
Multi‐scale spatial patterns of three seagrass species with different growth dynamics
Author(s) -
Kendrick Gary A.,
Holmes Karen W.,
Van Niel Kimberly P.
Publication year - 2008
Publication title -
ecography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.973
H-Index - 128
eISSN - 1600-0587
pISSN - 0906-7590
DOI - 10.1111/j.0906-7590.2008.5252.x
Subject(s) - seagrass , ecology , spatial ecology , spatial variability , habitat , ecological succession , colonization , environmental science , biology , geography , statistics , mathematics
Knowledge of landscape spatial patterns of seagrasses and their rates of loss and natural colonization is critical for understanding the ecology of this group of submerged aquatic plants. Seagrasses form extensive meadows that occupy sheltered coastal seas of the world. In this paper, we examine the multi‐scale variability of three seagrass species over a large near‐shore region (42 km 2 ) in Western Australia. Geostatistical non‐parametric methods were used to explore spatial variation in presence of Amphibolis griffithii , Posidonia coriacea and P. sinuosa , and to identify the spatial scales at which distinct patterns in the species distributions occur: <50, 50–610 and >610 m. Each species showed unique variance structure across local (<50 and 50–610 m) and regional scales (>610 m), suggesting differences in species biology, environmental requirements, inter‐species interactions, and their ability to modify their environment. These observations reflect that 1) seagrass landscapes are created by processes that independently act on each seagrass species at different spatial scales; 2) the species’ distributions differ in their hydrodynamic forcing, and; 3) seagrass species distributions reflect colonization history such that related species are separated in space because they have different places in the successional sequence. This cross‐scale study demonstrates that shoot studies only partly address the spatial structure of seagrass landscapes and further large‐scale spatially‐explicit research is required before we can interpret the driving processes.