EUNIS habitat's thresholds for the Western coast of the Iberian Peninsula — A Portuguese case study

The European Nature Information System (EUNIS) has been implemented for the establishment of a marine European habitats inventory. Its hierarchical classification is defined and relies on environmental variables which primarily constrain biological communities (e.g. substrate types, sea energy level, depth and light penetration). The EUNIS habitat classification scheme relies on thresholds (e.g. fraction of light and energy) which are based on expert judgment or on the empirical analysis of the above environmental data. The present paper proposes to establish and validate an appropriate threshold for energy classes (high, moderate and low) and for subtidal biological zonation (infralittoral and circalittoral) suitable for EUNIS habitat classification of the Western Iberian coast. Kineticwave-induced energy and the fraction of photosynthetically available light exerted on the marine bottom were respectively assigned to the presence of kelp (Saccorhiza polyschides, Laminaria hyperborea and Laminaria ochroleuca) and seaweed species in general. Both data were statistically described, ordered fromthe largest to the smallest and percentile analyseswere independently performed. The threshold between infralittoral and circalittoral was based on the first quartile while the ‘moderate energy’ class was established between the 12.5 and 87.5 percentiles. To avoid data dependence on sampling locations and assess the confidence interval a bootstrap technique was applied. According to this analysis,more than 75% of seaweeds are present at locations where more than 3.65% of the surface light reaches the sea bottom. The range of energy levels estimated using S. polyschides data, indicate that on the IberianWest coast the ‘moderate energy’ areas are between 0.00303 and 0.04385 N/m2 of wave-induced energy. The lack of agreement between different studies in different regions of Europe suggests the need for more standardization in the future. However, the obtained thresholds in the present study will be very useful in the near future to implement and establish the Iberian EUNIS habitats inventory.

Broad-scale mapping of seafloor habitats in the north-east Atlantic using existing environmental data

If marine management policies and actions are to achieve long-term sustainable use and management of the marine environment and its resources, they need to be informed by data giving the spatial distribution of seafloor habitats over large areas. Broad-scale seafloor habitat mapping is an approachwhich has the benefit of producing maps covering large extents at a reasonable cost. This approach was first investigated by Roff et al. (2003), who, acknowledging that benthic communities are strongly influenced by the physical characteristics of the seafloor, proposed overlaying mapped physical variables using a geographic information system (GIS) to produce an integrated map of the physical characteristics of the seafloor. In Europe the method was adapted to the marine section of the EUNIS (European Nature Information System) classification of habitat types under the MESH project, andwas applied at an operational level in 2011 under the EUSeaMap project. The present study compiled GIS layers for fundamental physical parameters in the northeast Atlantic, including (i) bathymetry, (ii) substrate type, (iii) light penetration depth and (iv) exposure to near-seafloor currents andwave action. Based on analyses of biological occurrences, significant thresholds were fine-tuned for each of the abiotic layers and later used in multi-criteria raster algebra for the integration of the layers into a seafloor habitat map. The final result was a harmonised broad-scale seafloor habitat map with a 250 m pixel size covering four extensive areas, i.e. Ireland, the Bay of Biscay, the Iberian Peninsula and the Azores. The map provided the first comprehensive perception of habitat spatial distribution for the Iberian Peninsula and the Azores, and fed into the initiative for a pan- European map initiated by the EUSeaMap project for Baltic, North, Celtic and Mediterranean seas.

Real-time image classification for adaptive mission planning using an Autonomous Underwater Vehicle

Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.

