Ecosystem-based approaches to fisheries management (EAFMs) have emerged as requisite for sustainable use of fisheries resources. At the same time, however, there is a growing recognition of the degree of variation among individuals within a population, as well as the ecological consequences of this variation. Managing resources at an ecosystem level calls on practitioners to consider evolutionary processes, and ample evidence from the realm of fisheries science indicates that anthropogenic disturbance can drive changes in predominant character traits (e.g. size at maturity). Eco-evolutionary theory suggests that human-induced trait change and the modification of selective regimens might contribute to ecosystem dynamics at a similar magnitude to species extirpation, extinction and ecological dysfunction. Given the dynamic interaction between fisheries and target species via harvest and subsequent ecosystem consequences, we argue that individual diversity in genetic, physiological and behavioural traits are important considerations under EAFMs. Here, we examine the role of individual variation in a number of contexts relevant to fisheries management, including the potential ecological effects of rapid trait change. Using select examples, we highlight the extent of phenotypic diversity of individuals, as well as the ecological constraints on such diversity. We conclude that individual phenotypic diversity is a complex phenomenon that needs to be considered in EAFMs, with the ultimate realization that maintaining or increasing individual trait diversity may afford not only species, but also entire ecosystems, with enhanced resilience to environmental perturbations. Put simply, individuals are the foundation from which population- and ecosystem-level traits emerge and are therefore of central importance for the ecosystem-based approaches to fisheries management.
Target 19, set by the Convention on Biological Diversity, seeks to improve the knowledge, science base, and technologies relating to biodiversity. We will fail to achieve this target unless prolific biases in the field of conservation science are addressed. We reveal that comparatively less research is undertaken in the world’s most biodiverse countries, the science conducted in these countries is often not led by researchers based in-country, and these scientists are also underrepresented in important international fora. Mitigating these biases requires wide-ranging solutions: reforming open access publishing policies, enhancing science communication strategies, changing author attribution practices, improving representation in international processes, and strengthening infrastructure and human capacity for research in countries where it is most needed.
Environmental and natural resource management in Australia occurs at a regional scale with many initiatives underpinned by an ecosystem services framework that aims to integrate economic, social and ecological values in decision-making. This research examines potential influences on value integration by identifying stakeholder perspectives for coastal ecosystem services using mangroves in south-east Queensland as a case study. The study site is one of Australia's fastest growing regions and exhibits a “hotbed of issues” with institutional complexity in coastal areas where urban development is concentrated. Q-methodology was used to systematically study stakeholder perspectives on coastal ecosystem services and identify natural groupings between stakeholders with shared values. A total of 43 respondents representing nine stakeholder categories were interviewed. Factor analysis identified four perspectives that were labelled: (1) Green Infrastructure; (2) Recreational Opportunity and Well-being; (3) Sustaining Regional Industries and Communities; and (4) Coastal Living. The concept of ecosystem ‘bundles’ was conducive to analysing the range of services valued by different perspectives and highlighted stakeholder priorities that underpin demand for coastal ecosystem services. Stakeholder perspectives show potential to influence coastal policy according to the ecosystem service categories that are prioritised in decision-making and the saliency of the services to the stakeholder group. This research contributes to the field of coastal management where a lack of progress on “well-documented problems” partly stems from governance failure to capture and consider pluralistic values in decision-making and exacerbates conflict between contested views.
Maine hosts numerous rural fishing villages that contribute greatly to the State's economy and culture. The cumulative effects of fisheries regulation, stock depletion, amenity migration and rural restructuring have impacted these communities in complex ways. Drawing on ethnographic research, interviews, and secondary data we have identified the patterns of change as symptomatic of gentrification, and we have investigated how these changes are affecting the communities' vulnerability and resilience. Gentrification of coastal property by amenity migrants is responsible for the displacement of community members, including fishermen. The loss-of-access to the waterfront has increased their sensitivity to future threats. Further changes in the demographics and economies of the communities have increased social and cultural conflicts. Nevertheless, this paper also demonstrates that gentrification can increase the resilience of the community. Amenity migrants have the capacity and desire to provide social and philanthropic support, and rural restructuring introduces new economic opportunities and sources of revenue. The underlying consequences of gentrification are difficult to discern from secondary data alone, and we argue that the ethnographic approach is crucial. Through interview responses we have identified an identity crisis in these communities undergoing gentrification, with many of the conflicts over the future importance of fishing to the community.
