Abstract
The population of European anchovy of the Bay of Biscay collapsed at the beginning of the 21st century, causing the closure of its fishery between 2005 and 2010. In order to study both the ...human and environmental causes of the anchovy population dynamics, an approach coupling individual bioenergetics to an individual-based model was applied between 2000 and 2015. This modelling framework was forced with outputs from a physical–biogeochemical model. In addition to a base-case scenario with realistic forcing, alternative scenarios were run without inter-annual variability in either fishing mortality or environmental conditions. During the decrease in population biomass, a high fishing pressure coincided with a combination of environmental variables promoting the appearance of large individuals that could not survive severe winters because of their high energetic demands. The recovery of the population was favoured by a period of warm years with abundant food favouring the winter survival of age 1 individuals, in coincidence with the closure of the fishery. Our modelling approach also allows to test the consequences of a retrospective implementation of the current harvest control rule from 2000 which, according to our results, would have prevented the collapse of the population and avoided the fishery closure.
Sound scattering layers (SSLs) are observed over a broad range of spatio-temporal scales and geographical areas. SSLs represent a large biomass, likely involved in the biological carbon pump and the ...structure of marine trophic webs. Yet, the taxonomic composition remains largely unknown for many SSLs. To investigate the challenges of SSL sampling, we performed a survey in a small study area in the Northern Bay of Biscay (France) by combining broadband and narrowband acoustics, net sampling, imagery and video recordings. In order to identify organisms contributing to the observed SSLs, we compared measured frequency spectra to forward predicted spectra derived from biological data. Furthermore, to assess the confidence in SSL characterization, we evaluated uncertainties in modeling, acoustical and biological samplings. Here, we demonstrate for the first time that SSL backscattering intensity in the Bay of Biscay can be dominated in springtime by resonant gas bearing organisms below 100 kHz, namely siphonophores and juvenile fishes and by pteropods at higher frequencies. Thus, we demonstrate the importance of broadband acoustics combined to nets, imagery and video to characterize resonant backscatterers and mixed mesozooplankton assemblages.
Declines in individuals' growth in exploited fish species are generally attributed to evolutionary consequences of size‐selective fishing or to plastic responses due to constraints set by changing ...environmental conditions dampening individuals' growth. However, other processes such as growth compensation and non‐directional selection can occur and their importance on the overall phenotypic response of exploited populations has largely been ignored. Using otolith growth data collected in European anchovy and sardine of the Bay of Biscay (18 cohorts from 2000 to 2018), we parameterized the breeder's equation to determine whether declines in size‐at‐age in these species were due to an adaptive response (i.e. related to directional or non‐directional selection differentials within parental cohorts) or a plastic response (i.e. related to changes in environmental). We found that growth at age‐0 in anchovy declined between parents and their offspring when biomass increased and the selective disappearance of large individuals was high in parents. Therefore, an adaptive response probably occurred in years with high fishing effort and the large increase in biomass after the collapse of this stock maintained this adaptive response subsequently. In sardine offspring, higher growth at age‐0 was associated with increasing biomass between parents and offspring, suggesting a plastic response to a bottom‐up process (i.e. a change in food quantity or quality). Parental cohorts in which selection favoured individuals with high growth compensation produced offspring high catch up growth rates, which may explain the smaller decline in growth in sardine relative to anchovy. Finally, on non‐directional selection differentials were not significantly related to the changes in growth at age‐0 and growth compensation at age‐1 in both species. Although anchovy and sardine have similar ecologies, the mechanisms underlying the declines in their growth are clearly different. The consequences of the exploitation of natural populations could be long lasting if density‐dependent processes follow adaptive changes.
Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology. The spatial distribution of fish populations observed in the wild results from ...the complex interactions of multiple controls both external or internal to the fish populations. Whilst species distribution models (SDMs) have been mostly concerned with static description of species distribution as a function of environmental constraints, models of animal movements (MAMs) have focussed on the dynamic nature of spatial distribution of groups of individuals under a number of constraints external and internal to the population. Besides SDMs and MAMs, modelling the spatial distribution of fish populations can be achieved by models that are fundamentally static (like SDMs) but can also incorporate many hypotheses on the control of fish spatial distribution (like MAMs). The hypotheses underlying these models need to make sense at the population level ‐ rather than at the individual or species level –we term these ‘population distribution models’ (PDMs). PDMs are statistical models that rely on several hypotheses, which include: (i) control through geographical attachment, (ii) environmental conditions, (iii) density‐dependent habitat selection, (iv) spatial dependency, (v) population demographic structure, (vi) species interactions and (vii) population memory. We review the basis behind each of these conceptual models and we examine corresponding numerical applications. We argue that the conceptual models are complementary rather than competing, that existing numerical applications are still rarely compared and combined, and that PDMs can offer a statistical framework to achieve this. We recommend that the numerical models associated with different hypotheses be constructed within such a common general framework. This will permit evaluation, comparison and combination of the multiple hypotheses on fish spatial distribution. It will ultimately lead to a more comprehensive understanding of the factors controlling the spatial distribution of fish populations and to more accurate predictions in which model uncertainty is accounted for.
