scholarly journals Satellite Remote Sensing and the Marine Biodiversity Observation Network: Current Science and Future Steps

Oceanography ◽  
2021 ◽  
Vol 34 (2) ◽  
Author(s):  
Maria Kavanaugh ◽  
◽  
Tom Bell ◽  
Dylan Catlett ◽  
Megan Cimino ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Marine Ecosystem ◽  
Marine Biodiversity ◽  
Human Populations ◽  
Coastal Zones ◽  
Distribution Models ◽  
Spatial And Temporal Scales ◽  
Biological Communities ◽  
Observation Network ◽  
Biodiversity Changes

Coastal ecosystems are rapidly changing due to human-caused global warming, rising sea level, changing circulation patterns, sea ice loss, and acidification that in turn alter the productivity and composition of marine biological communities. In addition, regional pressures associated with growing human populations and economies result in changes in infrastructure, land use, and other development; greater extraction of fisheries and other natural resources; alteration of benthic seascapes; increased pollution; and eutrophication. Understanding biodiversity is fundamental to assessing and managing human activities that sustain ecosystem health and services and mitigate humankind’s indiscretions. Remote-sensing observations provide rapid and synoptic data for assessing biophysical interactions at multiple spatial and temporal scales and thus are useful for monitoring biodiversity in critical coastal zones. However, many challenges remain because of complex bio-optical signals, poor signal retrieval, and suboptimal algorithms. Here, we highlight four approaches in remote sensing that complement the Marine Biodiversity Observation Network (MBON). MBON observations help quantify plankton functional types, foundation species, and unique species habitat relationships, as well as inform species distribution models. In concert with in situ observations across multiple platforms, these efforts contribute to monitoring biodiversity changes in complex coastal regions by providing oceanographic context, contributing to algorithm and indicator development, and creating linkages between long-term ecological studies, the next generations of satellite sensors, and marine ecosystem management.

scholarly journals Biodiversity baseline for large marine ecosystems: an example from the Barents Sea

2015 ◽  
Vol 72 (6) ◽  
pp. 1756-1768 ◽  
Author(s):  
Grégoire Certain ◽  
Benjamin Planque
Keyword(s):  
Fish Community ◽  
Biological Diversity ◽  
Barents Sea ◽  
Marine Ecosystem ◽  
Marine Ecosystems ◽  
Spatial And Temporal Scales ◽  
Diversity Measures ◽  
The Barents Sea ◽  
True Diversity ◽  
Biodiversity Changes

Abstract Biodiversity is an increasingly important issue for the management of marine ecosystems. However, the proliferation of biodiversity indices and difficulties associated with their interpretation have resulted in a lack of clearly defined framework for quantifying biodiversity and biodiversity changes in marine ecosystems for assessment purpose. Recent theoretical and numerical developments in biodiversity statistics have established clear algebraic relationships between most of the diversity measures commonly used, and have highlighted those that most directly relates to the concept of biological diversity, terming them “true” diversity measures. In this study, we implement the calculation of these “true” diversity measures at the scale of a large-marine ecosystem, the Barents Sea. We applied hierarchical partitioning of biodiversity to an extensive dataset encompassing 10 years of trawl-surveys for both pelagic and demersal fish community. We quantify biodiversity and biodiversity changes for these two communities across the whole continental shelf of the Barents Sea at various spatial and temporal scales, explicitly identifying areas where fish communities are stable and variable. The method is used to disentangle areas where community composition is subject to random fluctuations from areas where the fish community is drifting over time. We discuss how our results can serve as a spatio-temporal biodiversity baseline against which new biodiversity estimates, derived from sea surveys, can be evaluated.