Integrating field survey data with satellite image data to improve shallow water seagrass maps : the role of AUV and snorkeller surveys

Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

Characterization of Navassa National Wildlife Refuge: A preliminary report for NF-06-05 (NOAA ship "Nancy Foster", April 18-30, 2006)

Navassa is a small, undeveloped island in the Windward Passage between Jamaica and Haiti. It was designated a National Wildlife Refuge under the jurisdiction of the U.S. Fish and Wildlife Service in 1999, but the remote location makes management and enforcement challenging, and the area is regularly fished by artisanal fishermen from Haiti. In April 2006, the NOAA Center for Coastal Fisheries and Habitat Research conducted a research cruise to Navassa. The cruise produced the first high-resolution multibeam bathymetry for the area, which will facilitate habitat mapping and assist in refuge management. A major emphasis of the cruise was to study the impact of Haitian fishing gear on benthic habitats and fish communities; however, in 10 days on station only one small boat was observed with five fishermen and seven traps. Fifteen monitoring stations were established to characterize fish and benthic communities along the deep (28-34 m) shelf, as these areas have been largely unstudied by previous cruises. The fish communities included numerous squirrelfishes, triggerfishes, and parrotfishes. Snappers and grouper were also present but no small individuals were observed. Similarly, conch surveys indicated the population was in low abundance and was heavily skewed towards adults. Analysis of the benthic photoquadrats is currently underway. Other cruise activities included installation of a temperature logger network, sample collection for stable isotope analyses to examine trophic structure, and drop camera surveys to ground-truth habitat maps and overhead imagery. (PDF contains 58 pages)

Benthic habitats of Buck Island Reef National Monument

NOAA’s Center for Coastal Monitoring and Assessment’s Biogeography Branch has mapped and characterized large portions of the coral reef ecosystems inside the U.S. coastal and territorial waters, including the U.S. Caribbean. The complementary protocols used in these efforts have enabled scientists and managers to quantitatively compare different marine ecosystems in tropical U.S. waters. The Biogeography Branch used these same general protocols to generate three seamless habitat maps of the Bank/Shelf (i.e., from 0 ≤50 meters) and the Bank/Shelf Escarpment (i.e., from 50 ≤1,000 meters and from 1,000 ≤ 1,830 meters) inside Buck Island Reef National Monument (BIRNM). While this mapping effort marks the fourth time that the shallow-water habitats of BIRNM have been mapped, it is the first time habitats deeper than 30 meters (m) have been characterized. Consequently, this habitat map provides information on the distribution of mesophotic and deep-water coral reef ecosystems and serves as a spatial baseline for monitoring change in the Monument. A benthic habitat map was developed for approximately 74.3 square kilometers or 98% of the BIRNM using a combination of semi-automated and manual classification methods. The remaining 2% was not mapped due to lack of imagery in the western part of the Monument at depths ranging from 1,000 to 1,400 meters. Habitats were interpreted from orthophotographs, LiDAR (Light Detection and Ranging) imagery and four different types of MBES (Multibeam Echosounder) imagery. Three minimum mapping units (MMUs) (100, 1,000 and 5,000 square meters) were used because of the wide range of depths present in the Monument. The majority of the area that was characterized was deeper than 30 m on the Bank/Shelf Escarpment. This escarpment area was dominated by uncolonized sand which transitioned to mud as depth increased. Bedrock was exposed in some areas of the escarpment, where steep slopes prevented sediment deposition. Mesophotic corals were seen in the underwater video, but were too sparsely distributed to be reliably mapped from the source imagery. Habitats on the Bank/Shelf were much more variable than those seen on the Bank/Shelf Escarpment. The majority of this shelf area was comprised of coral reef and hardbottom habitat dominated by various forms of turf, fleshy, coralline or filamentous algae. Even though algae was the dominant biological cover type, nearly a quarter (24.3%) of the Monument’s Bank/Shelf benthos hosted a cover of 10%-<50% live coral. In total, 198 unique combinations of habitat classes describing the geography, geology and biology of the sea-floor were identified from the three types of imagery listed above. No thematic accuracy assessment was conducted for areas deeper than about 50 meters, most of which was located in the Bank/Shelf Escarpment. The thematic accuracy of classes in waters shallower than approximately 50 meters ranged from 81.4% to 94.4%. These thematic accuracies are similar to those reported for other NOAA benthic habitat mapping efforts in St. John (>80%), the Main Eight Hawaiian Islands (>84.0%) and the Republic of Palau (>80.0%). These digital maps products can be used with confidence by scientists and resource managers for a multitude of different applications, including structuring monitoring programs, supporting management decisions, and establishing and managing marine conservation areas. The final deliverables for this project, including the benthic habitat maps, source imagery and in situ field data, are available to the public on a NOAA Biogeography Branch website (http://ccma.nos.noaa.gov/ecosystems/coralreef/stcroix.aspx) and through an interactive, web-based map application (http://ccma.nos.noaa.gov/explorer/biomapper/biomapper.html?id=BUIS). This report documents the process and methods used to create the shallow to deep-water benthic habitat maps for BIRNM. Chapter 1 provides a short introduction to BIRNM, including its history, marine life and ongoing research activities. Chapter 2 describes the benthic habitat classification scheme used to partition the different habitats into ecologically relevant groups. Chapter 3 explains the steps required to create a benthic habitat map using a combination of semi-automated and visual classification techniques. Chapter 4 details the steps used in the accuracy assessment and reports on the thematic accuracy of the final shallow-water map. Chapter 5 summarizes the type and abundance of each habitat class found inside BIRNM, how these habitats compare to past habitat maps and outlines how these new habitat maps may be used to inform future management activities.