This review discusses the role of ecogenomic sensors in biological oceanography. Ecogenomic sensors are instruments that can autonomously collect biological samples and perform molecular analyses. This technology reduces logistical constraints on the length and duration of biological data collection. Autonomous, robotic performance of molecular assays shows particular promise in the field of public health. Recent applications include simultaneous detection of harmful algal species and fecal markers paired with same-day remote reporting of test results. Ecogenomic instruments are also showing promise for molecular ecological studies. Autonomous collection and preservation of biological samples is facilitating high-resolution ecological studies that are expanding our understanding of marine microbial ecology and dynamics. This review discusses recent applications of these instruments and makes recommendations for future developments.
Brown shrimp (Farfantepenaeus aztecus) support a commercially important fishery in the northern Gulf of Mexico, and juveniles use coastal estuaries as nurseries. Production of young shrimp from any given bay system, and hence commercial harvest of sub-adults and adults from the Gulf, is highly variable from year to year. We describe development of a spatially-explicit, individual-based model representing the cumulative effects of temperature, salinity, and access to emergent marsh vegetation on the growth and survival of young brown shrimp, and we use the model to simulate shrimp production from Galveston Bay, Texas, U.S.A. under environmental conditions representative of those observed from 1983 to 2012. Simulated mean annual (January through August) production ranged from 27.5 kg ha−1 to 43.5 kg ha−1 with an overall mean of 34.3 kg ha−1(±0.70 kg ha−1 SE). Sensitivity analyses included changing values of key model parameters by ±10% relative to baseline. Increasing growth rates 10% caused a 16% increase in production, whereas a 10% decrease resulted in an 18% decrease in production. A 10% increase in mortality probabilities resulted in a production decrease of 15% while a 10% decrease resulted in an 18% increase in production. We also changed values of environmental input data by ±10%. Mean production estimates increased 11% in response to increasing tide heights (and thus, marsh habitat access) and decreased 19% with a decrease in tide height (and marsh access). The thirty year mean production was affected negatively by both the 10% increase and decrease in air temperature (−2% and −14%, respectively). Simulations in which bay water salinities were entirely low (0–10 PSU), intermediate (10–20 PSU), or high (>20 PSU) resulted in mean baseline production rates being reduced by 55, 7, and 0%, respectively. Uncertainty in model estimates of shrimp production were related to the magnitude and the timing of postlarval shrimp recruitment to the bay system. Simulations indicated that mean production decreased when recruitment occurred earlier in the year under all environmental conditions. Mean production varied with environmental conditions, however, when recruitment was delayed. The model reproduced biomass and size distribution patterns observed in field data. Although annual variability of modeled shrimp production did not correlate well (R2 = 0.005) with fisheries independent trawl data from Galveston Bay, there was a significant correlation with similar trawl data collected in the northern Gulf of Mexico (R2 = 0.40; p = 0.0005). Identifying and representing spatially variable factors such as predator distribution and abundance among bays, therefore, may be the key to understanding bay-specific contributions to the adult stock.
The need for effective multi-level governance arrangements is becoming increasingly urgent because of complex functional interdependencies between biophysical and socioeconomic systems. We argue that social capital plays an important role in such systems. To explore the relationship between social capital and participation in resource governance arenas, we analyzed various small-scale fisheries governance regimes from the Gulf of California, Mexico. The components of social capital that we measured include levels of fishers’ structural ties to relevant groups and levels of trust in different entities (i.e. cognitive component). We collected data using surveys and interviews with residents of small-scale fishing communities adjacent to marine protected areas. We analyzed the data using a logistic regression model and narrative analysis. The results of our quantitative analysis highlight the multidimensional nature of social capital and reveals complex relationships between different types of social capital and fisher participation in monitoring, rulemaking and MPA design. Furthermore our qualitative analysis suggests that participation in fisheries conservation and management is not fully potentialized due to the social and historical context of participatory spaces in Mexico.