ATMOSPHERIC N DEPOSITION TO THE COASTAL AREA OF THE BLACK SEA: SOURCES, INTRA-ANNUAL VARIATIONS AND IMPORTANCE FOR BIOGEOCHEMISTRY AND PRODUCTIVITY OF THE SURFACE LAYER

2017 ◽  
Author(s):  
Alla Varenik ◽  
Alla Varenik ◽  
Sergey Konovalov ◽  
Sergey Konovalov
Keyword(s):  
Primary Production ◽  
Black Sea ◽  
Marine Ecosystem ◽  
C:N Ratio ◽  
N Deposition ◽  
Local Source ◽  
The Black Sea ◽  
Coastal Zones ◽  
Atmospheric N Deposition ◽  
Urban Location

Atmospheric precipitations can be an important source of nutrients to open and coastal zones of marine ecosystem. Jickells [1] has published that atmospheric depositions can sup-port 5-25% of nitrogen required to primary production. Bulk atmospheric precipitations have been collected in a rural location at the Black Sea Crimean coast – Katsiveli settlement, and an urban location – Sevastopol city. Samples have been analyzed for inorganic fixed nitrogen (IFN) – nitrate, nitrite, and ammonium. Deposi-tions have been calculated at various space and time scales. The monthly volume weighted mean concentration of IFN increases from summer to winter in both locations. A significant local source of IFN has been revealed for the urban location and this source and its spatial influence have been quantified. IFN deposition with atmospheric precipitations is up to 5% of its background content in the upper 10 m layer of water at the north-western shelf of the Black Sea. Considering Redfield C:N ratio (106:16) and the rate of primary production (PP) in coastal areas of the Black Sea of about 100-130 g C m-2 year-1 we have assessed that average atmospheric IFN depositions may intensify primary production by 4.5% for rural locations, but this value is increased many-fold in urban locations due to local IFN sources.

ATMOSPHERIC N DEPOSITION TO THE COASTAL AREA OF THE BLACK SEA: SOURCES, INTRA-ANNUAL VARIATIONS AND IMPORTANCE FOR BIOGEOCHEMISTRY AND PRODUCTIVITY OF THE SURFACE LAYER

2017 ◽  
Author(s):  
Alla Varenik ◽  
Alla Varenik ◽  
Sergey Konovalov ◽  
Sergey Konovalov
Keyword(s):  
Primary Production ◽  
Black Sea ◽  
Marine Ecosystem ◽  
C:N Ratio ◽  
N Deposition ◽  
Local Source ◽  
The Black Sea ◽  
Coastal Zones ◽  
Atmospheric N Deposition ◽  
Urban Location

Atmospheric precipitations can be an important source of nutrients to open and coastal zones of marine ecosystem. Jickells [1] has published that atmospheric depositions can sup-port 5-25% of nitrogen required to primary production. Bulk atmospheric precipitations have been collected in a rural location at the Black Sea Crimean coast – Katsiveli settlement, and an urban location – Sevastopol city. Samples have been analyzed for inorganic fixed nitrogen (IFN) – nitrate, nitrite, and ammonium. Deposi-tions have been calculated at various space and time scales. The monthly volume weighted mean concentration of IFN increases from summer to winter in both locations. A significant local source of IFN has been revealed for the urban location and this source and its spatial influence have been quantified. IFN deposition with atmospheric precipitations is up to 5% of its background content in the upper 10 m layer of water at the north-western shelf of the Black Sea. Considering Redfield C:N ratio (106:16) and the rate of primary production (PP) in coastal areas of the Black Sea of about 100-130 g C m-2 year-1 we have assessed that average atmospheric IFN depositions may intensify primary production by 4.5% for rural locations, but this value is increased many-fold in urban locations due to local IFN sources.

scholarly journals A Computational Methodology for the Calibration of Tephra Transport Nowcasting at Sakurajima Volcano, Japan

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 104
Author(s):  
Alexandros P. Poulidis ◽  
Atsushi Shimizu ◽  
Haruhisa Nakamichi ◽  
Masato Iguchi
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Volcanic Eruptions ◽  
Weather Research And Forecasting ◽  
Sakurajima Volcano ◽  
Observation Network ◽  
Complementary Strategy ◽  
Physical Quantities ◽  
Do So