Shallow-water benthic habitats of St. John, U.S. Virgin Islands

Coral reef ecosystems of the Virgin Islands Coral Reef National Monument, Virgin Islands National Park and the surrounding waters of St. John, U.S. Virgin Islands are a precious natural resource worthy of special protection and conservation. The mosaic of habitats including coral reefs, seagrasses and mangroves, are home to a diversity of marine organisms. These benthic habitats and their associated inhabitants provide many important ecosystem services to the community of St. John, such as fishing, tourism and shoreline protection. However, coral reef ecosystems throughout the U.S. Caribbean are under increasing pressure from environmental and anthropogenic stressors that threaten to destroy the natural heritage of these marine habitats. Mapping of benthic habitats is an integral component of any effective ecosystem-based management approach. Through the implementation of a multi-year interagency agreement, NOAA’s Center for Coastal Monitoring and Assessment - Biogeography Branch and the U.S. National Park Service (NPS) have completed benthic habitat mapping, field validation and accuracy assessment of maps for the nearshore marine environment of St. John. This work is an expansion of ongoing mapping and monitoring efforts conducted by NOAA and NPS in the U.S. Caribbean and replaces previous NOAA maps generated by Kendall et al. (2001) for the waters around St. John. The use of standardized protocols enables the condition of the coral reef ecosystems around St. John to be evaluated in context to the rest of the Virgin Island Territories and other U.S. coral ecosystems. The products from this effort provide an accurate assessment of the abundance and distribution of marine habitats surrounding St. John to support more effective management and conservation of ocean resources within the National Park system. This report documents the entire process of benthic habitat mapping in St. John. Chapter 1 provides a description of the benthic habitat classification scheme used to categorize the different habitats existing in the nearshore environment. Chapter 2 describes the steps required to create a benthic habitat map from visual interpretation of remotely sensed imagery. Chapter 3 details the process of accuracy assessment and reports on the thematic accuracy of the final maps. Finally, Chapter 4 is a summary of the basic map content and compares the new maps to a previous NOAA effort. Benthic habitat maps of the nearshore marine environment of St. John, U.S. Virgin Islands were created by visual interpretation of remotely sensed imagery. Overhead imagery, including color orthophotography and IKONOS satellite imagery, proved to be an excellent source from which to visually interpret the location, extent and attributes of marine habitats. NOAA scientists were able to accurately and reliably delineate the boundaries of features on digital imagery using a Geographic Information System (GIS) and fi eld investigations. The St. John habitat classification scheme defined benthic communities on the basis of four primary coral reef ecosystem attributes: 1) broad geographic zone, 2) geomorphological structure type, 3) dominant biological cover, and 4) degree of live coral cover. Every feature in the benthic habitat map was assigned a designation at each level of the scheme. The ability to apply any component of this scheme was dependent on being able to identify and delineate a given feature in remotely sensed imagery.

