0.31米），而草类的互花米草（Spartina patens）则处于较少被水淹的区域（0.27米，0.1米到0.35米NAVD88）。非本地的芦苇（Phragmites australis）在较低高程比本地的禾草类更占优势，但具有较宽的耐水淹范围，涵盖了前两者的范围（0.19米， -0.05米到0.36米NAVD88）。本地灌木假苍耳（Iva frutescens）也在较低高程占优势（0.20米，0.04米到0.30米NAVD88），尽管它之前被描述为一种高沼物种。这些分析不仅为在一个研究充分的单一地点收集的时间丰富但空间受限的数据提供了有价值的背景信息，而且为绘图技术和物种分带提供了广泛的见解。