Ground-based remote sensing equipment have the potential to be used for the nowcasting of the tephra hazard from volcanic eruptions. To do so raw data from the equipment first need to be accurately transformed to tephra-related physical quantities. In order to establish these relations for Sakurajima volcano, Japan, we propose a methodology based on high-resolution simulations. An eruption that occurred at Sakurajima on 16 July 2018 is used as the basis of a pilot study. The westwards dispersal of the tephra cloud was ideal for the observation network that has been installed near the volcano. In total, the plume and subsequent tephra cloud were recorded by 2 XMP radars, 1 lidar and 3 optical disdrometers, providing insight on all phases of the eruption, from plume generation to tephra transport away from the volcano. The Weather Research and Forecasting (WRF) and FALL3D models were used to reconstruct the transport and deposition patterns. Simulated airborne tephra concentration and accumulated load were linked, respectively, to lidar backscatter intensity and radar reflectivity. Overall, results highlight the possibility of using such a high-resolution modelling-based methodology as a reliable complementary strategy to common approaches for retrieving tephra-related quantities from remote sensing data.

scholarly journals Biodiversity of echinoids and their epibionts around the Scotia Arc, Antarctica

2008 ◽  
Vol 20 (3) ◽  
pp. 227-244 ◽  
Author(s):  
Katrin Linse ◽  
Lisa J. Walker ◽  
David K.A. Barnes
Keyword(s):  
Southern Ocean ◽  
Current Knowledge ◽  
Sea Urchins ◽  
Marine Biodiversity ◽  
Current View ◽  
Depth Range ◽  
Tissue Mass ◽  
Scotia Arc ◽  
Biodiversity Changes ◽  
Study Species

AbstractThe Scotia Arc, linking the Magellan region with the Antarctic Peninsula, comprises young and old islands both near continents and isolated, and is the only semi-continuous link between cool temperate and Antarctic environments. It is an ideal region for studies on how marine biodiversity changes across an extended transition zone. Echinoids (sea urchins) and their associated epibionts were found across depths from 91–1045 m, with 19 species from shelf and four from slope depths. The 23 species from 38 trawls represent 31% of all echinoid species known from the Southern Ocean and 38% of the shelf/upper slope echinoids. The specimens collected comprise representatives of the five families Cidaridae, Echinidae, Temnopleuridae, Schizasteridae and Pourtalesiidae. Echinoids are probably a good model for how well we know Antarctic shelf and slope megabenthos; none of the species we report are new to science but we found nine (39%) of our study species present at new localities, some thousands of kilometres from previous findings. New biogeographic ranges are illustrated forCtenocidaris gigantea,C. nutrix,C. spinosa,Abatus curvidens,A. ingens,A. shackletoni,Amphineustes rostratus,Tripylaster philippiandPourtalesia aurorae. Southern Ocean echinoids show eurybathy as the mean depth range of our study species was 1241 m and only one was at less than 500 m. The current view of echinoid dominance of super-abundance in the shallows seems to be not transferable to shelf and slope depths as only one of 38 trawls was dominated by echinoids. Current knowledge on maximum sizes in Antarctic echinoids seems to be good as our morphometric measurements were mainly within known size ranges. Regular echinoids increased predictably in mass with increasing test length, apart fromCtenocidaris spinosa. Tissue mass of cidaroid species was ~17%, but across irregular species varied from 17.7–8.9%. No epibionts were found on irregular echinoids or Echinidae but 70 cidaroids examined carried 51 species representing ten classes. Many of these species are reported as cidaroid epibionts for the first time. Cidaroids and their epibionts constituted > 38% of the total macrofaunal richness in the trawls they were present in. Echinoids and their epibionts clearly contribute significantly to Southern Ocean biodiversity but are minor components of biomass except in the shallows.

