Corner inlet and Nooramunga habitat mapping project

Deakin University and the University of Tasmania were commissioned by Parks Victoria (PV) to create two updated habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. The team obtained a ground-truth data set using in situ video and still photographs. This dataset was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both ALOS (Advanced Land Observation Satellite) imagery atmospherically corrected by CSIRO and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, returning overall accuracies >73 % and kappa values > 0.62 for both study localities. Habitats predicted with highest accuracies included Zosteraceae in Nooramunga (91 %), reef in Corner Inlet (80 %), and bare sediment (no-visible macrobiota/no-visible seagrass classes; both > 76 %). The majority of classification errors were due to the misclassification of areas of sparse seagrass as bare sediment. For the Corner Inlet study locality the no-visible macrobiota (10,698 ha), Posidonia (4,608 ha) and Zosteraceae (4,229 ha) habitat classes covered the most area. In Nooramunga no-visible seagrass (5,538 ha), Zosteraceae (4,060 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

In addition to the commissioned work preliminary change detection analyses were undertaken as part of this project. These analyses indicated shifts in habitat extents in both study localities since the late 1990s/2000. In particular, a post-classification analysis highlighted that there were considerable increases in seagrass habitat (primarily Zosteraceae) throughout the littoral zones and river/creek mouths of both study localities. Further, the numerous channel systems remained stable and were free of seagrass at both times. A substantial net loss of Posidonia in the Corner Inlet locality is likely but requires further investigation due to potential misclassifications between habitats in both the 1998 map (Roob et al. 1998) and the current mapping. While the unsupervised Independent Components Analysis (ICA) change detection technique indicated some changes in habitat extent and distribution, considerable areas of habitat change observed in the post-classification approach are questionable, and may reflect misclassifications rather than real change. A particular example of this is an apparent large decrease in Zosteraceae and increase in Posidonia being related to the classification of Posidonia beds as Zosteraceae in the 1998 mapping. Despite this, we believe that changes indicated by both the ICA and post-classification approaches have a high likelihood of being ‘actual’ change. A pattern of gains and losses of Zosteraceae in the region north of Stockyard channel is an example of this. Further analyses and refinements of approaches in change detection analyses such as would improve confidence in the location and extent of habitat changes over this time period.

This work has been successful in providing new baseline maps using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Corner Inlet and Nooramunga Habitat Mapping Project – Part 2 : High resolution mapping and change detection analysis using 2011 Rapid Eye Satellite Image compared to 2009 ALOS Satellite Image

Building on a habitat mapping project completed in 2011, Deakin University was commissioned by Parks Victoria (PV) to apply the same methodology and ground-truth data to a second, more recent and higher resolution satellite image to create habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. A ground-truth data set using in situ video and still photographs was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both RapidEye satellite imagery (corrected for atmospheric and water column effects by CSIRO) and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, with error rates similar to or better than the earlier classification (>73 % and kappa values > 0.58 for both study localities). The RapidEye classification failed to accurately detect Pyura and reef habitat classes at the Corner Inlet locality, possibly due to differences in spectral frequencies. For comparison, these categories were combined into a ‘non-seagrass’ category, similar to the one used at the Nooramunga locality in the original classification. Habitats predicted with highest accuracies differed from the earlier classification and were Posidonia in Corner Inlet (89%), and bare sediment (no-visible seagrass class) in Nooramunga (90%). In the Corner Inlet locality reef and Pyura habitat categories were not distinguishable in the repeated classification and so were combined with bare sediments. The majority of remaining classification errors were due to the misclassification of Zosteraceae as bare sediment and vice versa. Dominant habitats were the same as those from the 2011 classification with some differences in extent. For the Corner Inlet study locality the no-visible seagrass category remained the most extensive (9059 ha), followed by Posidonia (5,513 ha) and Zosteraceae (5,504 ha). In Nooramunga no-visible seagrass (6,294 ha), Zosteraceae (3,122 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

Change detection analyses between the 2009 and 2011 imagery were undertaken as part of this project, following the analyses presented in Monk et al. (2011) and incorporating error estimates from both classifications. These analyses indicated some shifts in classification between Posidonia and Zosteraceae as well as a general reduction in the area of Zosteraceae. Issues with classification of mixed beds were apparent, particularly in the main Posidonia bed at Nooramunga where a mosaic of Zosteraceae and Posidonia was seen that was not evident in the ALOS classification. Results of a reanalysis of the 1998-2009 change detection illustrating effects of binning of mixed beds is also provided as an appendix.

