Biotic indices for monitoring marine ecosystems are mostly based on the analysis of benthic macroinvertebrate communities. Due to their high sensitivity to pollution and fast response to environmental changes, bacterial assemblages could complement the information provided by benthic metazoan communities as indicators of human-induced impacts, but so far, this biological component has not been well explored for this purpose. Here we performed 16S rRNA gene amplicon sequencing to analyze the bacterial assemblage composition of 51 estuarine and coastal stations characterized by different environmental conditions and human-derived pressures. Using the relative abundance of putative indicator bacterial taxa, we developed a biotic index that is significantly correlated with a sediment quality index calculated on the basis of organic and inorganic compound concentrations. This new index based on bacterial assemblage composition can be a sensitive tool for providing a fast environmental assessment and allow a more comprehensive integrative ecosystem approach for environmental management.
Marine ecosystems are subject to anthropogenic change at global, regional and local scales. Global drivers interact with regional- and local-scale impacts of both a chronic and acute nature. Natural fluctuations and those driven by climate change need to be understood to diagnose local- and regional-scale impacts, and to inform assessments of recovery. Three case studies are used to illustrate the need for long-term studies: (i) separation of the influence of fishing pressure from climate change on bottom fish in the English Channel; (ii) recovery of rocky shore assemblages from the Torrey Canyon oil spill in the southwest of England; (iii) interaction of climate change and chronic Tributyltin pollution affecting recovery of rocky shore populations following the Torrey Canyon oil spill. We emphasize that “baselines” or “reference states” are better viewed as envelopes that are dependent on the time window of observation. Recommendations are made for adaptive management in a rapidly changing world.
Marine renewable energy developments (MREDs) are rapidly expanding in size and number as society strives to maintain electricity generation whilst simultaneously reducing climate-change linked CO2 emissions. MREDs are part of an ongoing large-scale modification of coastal waters that also includes activities such as commercial fishing, shipping, aggregate extraction, aquaculture, dredging, spoil-dumping and oil and gas exploitation. It is increasingly accepted that developments, of any kind, should only proceed if they are ecologically sustainable and will not reduce current or future delivery of ecosystem services. The benthos underpins crucial marine ecosystem services yet, in relation to MREDs, is currently poorly monitored: current monitoring programmes are extensive and costly yet provide little useful data in relation to ecosystem-scale-related changes, a situation called ‘data-rich, information-poor’ (DRIP). MRED –benthic interactions may cause changes that are of a sufficient scale to change ecosystem services provision, particularly in terms of fisheries and biodiversity and, via trophic linkages, change the distribution of fish, birds and mammals. The production of DRIPy data should be eliminated and the resources used instead to address relevant questions that are logically bounded in time and space. Efforts should target identifying metrics of change that can be linked to ecosystem function or service provision, particularly where those metrics show strongly non-linear effects in relation to the stressor. Future monitoring should also be designed to contribute towards predictive ecosystem models and be sufficiently robust and understandable to facilitate transparent, auditable and timely decision-making.
Imagery collected from Autonomous Underwater Vehicles (AUVs) provides a novel means of monitoring changes in benthic ecosystems over large spatial scales and depth ranges. However, for many benthic ecosystems there is little baseline data to quantify temporal and spatial variance for key indicator species. This information is crucial for isolating background “noise” from long-term “signals”. Here we quantify components of variance for five key deep-water sessile invertebrate species across four long-term benthic monitoring sites in a region undergoing strong climate-driven changes. We use linear mixed models to estimate the contribution of sources of spatial and temporal variance in species covers from empirical data. We then combine this information with projected long-term climate-driven changes in the cover of these groups and test the power of various survey designs to detect change through time. Large short-term temporal and spatial variability in the cover of a gorgonian octocoral results in high components of variance that limit the detectability of the projected long-term trend for this species. Conversely, for three of the sponge species high power is achievable with revisits to the four original sites every two years until 2060. By including more sites in the revisit design, high power can be achieved with less frequent revisits. For the fifth species, we find high power is unachievable due to the small trend predicted. Overall, we highlight how examination of components of variance in a system can aid in the selection of suitable indicators and the establishment of effective monitoring programs.
This report provides an assessment of emerging evidence on the socio-economic impacts of Scotland’s Marine Protected Areas (MPAs). The reports objectives are to develop a methodology for monitoring the socioeconomic impacts of MPA management measures and to gather and analyse evidence on the ex post socioeconomic impacts of MPA management measures. This report presents evidence from key informant interviews, analysis of fishing activity data and three case studies.
Scientists increasingly rely on protected areas to assist in biodiversity conservation, yet the efficacy of these areas are rarely systematically assessed, often as a byproduct of underfunding, particularly in developing countries. Still, adaptive management strategies to maximize conservation success often rely on understanding the temporal and spatial dynamism of population therein. Environmental DNA (eDNA) has been employed as a time and cost-effective method to monitor species’ distribution, with quantitative PCR (qPCR) techniques also assisting in our knowledge about abundance of aquatic taxa. To date however, this novel methodology remains underutilized by conservation managers in assessing populations in protected areas. In this study, we used eDNA concentration of the critically endangered Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis) to circumscribe population ecology in the Tian e-Zhou National Nature Reserve in Hubei, China. We developed, validated, and optimized a qPCR-based eDNA method and applied this protocol to diagnose the geographical reserve use across seasons. Our results suggest spatio-temporal idiosyncrasies, highlighting previously undescribed site and habitat preferences, and a propensity for post-breeding population dispersal. eDNA thus presents a quick and cost-effective method for assessing population-wide utilization of a protected area and, when accounting for environmental-specific nuances, can prove useful for current and future conservation goals.