Maritime built heritage and marine wildlife: Remote sensing as a tool to identify and prioritise integrated conservation in coastal environments

2021 ◽  
Author(s):  
Tim Baxter ◽  
Martin Coombes ◽  
Heather Viles
Keyword(s):  
Remote Sensing ◽  
Structural Information ◽  
Regional Scale ◽  
Initial Assessment ◽  
Marine Biodiversity ◽  
Engineering Structures ◽  
Built Heritage ◽  
Ecological Importance ◽  
Integrated Conservation ◽  
Marine Wildlife

<p>Maritime built heritage is threatened by natural hazards and human activities around the world. Likewise, marine wildlife is increasingly threatened by the effects of climate change and human development. Due to their age and traditional construction, maritime built heritage (e.g. historic harbours) may provide unique habitats for diverse assemblages of marine wildlife. Yet, as aspects of built heritage are often missing in assessments of marine infrastructure, identifying which heritage assets have the potential to provide the greatest ecological benefits remains a challenge. An improved understanding of the ecological importance of maritime built heritage can enhance arguments for its continued protection, maintenance and repair. At the same time, this may present new opportunities to conserve important and largely unidentified hotspots of marine biodiversity.</p><p>Using preliminary results from the Isles of Scilly, UK, this study presents a novel method for quantifying the full extent of marine engineering structures (including heritage assets) at a regional scale, and for identifying priority structures for joint biodiversity and heritage conservation.</p><p>Remote sensing data were considered alongside historic environment data and records of modern coastal defences in a rapid desk-based assessment to create a complete inventory of marine structures along the entire coastline of the Isles of Scilly. In total, 68 structures were recorded (6,180 m in length), with over half registered as heritage assets. LiDAR and aerial photography were used to determine the site characteristics of each structure (e.g. shore position). This allowed for an initial assessment of the potential ecological importance of these structures when considered alongside structural information, including building age and material. By evaluating the ecological potential and heritage value of each structure using a novel scoring system, priorities for conservation and other managed interventions are identified. This includes listed buildings and scheduled monuments that due to their construction features and shore position are most likely to support diverse marine assemblages.</p><p>Combined ecological-heritage evaluations incorporating remote sensing datasets allow for the identification of those structures with the greatest potential for the integrated conservation of built heritage and marine wildlife. Research is now needed to develop this method further, ground-truth its outputs, and test its application in other geographical locations and at varying scales.</p>

scholarly journals Wavelet-based spatial comparison technique for analysing and evaluating two-dimensional geophysical model fields

2012 ◽  
Vol 5 (1) ◽  
pp. 223-230 ◽  
Author(s):  
S. Saux Picart ◽  
M. Butenschön ◽  
J. D. Shutler
Keyword(s):  
Satellite Data ◽  
Fishery Management ◽  
Numerical Models ◽  
Spatial Scales ◽  
Marine Ecosystem ◽  
Original Method ◽  
Precipitation Forecast ◽  
Spatial And Temporal Scales ◽  
Geographical Patterns ◽  
Marine Ecosystem Model

Abstract. Complex numerical models of the Earth's environment, based around 3-D or 4-D time and space domains are routinely used for applications including climate predictions, weather forecasts, fishery management and environmental impact assessments. Quantitatively assessing the ability of these models to accurately reproduce geographical patterns at a range of spatial and temporal scales has always been a difficult problem to address. However, this is crucial if we are to rely on these models for decision making. Satellite data are potentially the only observational dataset able to cover the large spatial domains analysed by many types of geophysical models. Consequently optical wavelength satellite data is beginning to be used to evaluate model hindcast fields of terrestrial and marine environments. However, these satellite data invariably contain regions of occluded or missing data due to clouds, further complicating or impacting on any comparisons with the model. This work builds on a published methodology, that evaluates precipitation forecast using radar observations based on predefined absolute thresholds. It allows model skill to be evaluated at a range of spatial scales and rain intensities. Here we extend the original method to allow its generic application to a range of continuous and discontinuous geophysical data fields, and therefore allowing its use with optical satellite data. This is achieved through two major improvements to the original method: (i) all thresholds are determined based on the statistical distribution of the input data, so no a priori knowledge about the model fields being analysed is required and (ii) occluded data can be analysed without impacting on the metric results. The method can be used to assess a model's ability to simulate geographical patterns over a range of spatial scales. We illustrate how the method provides a compact and concise way of visualising the degree of agreement between spatial features in two datasets. The application of the new method, its handling of bias and occlusion and the advantages of the novel method are demonstrated through the analysis of model fields from a marine ecosystem model.