This work has been successful in providing baseline maps at an improved level of detail using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Coastal environmental gradients – Key to reproduction habitat mapping of freshwater fish in the Baltic Sea

Habitat requirements of fish are most strict during the early life stages, and the quality and quantity of reproduction habitats lays the basis for fish production. A considerable number of fish species in the northern Baltic Sea reproduce in the shallow coastal areas, which are also the most heavily exploited parts of the brackish marine area. However, the coastal fish reproduction habitats in the northern Baltic Sea are poorly known. The studies presented in this thesis focused on the influence of environmental conditions on the distribution of coastal reproduction habitats of freshwater fish. They were conducted in vegetated littoral zone along an exposure and salinity gradient extending from the innermost bays to the outer archipelago on the south-western and southern coasts of Finland, in the northern Baltic Sea. Special emphasis was placed on reed-covered Phragmites australis shores, which form a dominant vegetation type in several coastal archipelago areas. The main aims of this research were to (1) develop and test new survey and mapping methods, (2) investigate the environmental requirements that govern the reproduction of freshwater fish in the coastal area and (3) survey, map and model the distribution of the reproduction habitats of pike (Esox lucius) and roach (Rutilus rutilus). The white plate and scoop method with a standardized sampling time and effort was demonstrated to be a functional method for sampling the early life stages of fish in dense vegetation and shallow water. Reed-covered shores were shown to form especially important reproduction habitats for several freshwater fish species, such as pike, roach, other cyprinids and burbot, in the northern Baltic Sea. The reproduction habitats of pike were limited to sheltered reed- and moss-covered shores of the inner and middle archipelago, where suitable zooplankton prey were available and the influence of the open sea was low. The reproduction habitats of roach were even more limited and roach reproduction was successful only in the very sheltered reed-covered shores of the innermost bay areas, where salinity remained low (< 4‰) during the spawning season due to freshwater inflow. After identifying the critical factors restricting the reproduction of pike and roach, the spatial distribution of their reproduction habitats was successfully mapped and modelled along the environmental gradients using only a few environmental predictor variables. Reproduction habitat maps are a valuable tool promoting the sustainable use and management of exploited coastal areas and helping to maintain the sustainability of fish populations. However, the large environmental gradients and the extensiveness of the archipelago zone in the northern Baltic Sea demand an especially high spatial resolution of the coastal predictor variables. Therefore, the current lack of accurate large-scale, high-resolution spatial data gathered at exactly the right time is a considerable limitation for predictive modelling of shallow coastal waters.

Yaringa and French Island Marine National Park habitat mapping

Deakin University and the Department of Primary Industries were commissioned by ParksVictoria (PV) to create two updated habitat maps for Yaringa and French Island MarineNational Parks. The team obtained a ground-truth data set using in situ video and still photographs. This dataset was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from World-View-2 imagery atmospherically corrected by CSIRO and LiDAR (Light Detection and Ranging) bathymetry. In addition, the team applied an unsupervised classification approach to an aerial photograph to assess the differences between the two remote sensors. This report describes the results of the mapping as well as the methodology used to produce these habitat maps.This study has provided mapping of intertidal and subtidal habitats of Yaringa and FrenchIsland MNPs at a 2 m resolution with fair to good accuracies (Kappa 0.40-0.75). These were combined with mangrove and saltmarsh habitats recently mapped by Boon et al. (2011) to provide compete-coverage habitat maps of Yaringa and French Island MNPs.The mapping showed that Yaringa MNP was dominated by mangroves, wet saltmarsh and dense Zostereaceae, covering 33%, 29% and 19%, respectively. Similarly, intertidalvegetation and subtidal vegetation (dominated by Zosteraceae) covered 26% and 25% ofFrench Island MNP. However, as a result of turbidity and missing satellite imagery 27% ofFrench Island MNP remains unmapped.The coupling of WV-2 and LiDAR reduced potential artefacts (e.g. sun glint causing whiteand black pixels known as the “salt and pepper effect”). The satellite classification appeared to provide better results than the aerial photography classification. However, since there is a two-year difference between the capture of the aerial photography and the collection of the ground-truth data this comparison is potentially temporally confounded. It must also be noted that there are differences in costs of the data,the spatial resolution between the two datasets (i.e. WV-2 = 2 m and the Aerial = 0.5 m) and the amount spectral information contained in the data (i.e. WV-2 = 8 bands and the aerial = 4 bands), which may ultimately determine its utility for a particular project.The spatial assessment using FRAGSTATs of habitat patches within Yaringa MNP provides a viable and cost effect way to assess habitat condition (i.e. shape, size and arrangement).This spatial assessment determined that dense Zosteraceae and NVSG habitat classeswere generally larger in patch size and continuity than the medium/sparse Zosteraceaehabitat. The application spatial techniques to time-series mapping may provide a way toremotely monitor the change in the spatial characteristics of marine habitats.This work was successful in providing new baseline habitat maps using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, fisheries and catchment management, and contribute toward infrastructure planning to limit impacts on Western Port.