In the face of increasing threats to biodiversity, the advancement of methods for surveying biological communities is a major priority for ecologists. Recent advances in molecular biological technologies have made it possible to detect and sequence DNA from environmental samples (environmental DNA or eDNA); however, eDNA techniques have not yet seen widespread adoption as a routine method for biological surveillance primarily due to gaps in our understanding of the dynamics of eDNA in space and time. In order to identify the effective spatial scale of this approach in a dynamic marine environment, we collected marine surface water samples from transects ranging from the intertidal zone to four kilometers from shore. Using PCR primers that target a diverse assemblage of metazoans, we amplified a region of mitochondrial 16S rDNA from the samples and sequenced the products on an Illumina platform in order to detect communities and quantify their spatial patterns using a variety of statistical tools. We find evidence for multiple, discrete eDNA communities in this habitat, and show that these communities decrease in similarity as they become further apart. Offshore communities tend to be richer but less even than those inshore, though diversity was not spatially autocorrelated. Taxon-specific relative abundance coincided with our expectations of spatial distribution in taxa lacking a microscopic, pelagic life-history stage, though most of the taxa detected do not meet these criteria. Finally, we use carefully replicated laboratory procedures to show that laboratory treatments were remarkably similar in most cases, while allowing us to detect a faulty replicate, emphasizing the importance of replication to metabarcoding studies. While there is much work to be done before eDNA techniques can be confidently deployed as a standard method for ecological monitoring, this study serves as a first analysis of diversity at the fine spatial scales relevant to marine ecologists and confirms the promise of eDNA in dynamic environments.
False killer whales (Pseudorca crassidens) feed primarily on several species of large pelagic fish, species that are also targeted by the Hawai‘i-permitted commercial deep-set longline fishery. False killer whales have been known to approach fishing lines in an attempt to procure bait or catch from the lines, a behavior known as depredation. This behavior can lead to the hooking or entanglement of an animal, which currently exceeds sustainable levels for pelagic false killer whales in Hawai‘i. Passive acoustic monitoring (PAM) was used to record false killer whales near longline fishing gear to investigate the timing, rate, and spatial extent of false killer whale occurrence. Acoustic data were collected using small autonomous recorders modified for deployment on the mainline of longline fishing gear. A total of 90 fishing sets were acoustically monitored in 2013 and 2014 on a chartered longline vessel using up to five acoustic recorders deployed throughout the fishing gear. Of the 102 odontocete click and/or whistle bouts detected on 55 sets, 26 bouts detected on 19 different fishing sets were classified as false killer whales with high or medium confidence based on either whistle classification, click classification, or both. The timing of false killer whale acoustic presence near the gear was related to the timing of fishing activities, with 57% of the false killer whale bouts occurring while gear was being hauled, with 50% of those bouts occurring during the first third of the haul. During three fishing sets, false killer whales were detected on more than one recorder, and in all cases the whales were recorded on instruments farther from the fishing vessel as the haul proceeded. Only three of the 19 sets with acoustically-confirmed false killer whale presence showed signs of bait or catch damage by marine mammals, which may relate to the difficulty of reporting depredation. PAM has proven to be a relatively inexpensive and efficient method for monitoring the Hawai‘i longline fishery for interactions with false killer whales.
- Marine conservation areas require high levels of compliance to meet conservation objectives, yet little research has assessed compliance quantitatively, especially for recreational fishers. Recreational fishers take 12% of global annual fish catches. With millions of people fishing from small boats, this fishing sector is hard to monitor, making accurate quantification of non-compliance an urgent research priority.
- Shore-based remote camera monitoring was tested for quantifying recreational non-compliance in near-shore, coastal rockfish conservation areas (RCAs) in the Salish Sea, Canada.
- Six high definition trail cameras were used to monitor 42 locations between July and August 2014.
- Seventy-nine percent of monitored conservation area sites showed confirmed or probable fishing activity, with no significant difference in fishing effort inside and outside RCAs.
- Mixed effects generalized linear models were used to test environmental and geographic factors influencing compliance. Sites with greater depth had significantly higher fishing effort, which may imply high, barotrauma-induced, rockfish mortality in RCA sites.
- Non-compliance estimates were similar to aerial fly-over compliance data from 2011, suggesting that trail camera monitoring may be an accurate and affordable alternative method of assessing non-compliance in coastal conservation areas, especially for community-based organizations wishing to monitor local waters.
- Widespread non-compliance could compromise the ability of RCAs to protect and rebuild rockfish populations. Increased education, signage, and enforcement is likely to improve compliance.
The expansion of shell disease is an emerging threat to the inshore lobster fisheries in the northeastern United States. The development of models to improve the efficiency and precision of existing monitoring programs is advocated as an important step in mitigating its harmful effects. The objective of this study is to construct a statistical model that could enhance the existing monitoring effort through (1) identification of potential disease-associated abiotic and biotic factors, and (2) estimation of spatial variation in disease prevalence in the lobster fishery. A delta-generalized additive modeling (GAM) approach was applied using bottom trawl survey data collected from 2001–2013 in Long Island Sound, a tidal estuary between New York and Connecticut states. Spatial distribution of shell disease prevalence was found to be strongly influenced by the interactive effects of latitude and longitude, possibly indicative of a geographic origin of shell disease. Bottom temperature, bottom salinity, and depth were also important factors affecting the spatial variability in shell disease prevalence. The delta-GAM projected high disease prevalence in non-surveyed locations. Additionally, a potential spatial discrepancy was found between modeled disease hotspots and survey-based gravity centers of disease prevalence. This study provides a modeling framework to enhance research, monitoring and management of emerging and continuing marine disease threats.