Remote Sensing: A Key Tool for Interdisciplinary Assessment of Coral Reef Processes

Without Abstract

Comparing the information content of coral reef geomorphological and biological habitat maps, Amirantes Archipelago (Seychelles), Western Indian Ocean

Increasing the use of geomorphological map products in marine spatial planning has the potential to greatly enhance return on mapping investment as they are commonly two orders of magnitude cheaper to produce than biologically-focussed maps of benthic communities and shallow substrates. The efficacy of geomorphological maps derived from remotely sensed imagery as surrogates for habitat diversity is explored by comparing two map sets of the platform reefs and atolls of the Amirantes Archipelago (Seychelles), Western Indian Ocean. One mapping campaign utilised Compact Airborne Spectrographic Imagery (19 wavebands, 1 m spatial resolution) to classify 11 islands and associated reefs into 25 biological habitat classes while the other campaign used Landsat 7 þ ETM imagery (7 bands, 30 m spatial resolution) to generate maps of 14 geomorphic classes. The maps were compared across a range of characteristics, including habitat richness (number of classes mapped), diversity (ShannoneWeiner statistic) and thematic content (Cramer’s V statistic). Between maps, a strong relationship was revealed for habitat richness (R2 ¼ 0.76), a moderate relationship for class diversity and evenness (R2 ¼ 0.63) and a variable relationship for thematic content, dependent on site complexity (V range 0.43 e0.93). Geomorphic maps emerged as robust predictors of the habitat richness in the Amirantes. Such maps therefore demonstrate high potential value for informing coastal management activities and conservation planning by drawing on information beyond their own thematic content and thus maximizing the return on mapping investment

Open and Closed Seascapes: Where Does Habitat Patchiness Create Populations with High Fractions of Self-Recruitment?

Which populations are replenished primarily by immigrants (open) and which by local production (closed) remains an important question for management with implications for response to exploitation, protection, and disturbance. However, we lack methods for predicting population openness. Here, we develop a model for openness and show that considering habitat isolation explains the existence of surprisingly closed populations in high-dispersal species, including many marine organisms. Relatively closed populations are expected when patch spacing is more than twice the standard deviation of a species\u27 dispersal kernel. In addition, natural scales of habitat patchiness on coral reefs are sufficient to create both largely open and largely closed populations. Contrary to some previous interpretations, largely closed marine populations do not require mean dispersal distances that are unusually short, even for species with relatively long pelagic larval durations. We predict that habitat patchiness has strong control over population openness for many marine and terrestrial species with a highly dispersive life stage and relatively sedentary adults. This information can be used to make initial predictions about where populations will be more or less resilient to local exploitation and disturbance

PEMETAAN HABITAT BENTIK PADA EKOSISTEM TERUMBU KARANG DI PERAIRAN PULAU MENJANGAN

Ekosistem pesisir yang meliputi tiga bagian penting yakni mangrove, padang lamun dan terumbu karang merupakan bagian yang tidak terpisahkan dalam proses pemetaan habitat. Penelitian ini bertujuan untuk melakukan pemetaan habitat secara geomorfologi di Pulau Menjangan, Taman Nasional Bali Barat, Bali. Pengumpulan data lapangan dilakukan pada bulan Februari, April dan Agustus 2017.  Total 104 titik sampling telah dikumpulkan, dan dilakukan analisis perbedaan tekstur menggunakan program ENVI v4.7 dari data citra satelit  Worldview 2 dengan resolusi spasial 2 m, tanggal 14 Oktober 2016. Hasil penelitian menunjukkan bahwa secara geomorfologi, kawasan pesisir Pulau Menjangan terbagi dalam 6 tipe habitat yakni mangrove, terumbu depan, lereng terumbu, rataan terumbu, pecahan karang (rubble), pasir dan teras. Berdasarkan hasil foto transek habitat dengan pendekatan skala medium (Medium Scale Approach) khususnya pada daerah rataan terumbu dan terumbu depan (fore reef/crest) dapat diklasifikasikan dalam 12 jenis habitat dengan komposisi bentik dominan karang  adalah 30% yang meliputi beberapa jenis karang keras (Scleractinia) yakni Acropora sp, Montipora sp, Porites lutea dan Porites cylindrica; Rubble & Alga (dari divisi Chlorophyta dan Phaeophyta) masing-masing sebesar 16 %; Pasir  12%; Lamun (diantaranya Syringodium sp, Cymodocea sp dan Thalasia sp) 11% dan sisanya adalah asosiasi karang Heliopora coerulea (non Scleractinia), karang mati dan teras. Daerah rataan terumbu memiliki kategori rugosity berada pada level 1 - 2, sedangkan  terumbu depan dengan rugosity level 3 - 4

A method to analyze the potential of optical remote sensing for benthic habitat mapping

