11th ICRS Abstract book - Nova Southeastern University

Oral Mini-Symposium 17: Emerging Techniques in Remote Sensing and Geospatial Analysis
17-25
A Novel Model Framework For Predicting Organismal Distributions Across The
Seascape Using Gis Topographic Metrics And Benthic Habitat Associations.
Brian WALKER* 1
1 National Coral Reef Institute, Nova Southeastern University Oceanographic Center,
Dania Beach, FL
Increased topographic complexity has been linked to increased species diversity and/or
abundance in many ecological communities including coral reefs. Several topographic
metrics can be measured remotely in GIS using high resolution bathymetry including
elevation, surface rugosity, and seafloor volume within specified areas. Statistical
relationships between these data and organismal distributions within mapped habitats can
be used to make predictions across the entire bathymetric dataset. In this study a model
framework is presented which determines statistically significant relationships between
reef fish abundance and species richness and GIS topographic complexity measurements
for samples within similar benthic habitats. Predictions from these relationships for each
habitat were then projected to create GIS-based prediction maps of abundance and
species richness for the entire seascape. Reef fish associations with GIS topographic
metrics were significant and varied between habitats. Model evaluation showed that
patterns in the measured data emerged in the prediction data. The results allow for
viewing of data trends throughout the seascape, quantification of assemblages in nonsampled
areas, and statistical comparisons of areas within the region to support and guide
management related decisions. This model framework can be adapted to other
communities (e.g. benthic organisms) and/or parameters (e.g. diversity) that relate to
topographic complexity.
17-26
An Investigation Of Reef Fish Community Modelling With Geostatistical Methods
Jeanne DE MAZIERES* 1 , James COMLEY 2
1 School of Marine Studies, University of the South Pacific, Suva, Fiji, 2 Institute of
Applied Science, University of the South Pacific, Suva, Fiji
The objective of this study was to determine the spatial distribution of reef fish
communities according to the habitat types of the Coral Coast, Fiji Islands by using
geostatistical analysis methods. The Coral Coast is located on the south coast of Viti
Levu, Fiji’s main island which is bordered by a fringing reef about 80 km long. The study
area was divided into 22 geomorphological reef units where biological data were
previously collected. Substrate cover and fish counts were obtained for a total of 312
transects. Data were processed and a spatial database was created including the location
of the surveyed transects associated with quantitative and qualitative information on
substrate cover, habitat type and fish family abundance. We worked with six classes of
habitats (sand, rubble, bedrock, macroalgae, seagrass and live coral) which were
distinguished according to thresholds of 20% for the biotic substrate and 50% for the
abiotic. Nine fish families were selected due to their importance for the fisheries and as
reef health indicators. We conducted batches of exploratory and multivariate statistical
tests to identify distinct and significant patterns of fish assemblage distribution at both
scales of the reef system and the reef unit. The overall results showed that sand, seagrass
and live coral habitats hosted significantly different communities. We then determined
the fish families which were characteristic of those habitats. Their distribution was
predicted at the reef unit scale by using the cokriging geostatistical model which allowed
multivariate interpolation and estimation of prediction error. It seemed that the quality of
the estimations varied highly depending on the reef unit and the family. Used as a
complement to the others available tools, this geostatistical model might provide a useful
support for decision-making and management of the reef resources.
17-27
Predictive Habitat Mapping Of Deep Or Turbid Coral Reefs Using An Ecological
Modelling Approach With Multibeam Data
Ben RADFORD* 1 , Kimberly VAN NIEL 1 , Karen HOLMES 1,2 , Gary KENDRICK 3 , Jessica
MEEUWIG 3 , Euan HARVEY 3
1 School of Earth and Geographical Sciences, University of Western Australia, Perth, Australia,
2 Centre for Ecohydrology, University of Western Australia, Perth, Australia, 3 Botany,
University of Western Australia, Perth, Australia
In the past coral reef mapping using forms of remotely sensed data (such as satellite imagery,
aerial photography) has been largely been limited areas shallower 30 meters of water depth
because of light availability. However in resent years this has changed with in the introduction
of sensors that can collect high resolution “Multibeam” sonar data. Multibeam sonar provides
the potential to map at broad scale by providing high resolution bathymetric and substrate
information from water depths of 20 to over 60 meters, When combined with an ecological
modelling approach, multibeam and towed video imagery provide the basis for mapping living
coral on deep or turbid coral reefs.
Here we outline this approach integrating data capture with analysis methods and ecological
theory. We demonstrate this mapping method using deeper coral reefs areas from the Abrolhos
Islands, Western Australia. This mapping approach involved a number of stages: (1) collecting
and processing of raw data, (2) extensive secondary modelling on primary data, such as
bathymetry, to develop spatial surfaces which are relevant to both the physical (e.g. h) and
biotic aspects of a site, (3) integrating spatial surfaces and in situ information, (4) the
development of predictive habitat models, and (5) the spatial extension of the in situ data to the
unknown areas using the predictive models. Each of these steps is essential to build realistic
spatially explicit models of reef substrate and major biotic groups. Predictive modelling
methods were used to explore the data and final predictions were developed using a novel
approach of merging multiple biotic predictions. This framework facilitated development of
high accuracy maps of hard coral distribution (and other important biotic groups) were
traditional spectral remote sensing would fail.
17-28
Seafloor Characterization Using Multibeam and Optical Data at French Frigate Shoals,
Northwestern Hawaiian Islands
Jonathan WEISS* 1 , Joyce MILLER 1 , John ROONEY 1
1 Joint Institute for Marine and Atmospheric Research, University of Hawaii, and NOAA Pacific
Islands Fisheries Science Center, Honolulu, HI
Multibeam bathymetry, backscatter, and optical data collected by NOAA’s Coral Reef
Ecosystem Division are used to create maps of seafloor habitats on the bank top at French
Frigate Shoals in water depths ranging from