The potential use of mapped extent and distribution of habitats as indicators of Good Environmental Status (GES)

The Healthy and Biologically Diverse Seas Evidence Group (HBDSEG) has been tasked with providing the technical advice for the implementation of the Marine Strategy Framework Directive (MSFD) with respect to descriptors linked to biodiversity. A workshop was held in London to address one of the Research and Development (R&D) proposals entitled: ‘Mapping the extent and distribution of habitats using acoustic and remote techniques, relevant to indicators for area/extent/habitat loss.’ The aim of the workshop was to identify, define and assess the feasibility of potential indicators of benthic habitat distribution and extent, and identify the R&D work which could be required to fully develop these indicators. The main points that came out of the workshop were: (i) There are many technical aspects of marine habitat mapping that still need to be resolved if cost-effective spatial indicators are to be developed. Many of the technical aspects that need addressing surround issues of consistency, confidence and repeatability. These areas should be tackled by the JNCC Habitat Mapping and Classification Working Group and the HBDSEG Seabed Mapping Working Group. (ii) There is a need for benthic ecologists (through the HBDSEG Benthic Habitats Subgroup and the JNCC Marine Indicators Group) to finalise the list of habitats for which extent and/or distribution indicators should be considered for development, building upon the recommendations from this report. When reviewing the list of indicators, benthic habitats could also be distinguished into those habitats that are defined/determined primarily by physical parameters (although including biological assemblages) (e.g. subtidal shallow sand) and those defined primarily by their biological assemblage (e.g. seagrass beds). This distinction is important as some anthropogenic pressures may influence the biological component of the ecosystem despite not having a quantifiable effect on the physical habitat distribution/extent. (iii) The scale and variety of UK benthic habitats makes any attempt to undertake comprehensive direct mapping exercises prohibitively expensive (especially where there is a need for repeat surveys for assessment). There is a clear need therefore to develop a risk-based approach that uses indirect indicators (e.g. modelling), such as habitats at risk from pressures caused by current human activities, to develop priorities for information gathering. The next steps that came out of the workshop were: (i) A combined approach should be developed by the JNCC Marine Indicators Group together with the HBDSEG Benthic Habitats Subgroup, which will compile and ultimately synthesise all the criteria used by the three different groups from the workshop. The agreed combined approach will be used to undertake a final review of the habitats considered during the workshop, and to evaluate any remaining habitats in order to produce a list of habitats for indicator development for which extent and/or distribution indicators could be appropriate. (ii) The points of advice raised at this workshop, alongside the combined approach aforementioned, and the final list of habitats for extent and/or distribution indicator development will be used to develop a prioritised list of actions to inform the next round of R&D proposals for benthic habitat indicator development in 2014. This will be done through technical discussions within JNCC and the relevant HBDSEG Subgroups. The preparation of recommendations by these groups should take into account existing work programmes, and consider the limited resources available to undertake any further R&D work.

Nomenclature and syntaxonomic notes on some high-rank syntaxa of the European grassland vegetation

We present descriptions of a new order (Ranunculo cortusifolii-Geranietalia reuteri and of a new alliance (Stachyo lusitanicae-Cheirolophion sempervirentis) for the herbaceous fringe communities of Macaronesia and of the southwestern Iberian Peninsula, respectively. A new alliance, the Polygalo mediterraneae-Bromion erecti (mesophilous post-cultural grasslands), was introduced for the Peninsular Italy. We further validate and typify the Armerietalia rumelicae (perennial grasslands supported by nutrient-poor on siliceous bedrocks at altitudes characterized by the submediterranean climate of central-southern Balkan Peninsula), the Securigero-Dasypyrion villosae (lawn and fallow-land tall-grass annual vegetation of Italy), and the Cirsio vallis-demoni-Nardion (acidophilous grasslands on siliceous substrates of the Southern Italy). Nomenclatural issues (validity, legitimacy, synonymy, formal corrections) have been discussed and clarified for the following names: Brachypodio-Brometalia, Bromo pannonici-Festucion csikhegyensis, Corynephoro-Plantaginion radicatae, Heleochloion, Hieracio-Plantaginion radicatae, Nardetea strictae, Nardetalia strictae, Nardo-Callunetea, Nardo-Galion saxatilis, Oligo-Bromion, Paspalo-Heleochloetalia, Plantagini-Corynephorion and Scorzoneret alia villosae. 