The Salton Sea, the largest inland surface water body in California, has been designated as a sensitive ecological area by federal and state governments. Its two main tributaries, the New River and Alamo River are impacted by urban and agriculture land use wastes. The purpose of this study was to temporally and spatially evaluate the ecological risks of contaminants of concern in water, sediments and fish tissues. A total of 229 semivolatile organic compounds and 12 trace metals were examined. Among them Selenium, DDTs, PAHs, PCBs, chlorpyrifos and some current-use pesticides such as pyrethroids exceeded risk thresholds. From 2002 to 2012, measurements of chlorpyrifos in sediments generally declined and were not observed after 2009 at the river outlets. In contrast, pyrethroid concentrations in sediments rose consistently after 2009. In water samples, the outlets of the two rivers showed relatively higher levels of contamination than the main water body of the Salton Sea. However, sediments of the main water body of the Salton Sea showed relatively higher sediment concentrations of contaminants than the two rivers. This was particularly true for selenium which showed reductions in concentrations from 2002 to 2007, but then gradual increases to 2012. Consistent with water evaluations, contaminant concentrations in fish tissues tended to be higher at the New River boundary and at the drainage sites for the Alamo River compared to sites along each river. The persistent contaminants DDTs, PAHs, chlorpyrifos and several pyrethroid insecticides were associated with the toxicity of sediments and water collected from the rivers. Overall, assessment results suggested potential ecological risk in sediments of the Salton Sea as well as in water and fish from the two rivers.
This study suggests strategies for conducting an offshore wind farm site selection and evaluates feasible offshore wind farm sites in the coastal areas of Jeju Island, South Korea. The site selection criteria are classified into four categories: energy resources and economics, conservation areas and landscape protection, human activities, and the marine environment and marine ecology. We used marine spatial techniques from GIS and the investigated resources available in the country. The results indicate that offshore wind farms can be located along a wide range of the eastern and western coasts of Jeju Island, considering energy resources and economics only. However, when considering the four categories presented in this study, the number of feasible offshore wind farm sites was significantly less than when only energy resources and economics were considered. The data and analysis presented in this study will be useful for the offshore wind farm site selection around Jeju Island, and it will also contribute to minimizing the environmental impacts and reducing the social conflicts between stakeholders.
Geographically weighted regression (GWR) is a relatively new technique to explore spatially-varying relationships between biological and environmental processes. It allows parameters to vary over space and assumes data to follow a normal distribution. We extend GWR to a geographically weighted generalized linear model (GW-GLM) by incorporating statistical distributions other than the normal distribution (i.e., the binomial distribution). We demonstrate the application of GW-GLM with an empirical example, U.S. Atlantic pelagic longline seabird bycatch. Due to the high percentage of zero observations in the seabird bycatch data, we analyzed the positive catch rates (number of seabirds caught per 1000 hooks) and the probability of catching a seabird separately. Parameter estimates exhibited considerable spatial variation, especially for target catch rate when analyzing the positive catch data, and for intercept, water depth and water temperature when estimating the probability of catching seabirds. We compared model performance of GW-GLM with a global generalized linear model, a mixed effect model with a random areal effect, and a spatial expansion model that is an early technique to model spatially-varying ecological relationships by modeling each of the parameters as a function of location. The GW-GLM performed best. Simulations with hypothetical datasets having different percentages of zeros showed that, regardless of the zero percentage in the data, GW-GLM performed best on average. Applying a range of bandwidth indicated that the GW-GLM was more robust to an overestimated bandwidth than an underestimated bandwidth.