Forests of the sea: predictive habitat modelling to assess the abundance of canopy forming kelp forests on temperate reefs

 Large brown seaweeds (kelps) form forests in temperate and boreal marine systems that serve as foundations to the structure and dynamics of communities. Mapping the distributions of these species is important to understanding the ecology of coastal environments, managing marine ecosystems (e.g., spatial planning), predicting consequences of climate change and the potential for carbon production. We demonstrate how combining seafloor mapping technologies (LiDAR and multibeam bathymetry) and models of wave energy to map the distribution and relative abundance of seaweed forests of Ecklonia radiata can provide complete coverage over hundreds of square kilometers. Using generalized linear mixed models (GLMMs), we associated observations of E. radiata abundance from video transects with environmental variables. These relationships were then used to predict the distribution of E. radiata across our 756.1km2 study area off the coast of Victoria, Australia. A reserved dataset was used to test the accuracy of these predictions. We found that the abundance distribution of E. radiata is strongly associated with depth, presence of rocky reef, curvature of the reef topography, and wave exposure. In addition, the GLMM methodology allowed us to adequately account for spatial autocorrelation in our sampling methods. The predictive distribution map created from the best GLMM predicted the abundance of E. radiata with an accuracy of 72%. The combination of LiDAR and multibeam bathymetry allowed us to model and predict E. radiata abundance distribution across its entire depth range for this study area. Using methods like those presented in this study, we can map the distribution of macroalgae species, which will give insight into ecological communities, biodiversity distribution, carbon uptake, and potential sequestration.

Large-scale habitat mapping using vision-based AUVs : experiences, challenges & vehicle design

This paper overviews the development of a vision-based AUV along with a set of complementary operational strategies to allow reliable autonomous data collection in relatively shallow water and coral reef environments. The development of the AUV, called Starbug, encountered many challenges in terms of vehicle design, navigation and control. Some of these challenges are discussed with focus on operational strategies for estimating and reducing the total navigation error when using lower-resolution sensing modalities. Results are presented from recent field trials which illustrate the ability of the vehicle and associated operational strategies to enable rapid collection of visual data sets suitable for marine research applications.

Central Coast Region South District Basin Planning & Habitat Mapping Project

This is a report to the California Department of Fish and Game. Between 2003 and 2008, the Foundation of CSUMB produced fish habitat maps and GIS layers for CDFG based on CDFG field data. This report describes the data entry, mapping, and website construction procedures associated with the project. Included are the maps that have been constructed. This report marks the completion of the Central Coast region South District Basin Planning and Habitat Mapping Project. (Document contains 40 pages)

Fish Habitat Utilization Patterns and Evaluation of the Efficacy of Marine Protected Areas in Hawaii: Integration of NOAA Digital Benthic Habitat Mapping and Coral Reef Ecological Studies