Satellite remote sensing and natural disturbances

2019 ◽  
pp. 37-50
Author(s):  
Nathalie Pettorelli
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Accurate Information ◽  
Ecological Knowledge ◽  
Natural Disturbances ◽  
Ecosystem Impacts ◽  
Spatial And Temporal Scales ◽  
Continental Scale ◽  
Management Actions ◽  
Wild Fire

This chapter provides an overview of how satellite remote sensing can help map the occurrence, and risk of occurrence, of several environmental disturbances; assess the extent of the associated damages; and monitor the recovery of the areas impacted by these disturbances. It particularly focuses on floods, wild fires, droughts, frost, extreme winter warming events, infestations and blooms, and bleaching events, as these are all well-known natural disturbances likely to change in frequency of occurrence and intensity over the coming decades. Through the use of examples, this chapter demonstrates how the utility of satellite remote sensing resides in the ability it provides to separate and characterise (i.e. through form, intensity, and trajectory) disturbances and responses at various spatial and temporal scales, thereby facilitating ecological knowledge expansion and the identification of relevant management actions. In particular, this contribution shows how satellites offer multiple opportunities to gain accurate information on the location, spatial extent, and duration of disturbances at the continental scale, which is needed to evaluate the ecosystem impacts of land cover changes due to, for example, wild fire, insect epidemics, and flooding, thereby reducing uncertainties in our ability to model global carbon budgets.

Active Microwave Systems for Monitoring Drought Stress

2005 ◽  
Author(s):  
Anne M. Smith
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Value Added ◽  
Agricultural Drought ◽  
Sensor System ◽  
Spatial And Temporal Scales ◽  
Satellite Systems ◽  
Radio Detection ◽  
Vegetation Water ◽  
Radar Satellite

Remote sensing can provide timely and economical monitoring of large areas. It provides the ability to generate information on a variety of spatial and temporal scales. Generally, remote sensing is divided into passive and active depending on the sensor system. The majority of remote-sensing studies concerned with drought monitoring have involved visible–infrared sensor systems, which are passive and depend on the sun’s illumination. Radar (radio detection and ranging) is an active sensor system that transmits energy in the microwave region of the electromagnetic spectrum and measures the energy reflected back from the landscape target. The energy reflected back is called backscatter. The attraction of radar over visible– infrared remote sensing (chapters 5 and 6) is its independence from the sun, enabling day/night operations, as well as its ability to penetrate cloud and obtain data under most weather conditions. Thus, unlike visible–infrared sensors, radar offers the opportunity to acquire uninterrupted information relevant to drought such as soil moisture and vegetation stress. Drought conditions manifest in multiple and complex ways. Accordingly, a large number of drought indices have been defined to signal abnormally dry conditions and their effects on crop growth, river flow, groundwater, and so on (Tate and Gustard, 2000). In the field of radar remote sensing, much work has been devoted to developing algorithms to retrieve geophysical parameters such as soil moisture, crop biomass, and vegetation water content. In principle, these parameters would be highly relevant for monitoring agricultural drought. However, despite the existence of a number of radar satellite systems, progress in the use of radar in environmental monitoring, particularly in respect to agriculture, has been slower than anticipated. This may be attributed to the complex nature of radar interactions with agricultural targets and the suboptimal configuration of the satellite sensors available in the 1990s (Ulaby, 1998; Bouman et al., 1999). Because most attention is still devoted to the problem of deriving high-quality soil moisture and vegetation products, there have been few investigations on how to combine such radar products with other data and models to obtain value-added agricultural drought products.

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