Marine Ecology Progress Series · 2009 · 65 citations · 26 references
Natural SciencesEcologyMarine SciencesCoastal OceanographyCoral Reef EcologyMarine EcologyCoastal Ecosystem EcologyCoral Reef BiodiversityReef Fish EcologySeagrass EcologySeagrass Associated FaunaSeagrass Bed Benthic CommunitiesSeagrass CommunitiesSeagrass Distribution PatternsSeagrass Faunal AssociationsSeagrass Habitat DiversitySeagrass Habitat StructureSeagrass Species Diversity
Seagrasses in waters deeper than 15 m in the Great Barrier Reef World Heritage Area (adjacent to the Queensland coast) were surveyed using a camera and dredge (towed for a period of 4 to 6 min); 1426 sites were surveyed, spanning from 10 to 25°S, and from inshore to the edge of the reef (out to 120 nautical miles from the coast). At each site seagrass presence, species, and biomass were recorded; together with depth, sediment, secchi, algae presence, epibenthos, and proximity to reefs. Seagrasses in the study area extend down to water depths of 61 m, and are difficult to map other than by generating distributions from point source data. Statistical modeling of the seagrass distribution suggests 40000 km2 of the sea bottom has a probability of some seagrass being present. There is strong spatial variation driven in part by the constraint of the Great Barrier Reef’s long, thin shape, and by physical processes associated with the land and ocean. All seagrass species found were from the genus Halophila. Probability distributions were mapped for the 4 most common species: Halophila ovalis, H. spinulosa, H. decipiens, and H. tricostata. Distributions of H. ovalis and H. spinulosa show strong depth and sediment effects, whereas H. decipiens and H. tricostata are only weakly correlated with environmental variables, but show strong spatial patterns. Distributions of all species are correlated most closely with water depth, the proportion of medium-sized sediment, and visibility measured by Secchi depth. These 3 simple characteristics of the environment correctly predict the presence of seagrass 74% of the time. The results are discussed in terms of environmental dynamics, management of the Great Barrier Reef province, and the potential for using surrogates to predict the presence of seagrass habitats.
26
Greedy function approximation: A gradient boosting machine.
Jerome H. Friedman · The Annals of Statistics · 2001 · 29K citations · Full text
The value of the world's ecosystem services and natural capital
Robert Costanza, Ralph C. d’Arge, R.S. de Groot et al. · Nature · 1997 · 22K citations
Natural Resources, Natural Resource Economics, Resource Economics +14
A Global Crisis for Seagrass Ecosystems
Robert J. Orth, Tim J. B. Carruthers, William C. Dennison et al. · BioScience · 2006 · 3K citations · Full text
BOOSTED TREES FOR ECOLOGICAL MODELING AND PREDICTION
Glenn De’ath · Ecology · 2007 · 1.3K citations
Computing, Biostatistics, Ecology +13