Over the past four decades, the state of Hawaii has developed a system of eleven Marine Life Conservation Districts (MLCDs) to conserve and replenish marine resources around the state. Initially established to provide opportunities for public interaction with the marine environment, these MLCDs vary in size, habitat quality, and management regimes, providing an excellent opportunity to test hypotheses concerning marine protected area (MPA) design and function using multiple discreet sampling units. NOAA/NOS/NCCOS/Center for Coastal Monitoring and Assessment’s Biogeography Team developed digital benthic habitat maps for all MLCD and adjacent habitats. These maps were used to evaluate the efficacy of existing MLCDs for biodiversity conservation and fisheries replenishment, using a spatially explicit stratified random sampling design. Coupling the distribution of habitats and species habitat affinities using GIS technology elucidates species habitat utilization patterns at scales that are commensurate with ecosystem processes and is useful in defining essential fish habitat and biologically relevant boundaries for MPAs. Analysis of benthic cover validated the a priori classification of habitat types and provided justification for using these habitat strata to conduct stratified random sampling and analyses of fish habitat utilization patterns. Results showed that the abundance and distribution of species and assemblages exhibited strong correlations with habitat types. Fish assemblages in the colonized and uncolonized hardbottom habitats were found to be most similar among all of the habitat types. Much of the macroalgae habitat sampled was macroalgae growing on hard substrate, and as a result showed similarities with the other hardbottom assemblages. The fish assemblages in the sand habitats were highly variable but distinct from the other habitat types. Management regime also played an important role in the abundance and distribution of fish assemblages. MLCDs had higher values for most fish assemblage characteristics (e.g. biomass, size, diversity) compared with adjacent fished areas and Fisheries Management Areas (FMAs) across all habitat types. In addition, apex predators and other targeted resources species were more abundant and larger in the MLCDs, illustrating the effectiveness of these closures in conserving fish populations. Habitat complexity, quality, size and level of protection from fishing were important determinates of MLCD effectiveness with respect to their associated fish assemblages. (PDF contains 217 pages)

Guidance for benthic habitat mapping: an aerial photographic approach

This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic Approach, describes proven technology that can be applied in an operational manner by state-level scientists and resource managers. This information is based on the experience gained by NOAA Coastal Services Center staff and state-level cooperators in the production of a series of benthic habitat data sets in Delaware, Florida, Maine, Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well as during Center-sponsored workshops on coral remote sensing and seagrass and aquatic habitat assessment. (PDF contains 39 pages) The original benthic habitat document, NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the Department of Commerce in 1995. That document summarized procedures that were to be used by scientists throughout the United States to develop consistent and reliable coastal land cover and benthic habitat information. Advances in technology and new methodologies for generating these data created the need for this updated report, which builds upon the foundation of its predecessor.

Habitat mapping effort at the Olympic Coast National Marine Sanctuary – Current status and future needs

With elevating interest to establish conservation efforts for groundfish stocks and continued scrutiny over the value of marine protected areas along the west coast, the importance of enhancing our knowledge of seabed characteristics through mapping activities is becoming increasingly more important, especially in a timely manner. Shortly after the inception of the Seabed Mapping Initiative instituted with the US Geological Survey (USGS), the National Marine Sanctuary Program (NMSP) assembled a panel of habitat mapping experts. They determined that the status of existing data sets and future data acquisition needs varied widely among the individual sanctuaries and that more detailed site assessments were needed to better prioritize mapping efforts and outline an overall joint strategy. To assist with that specific effort and provide pertinent information for the Olympic Coast National Marine Sanctuary’s (OCNMS) Management Plan Review, this report summarizes the mapping efforts that have taken place at the site to date; calculates a timeframe for completion of baseline mapping efforts when operating under current data acquisition limitations; describes an optimized survey strategy to dramatically reduce the required time to complete baseline surveying; and provides estimates for the needed vessel sea-days (DAS) to accomplish baseline survey completion within a 2, 5 and 10 year timeframe. (PDF contains 38 pages.)

Olympic Coast National Marine Sanctuary Habitat Mapping: Survey report and classification of side scan sonar data from surveys HMPR-114-2004-02 and HMPR-116-2005-01.