Hydro-acoustic remote sensing of benthic biological communities on the shallow South East Australian continental shelf

Information regarding the composition and extent of benthic habitats on the South East Australian continental shelf is limited. In this habitat mapping study, multibeam echosounder (MBES) data are integrated with precisely geo-referenced video ground-truth data to quantify benthic biotic communities at Cape Nelson, Victoria, Australia. Using an automated decision tree classification approach, 5 representative biotic groups defined from video analysis were related to hydro-acoustically derived variables in the Cape Nelson survey area. Using a combination of multibeam bathymetry, backscatter and derivative products produced highest overall accuracy (87%) and kappa statistic (0.83). This study demonstrates that decision tree classifiers are capable of integrating variable data types for mapping distributions of benthic biological assemblages, which are important in maintaining biodiversity and other system services in the marine environment.

Integrating time-series hydroacoustics and video observations for detecting changes in benthic habitats

The ability to quantify change in marine benthic habitats must be considered a key goal of marine habitat mapping activities. Changes in distribution of distinct suites of benthic biological species may occur as a result of natural or human induced processes and these processes may operate at a range of temporal and spatial scales. It is important to understand natural small scale inter-annual patterns of change in order to separate these signals from potential patterns of longer term change. Work to describe these processes of change from an acoustic remote sensing stand point has thus far been limited due to the relatively recent availability of full coverage swath acoustic datasets and cost pressures associated with multiple surveys of the same area. This paper describes the use of landscape transition analysis as a means to differentiate seemingly random patterns of habitat change from systematic signals of habitat transition at a shallow (10–50 m depth) 18 km2 study area on the temperate Australian continental shelf between the years 2006 and 2007. Supervised classifications for each year were accomplished using independently collected high resolution (3 m cell-size) multibeam echosounder (MBES) and video-derived reference data. Of the 4 representative biotic classes considered, signals of directional systematic changes were observed to occur between a shallow kelp dominated class, a deep sessile invertebrate dominated class and a mixed class of kelp and sessile invertebrates. These signals of change are interpreted as inter-annual variation in the density and depth related extent of canopy forming kelp species at the site, a phenomenon reported in smaller scale temporal studies of the same species. The methods applied in this study provide a detailed analysis of the various components of the traditional change detection cross tabulation matrix allowing identification of the strongest signals of systematic habitat transitions across broad geographical regions. Identifying clear patterns of habitat change is an important first step in linking these patterns to the processes that drive them.

Detecting patterns of change in benthic habitats by acoustic remote sensing

Changes in benthic habitats occur as a result of natural variation or human-induced processes. It is important to understand natural fine-scale inter-annual patterns of change to separate these signals from patterns of long-term change. Describing change from an acoustic remote sensing standpoint has been facilitated by the recent availability of full coverage swath acoustic datasets, but is limited by cost pressures associated with multiple surveys of the same area. We studied the use of landscape transition analysis as a means to differentiate seemingly random patterns of habitat change from systematic signals of habitat transition at a shallow (10 to 50 m depth) 18 km2 site on the temperate Australian continental shelf in 2006 and 2007. Supervised classifications for each year were accomplished using inde pendently collected highresolution swath acoustic and video reference data. Of the 4 representative biotic clas ses considered, signals of directional systematic changes occurred be tween a kelp-dominated class, a sessile invertebrate-dominated class and a mixed class of kelp and sessile invertebrates. We provide a detailed analysis of the components of the traditional change detection cross tabulation matrix, allowing identification of the strongest signals of systematic habitat transitions. Iden tifying patterns of habitat change is an important first step toward understanding the processes that drive them.