Spawning location and timing are critical for understanding fish larval survival. The impact of a changing environment on spawning patterns is, however, poorly understood. A novel approach is to ...consider the impact of the environment on individual life histories and subsequent spawnings. In the present work, we extend the Dynamic Energy Budget (DEB) theory to investigate how environment variability impacts the spawning timing and duration of a multiple-batch spawning species. The model is successfully applied to reproduce the growth and reproduction of anchovy (
Engraulis encrasicolus) in the Bay of Biscay. The model captures realistically the start and ending of the spawning season, including the timing of the spawning events, and the change in egg number per batch. Using a realistic seasonal forcing of temperature and food availability derived from a bio-physical model, our simulation results show that two thirds of the total spawned mass already accumulates before the start of the spawning season and that the condition factor increases with body length. These simulation results are in accordance with previous estimations and observations on growth and reproduction of anchovy. Furthermore, we show how individuals of equal length can differ in reproductive performance according to the environmental conditions they encounter prior to the spawning season. Hatch date turns out to be key for fecundity at age-1 as it partly controls the ability to build up reserves allocated to reproduction. We suggest the model can be used to realistically predict spawning in spatially and temporally varying environments and provide initial conditions for bio-physical models used to predict larval survival.
Geostatistical techniques were applied and a series of spatial indicators were calculated (occupation, aggregation, location, dispersion, spatial autocorrelation and overlap) to characterize the ...spatial distributions of European anchovy and sardine during summer. Two ecosystems were compared for this purpose, both located in the Mediterranean Sea: the Strait of Sicily (upwelling area) and the North Aegean Sea (continental shelf area, influenced by freshwater). Although the biomass of anchovy and sardine presented high interannual variability in both areas, the location of the centres of gravity and the main spatial patches of their populations were very similar between years. The size of the patches representing the dominant part of the abundance (80%) was mostly ecosystem- and species-specific. Occupation (area of presence) appears to be shaped by the extent of suitable habitats in each ecosystem whereas aggregation patterns (how the populations are distributed within the area of presence) were species-specific and related to levels of population biomass. In the upwelling area, both species showed consistently higher occupation values compared to the continental shelf area. Certain characteristics of the spatial distribution of sardine (e.g. spreading area, overlapping with anchovy) differed substantially between the two ecosystems. Principal component analysis of geostatistical and spatial indicators revealed that biomass was significantly related to a suite of, rather than single, spatial indicators. At the spatial scale of our study, strong correlations emerged between biomass and the first principal component axis with highly positive loadings for occupation, aggregation and patchiness, independently of species and ecosystem. Overlapping between anchovy and sardine increased with the increase of sardine biomass but decreased with the increase of anchovy. This contrasting pattern was attributed to the location of the respective major patches combined with the specific occupation patterns of the two species. The potential use of spatial indices as auxiliary stock monitoring indicators is discussed.
The spatial extent of small pelagic fish spawning habitat is influenced by environmental factors and by the state of the adult population. In return, the configuration of spawning habitat affects ...recruitment and therefore the future structure of the adult population. Interannual changes in spatial patterns of spawning reflect variations in adult population structures and their environment. The present study describes the historical changes in the spatial distribution of spawning of anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) in the Bay of Biscay during two periods: 1967–72 and 2000–2004. Using data from egg surveys conducted in spring, the spatial distributions of anchovy and sardine eggs are characterized by means of geostatistics. For each survey, a map of probability of egg presence is constructed. The maps are then compared to define (1) recurrent spawning areas, (2) occasional spawning areas and (3) unfavourable spawning areas during each period. Sardine spawning habitat is generally fragmented and appears spatially limited by the presence of cold bottom water. It is confined to coastal or shelf break refuge areas in years of restricted spawning extent. For anchovy, recurrent spawning sites are found in Gironde and Adour estuaries whilst spawning can extend further offshore in years of more intense spawning. For both species, the mean pattern of spawning has changed between 1967–72 and 2000–2004. Noticeably, the spatial distribution of anchovy eggs in spring has expanded northward. This trend possibly results from changes in environmental conditions during the last four decades.
This paper presents a novel application of the geostatistical multivariate method known as min–max autocorrelation factors (MAFs) for analysing fisheries survey data in a space–time context. The ...method was used to map essential fish habitats and evaluate the variability in time of their occupancy. Research surveys at sea on marine fish stocks have been undertaken for several decades now. The data are time series of yearly maps of fish density, making it possible to analyse the space–time variability in fish spatial distributions. Space–time models are key to addressing conservation issues requiring the characterization of variability in habitat maps over time. Here, the variability in fisheries survey data series is decomposed in space and time to address these issues, using MAFs. MAFs were originally developed for noise removal in hyperspectral multivariate data and are obtained using a specific double principal components analysis. Here, MAFs were used to extract the most continuous spatial components that are consistent in time, together with the time series of their amplitudes. MAFs formed an empirical isofactorial model of the data, which served for kriging in each year using all available information across the data series. The approach was applied on the spawning distributions of sardine in the Bay of Biscay from 2000 to 2017. A multivariate approach for dealing with space–time data was adapted here, because the evolution in time was highly variable. Maps were classified using the amplitudes of the MAFs, and groups of typical distributions were identified, which showed different occurrence probabilities in different periods.
The closure of the anchovy (Engraulis encrasicolus) fishery in the Bay of Biscay between 2005 and 2010 because of low biomass levels provided an opportunity to estimate natural mortality using data ...from egg (daily egg production method, DEPM) and acoustic surveys implemented for the assessment of this population since 1987. Assuming that natural mortality (M) is constant over time and that catchability in both surveys is equal for all ages, M could be estimated using log-linear models on the series of surveys of population numbers at age and seasonal integrated stock assessments. The analysis suggests M values of around 0.9 for a common natural mortality at all ages. However, we found firm evidence that natural mortality at ages 2 and older (M2+) is markedly higher than at age 1 (M1), which indicates senescent mortality, a possibility suggested a long time ago for this type of short-lived species.
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