The Olympic Coast National Marine Sanctuary (OCNMS) continues to invest significant resources into seafloor mapping activities along Washington’s outer coast (Intelmann and Cochrane 2006; Intelmann et al. 2006; Intelmann 2006). Results from these annual mapping efforts offer a snapshot of current ground conditions, help to guide research and management activities, and provide a baseline for assessing the impacts of various threats to important habitat. During the months of August 2004 and May and July 2005, we used side scan sonar to image several regions of the sea floor in the northern OCNMS, and the data were mosaicked at 1-meter pixel resolution. Video from a towed camera sled, bathymetry data, sedimentary samples and side scan sonar mapping were integrated to describe geological and biological aspects of habitat. Polygon features were created and attributed with a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999). For three small areas that were mapped with both side scan sonar and multibeam echosounder, we made a comparison of output from the classified images indicating little difference in results between the two methods. With these considerations, backscatter derived from multibeam bathymetry is currently a costefficient and safe method for seabed imaging in the shallow (<30 meters) rocky waters of OCNMS. The image quality is sufficient for classification purposes, the associated depths provide further descriptive value and risks to gear are minimized. In shallow waters (<30 meters) which do not have a high incidence of dangerous rock pinnacles, a towed multi-beam side scan sonar could provide a better option for obtaining seafloor imagery due to the high rate of acquisition speed and high image quality, however the high probability of losing or damaging such a costly system when deployed as a towed configuration in the extremely rugose nearshore zones within OCNMS is a financially risky proposition. The development of newer technologies such as intereferometric multibeam systems and bathymetric side scan systems could also provide great potential for mapping these nearshore rocky areas as they allow for high speed data acquisition, produce precisely geo-referenced side scan imagery to bathymetry, and do not experience the angular depth dependency associated with multibeam echosounders allowing larger range scales to be used in shallower water. As such, further investigation of these systems is needed to assess their efficiency and utility in these environments compared to traditional side scan sonar and multibeam bathymetry. (PDF contains 43 pages.)

Benthic habitat mapping in the Olympic Coast National Marine Sanctuary: Classification of side scan sonar data from survey HMPR-108-2002-01: Version I

In September 2002, side scan sonar was used to image a portion of the sea floor in the northern OCNMS and was mosaiced at 1-meter pixel resolution using 100 kHz data collected at 300-meter range scale. Video from a remotely-operated vehicle (ROV), bathymetry data, sedimentary samples, and sonar mapping have been integrated to describe geological and biological aspects of habitat and polygon features have been created and attributed with a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999). The data can be used with geographic information system (GIS) software for display, query, and analysis. Textural analysis of the sonar images provided a relatively automated method for delineating substrate into three broad classes representing soft, mixed sediment, and hard bottom. Microhabitat and presence of certain biologic attributes were also populated into the polygon features, but strictly limited to areas where video groundtruthing occurred. Further groundtruthing work in specific areas would improve confidence in the classified habitat map. (PDF contains 22 pages.)

National summary of NOAA's shallow-water benthic habitat mapping of U.S. coral reef ecosystems

Coral reef ecosystems are some of the most complex and important ecosystems in the marine environment. They are also among the most biologically diverse and economically valuable ecosystems on earth, producing billions of dollars in food, as well as providing a suite of ecological services, such as recreation and tourism activities and coastal protection from storm and wave action. Yet, despite their value and importance, these fragile ecosystems are declining at an alarming rate (Waddell and Clarke (eds.) 2008) due to a myriad of threats both natural and manmade, including climate change, fishing pressure, and runoff and sedimentation. In response, the Unites States Coal Reef Task Force was established in 1998 by Presidential Executive Order 13089 to lead U.S. efforts to preserve and protect the nation’s coral reef ecosystems. In order to better understand the current state of coral reef ecosystems and successfully mitigate the impacts of stressors, informational products, such as benthic (or sea floor) habitat maps, are critical. Benthic habitat maps support the ability to prioritize areas for further study and protection, and offer a baseline to evaluate the changes in ecosystems over time. In 2000, the United States Coral Reef Task Force charged NOAA with leading federal efforts to produce comprehensive digital maps of all U.S. shallow-water (approximately 0 to 30 m in depth) coral reef ecosystem habitats.

Palmyra Atoll coral reef habitat mapping completion report

The United States Coral Reef Task Force (USCRTF) was established in 1998 by Presidential Executive Order 13089 to lead U.S. efforts to preserve and protect coral reef ecosystems. Current, accurate, and consistent maps greatly enhance efforts to preserve and manage coral reef ecosystems. With comprehensive maps and habitat assessments, coral reef managers can be more effective in designing and implementing a variety of conservation measures, including: • Long-term monitoring programs with accurate baselines from which to track changes; • Place-based conservation measures such as marine protected areas (MPAs); and • Targeted research to better understand the oceanographic and ecological processes affecting coral reef ecosystem health. The National Oceanic and Atmospheric Administration’s (NOAA) National Ocean Service (NOS) is tasked with leading the coral ecosystem mapping element of the U.S. Coral Reef Task Force (CRTF) under the authority of the Presidential Executive Order 13089 to map and manage the coral reefs of the United States.