TY - JOUR
T1 - Linkages between benthic assemblages and physical environmental factors: The role of geodiversity in Eastern Gulf of Finland ecosystems
AU - Kaskela, Anu M.
AU - Rousi, Heta
AU - Ronkainen, Minna
AU - Orlova, Marina
AU - Babin, Alex
AU - Gogoberidze, George
AU - Kostamo, Kirsi
AU - Kotilainen, Aarno T.
AU - Neevin, Igor
AU - Ryabchuk, Darya
AU - Sergeev, Alexander
AU - Zhamoida, Vladimir
PY - 2017
Y1 - 2017
N2 - We analyzed hydrology, geology and benthic species composition to determine benthic habitat distribution patterns in a geologically complex area of the Gulf of Finland, Northern Baltic Sea. The analysis included several datasets describing coastal influence and geodiversity at multiple spatial scales. Geodiversity in this context refers to variation and/or patchiness of benthic substrates and seabed features. Multivariate statistical methods including BEST and LINKTREE routines were used to identify correlative relationships between different ecological variables. Environmental variables (e.g. water depth, Secchi depth, salinity) were either measured by sampling and remote sensing methods or parameterized from geographic and oceanographic data. Benthic assemblages were assayed by both video recordings and zoobenthic sampling (benthic grabs). Statistical analyses identified correlations between benthic datasets and environmental variables, but correlation parameters were not consistent especially with respect to differing zoobenthic and video-based estimates of benthic diversity. The ratio of Secchi depth to water depth showed strong correlation with species distributions observed in video recordings (ρ = 0.56) whereas variables describing broad-scale geodiversity and archipelago gradient (the abundance of islands, ratio of land and sea area) correlated with zoobenthic sample data (generally ρ > 0.30). A model that included independent variables of Secchi depth and terrain roughness within a 20 km radius explained the greatest proportion of spatial variation in zoobenthic sample data (ρ = 0.69). Secchi depth and roughness values were positively correlated with species richness. We designated nine benthic marine landscapes on the basis of these two variables. Linkage tree statistical analysis (LINKTREE) routine utilized zoobenthic sample data as these offered better regional coverage and therefore effectively tracked relationships with other environmental variables. The benthic marine landscapes found in topographically complex seabed areas possessed higher species diversity than flatter areas with fewer seabed features. Our results indicate that on broad spatial scales, geodiversity and archipelago gradient directly influence benthic assemblages by providing a range of different habitats. These factors also indirectly influence benthic assemblages by channeling water movement and thereby distributing hydrologic conditions. This study demonstrates that broad-scale geodiversity should be considered in regional and mesoscale habitat mapping, maritime spatial planning and conservation policies.
AB - We analyzed hydrology, geology and benthic species composition to determine benthic habitat distribution patterns in a geologically complex area of the Gulf of Finland, Northern Baltic Sea. The analysis included several datasets describing coastal influence and geodiversity at multiple spatial scales. Geodiversity in this context refers to variation and/or patchiness of benthic substrates and seabed features. Multivariate statistical methods including BEST and LINKTREE routines were used to identify correlative relationships between different ecological variables. Environmental variables (e.g. water depth, Secchi depth, salinity) were either measured by sampling and remote sensing methods or parameterized from geographic and oceanographic data. Benthic assemblages were assayed by both video recordings and zoobenthic sampling (benthic grabs). Statistical analyses identified correlations between benthic datasets and environmental variables, but correlation parameters were not consistent especially with respect to differing zoobenthic and video-based estimates of benthic diversity. The ratio of Secchi depth to water depth showed strong correlation with species distributions observed in video recordings (ρ = 0.56) whereas variables describing broad-scale geodiversity and archipelago gradient (the abundance of islands, ratio of land and sea area) correlated with zoobenthic sample data (generally ρ > 0.30). A model that included independent variables of Secchi depth and terrain roughness within a 20 km radius explained the greatest proportion of spatial variation in zoobenthic sample data (ρ = 0.69). Secchi depth and roughness values were positively correlated with species richness. We designated nine benthic marine landscapes on the basis of these two variables. Linkage tree statistical analysis (LINKTREE) routine utilized zoobenthic sample data as these offered better regional coverage and therefore effectively tracked relationships with other environmental variables. The benthic marine landscapes found in topographically complex seabed areas possessed higher species diversity than flatter areas with fewer seabed features. Our results indicate that on broad spatial scales, geodiversity and archipelago gradient directly influence benthic assemblages by providing a range of different habitats. These factors also indirectly influence benthic assemblages by channeling water movement and thereby distributing hydrologic conditions. This study demonstrates that broad-scale geodiversity should be considered in regional and mesoscale habitat mapping, maritime spatial planning and conservation policies.
KW - Ecosystem based management
KW - biodiversity
KW - Geodiversity
KW - Marine landscape
KW - Benthic habitat mapping
KW - Marine spatial planning
KW - Ecosystem based management
KW - biodiversity
KW - Geodiversity
KW - Marine landscape
KW - Benthic habitat mapping
KW - Marine spatial planning
KW - Ecosystem based management
KW - biodiversity
KW - Geodiversity
KW - Marine landscape
KW - Benthic habitat mapping
KW - Marine spatial planning
U2 - 10.1016/j.csr.2017.05.013
DO - 10.1016/j.csr.2017.05.013
M3 - Article
SN - 0278-4343
VL - 142
SP - 1
EP - 13
JO - Continental Shelf Research
JF - Continental Shelf Research
ER -