Quantifying the number and type of benthic classes that are able to be spectrally identified in shallow water remote sensing is important in understanding its potential for habitat mapping. Factors that impact the effectiveness of shallow water habitat mapping include water column turbidity, depth, sensor and environmental noise, spectral resolution of the sensor and spectral variability of the benthic classes. In this paper, we present a simple hierarchical clustering method coupled with a shallow water forward model to generate water-column specific spectral libraries. This technique requires no prior decision on the number of classes to output: the resultant classes are optically separable above the spectral noise introduced by the sensor, image based radiometric corrections, the benthos’ natural spectral variability and the attenuating properties of a variable water column at depth. The modeling reveals the effect reducing the spectral resolution has on the number and type of classes that are optically distinct. We illustrate the potential of this clustering algorithm in an analysis of the conditions, including clustering accuracy, sensor spectral resolution and water column optical properties and depth that enabled the spectral distinction of the seagrass Amphibolis antartica from benthic algae

Multi-scale marine biodiversity patterns inferred efficiently from habitat image processing

Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.Camille Mellin, Lael Parrott, Serge Andréfouët, Corey J. A. Bradshaw, M. Aaron MacNeil, and M. Julian Cale

Seagrass ecosystem contributions to people's quality of life in the Pacific Island Countries and Territories

Seagrass ecosystems provide critical contributions (goods and perceived benefits or detriments) for the livelihoods and wellbeing of Pacific Islander peoples. Through in-depth examination of the contributions provided by seagrass ecosystems across the Pacific Island Countries and Territories (PICTs), we find a greater quantity in the Near Oceania (New Guinea, the Bismarck Archipelago and the Solomon Islands) and western Micronesian (Palau and Northern Marianas) regions; indicating a stronger coupling between human society and seagrass ecosystems. We also find many non-material contributions historically have been overlooked and under-appreciated by decision-makers. Closer cultural connections likely motivate guardianship of seagrass ecosystems by Pacific communities to mitigate local anthropogenic pressures. Regional comparisons also shed light on general and specific aspects of the importance of seagrass ecosystems to Pacific Islanders, which are critical for forming evidence-based policy and management to ensure the long-term resilience of seagrass ecosystems and the contributions they provide

Seagrass ecosystems of the Pacific Island countries and territories: a global bright spot

Seagrass ecosystems exist throughout Pacific Island Countries and Territories (PICTs). Despite this area covering nearly 8% of the global ocean, information on seagrass distribution, biogeography, and status remains largely absent from the scientific literature. We confirm 16 seagrass species occur across 17 of the 22 PICTs with the highest number in Melanesia, followed by Micronesia and Polynesia respectively. The greatest diversity of seagrass occurs in Papua New Guinea (13 species), and attenuates eastward across the Pacific to two species in French Polynesia. We conservatively estimate seagrass extent to be 1446.2 km2, with the greatest extent (84%) in Melanesia. We find seagrass condition in 65% of PICTs increasing or displaying no discernible trend since records began. Marine conservation across the region overwhelmingly focuses on coral reefs, with seagrass ecosystems marginalised in conservation legislation and policy. Traditional knowledge is playing a greater role in managing local seagrass resources and these approaches are having greater success than contemporary conservation approaches. In a world where the future of seagrass ecosystems is looking progressively dire, the Pacific Islands appears as a global bright spot, where pressures remain relatively low and seagrass more resilient

Incorporating uncertainty associated with habitat data in marine reserve design

One of the most pervasive forms of uncertainty in data used to make conservation decisions is error associated with mapping of conservation features. Whilst conservation planners should consider uncertainty associated with ecological data to make informed decisions, mapping error is rarely, if ever, accommodated in the planning process. Here, we develop a spatial conservation prioritization approach that accounts for the uncertainty inherent in coral reef habitat maps and apply it in the Kubulau District fisheries management area, Fiji. We use accuracy information describing the probability of occurrence of each habitat type, derived from remote sensing data validated by field surveys, to design a marine reserve network that has a high probability of protecting a fixed percentage (10-90%) of every habitat type. We compare the outcomes of our approach to those of standard reserve design approaches, where habitat-mapping errors are not known or ignored. We show that the locations of priority areas change between the standard and probabilistic approaches, with errors of omission and commission likely to occur if reserve design does not accommodate mapping accuracy. Although consideration of habitat mapping accuracy leads to bigger reserve networks, they are unlikely to miss habitat conservation targets. We explore the trade-off between conservation feature representation and reserve network area, with smaller reserve networks possible if we give up on trying to meet targets for habitats mapped with a low accuracy. The approach can be used with any habitat type at any scale to inform more robust and defensible conservation decisions in marine or terrestrial environments. (C) 2013 Elsevier Ltd. All rights reserved