Other affiliations: University of Oslo
Bio: Tristan Rouyer is an academic researcher from IFREMER. The author has contributed to research in topics: Population & Tuna. The author has an hindex of 16, co-authored 34 publications receiving 988 citations. Previous affiliations of Tristan Rouyer include University of Oslo.
TL;DR: This work model the underlying causes of sardine–anchovy fluctuations, using the California Current Ecosystem as a case study, and shows that the dynamics are explained by interacting density-dependent processes and climate forcing.
Abstract: Since the days of Elton, population cycles have challenged ecologists and resource managers. Although the underlying mechanisms remain debated, theory holds that both density-dependent and density-independent processes shape the dynamics. One striking example is the large-scale fluctuations of sardine and anchovy observed across the major upwelling areas of the world. Despite a long history of research, the causes of these fluctuations remain unresolved and heavily debated, with significant implications for fisheries management. We here model the underlying causes of these fluctuations, using the California Current Ecosystem as a case study, and show that the dynamics, accurately reproduced since A.D. 1661 onward, are explained by interacting density-dependent processes (i.e., through species-specific life-history traits) and climate forcing. Furthermore, we demonstrate how fishing modifies the dynamics and show that the sardine collapse of the 1950s was largely unavoidable given poor recruitment conditions. Our approach provides unique insight into the origin of sardine–anchovy fluctuations and a knowledge base for sustainable fisheries management in the California Current Ecosystem and beyond.
TL;DR: This work used 1/ƒ β models to test cycles in the wavelet spectrum against a null hypothesis that takes into account the highly autocorrelated nature of ecological time series and used the maximum covariance analysis to compare the time-frequency patterns of numerous time series.
Abstract: In nature, non-stationarity is rather typical, but the number of statistical tools allowing for non-stationarity remains rather limited. Wavelet analysis is such a tool allowing for non- stationarity but the lack of an appropriate test for statistical inference as well as the difficulty to deal with multiple time series are 2 important shortcomings that limits its use in ecology. We present 2 approaches to deal with these shortcomings. First, we used 1/ƒ β models to test cycles in the wavelet spectrum against a null hypothesis that takes into account the highly autocorrelated nature of ecological time series. To illustrate the approach, we investigated the fluctuations in bluefin tuna trap catches with a set of different null models. The 1/ƒ β models approach proved to be the most consistent to discriminate significant cycles. Second, we used the maximum covariance analysis to compare, in a quantitative way, the time-frequency patterns (i.e. the wavelet spectra) of numerous time series. This approach built cluster trees that grouped the wavelet spectra according to their time-frequency patterns. Controlled signals and time series of sea surface temperature (SST) in the Mediterranean Sea were used to test the ability and power of this approach. The results were satisfactory and clusters on the SST time series displayed a hierarchical division of the Mediterranean into a few homogeneous areas that are known to display different hydrological and oceanic patterns. We discuss the limits and potentialities of these methods to study the associations between ecological and environmental fluctuations.
TL;DR: In this article, the authors combine time series analysis and simulations to investigate the long-term dynamics of an overexploited population in the Mediterranean Sea, and its link with both fishing-induced demographic changes and hydroclimatic variability.
Abstract: The synergistic effects of fishing, climate and internal dynamics on population fluctuations are poorly understood due to the complexity of these interac- tions. In this paper, we combine time series analysis and simulations to investigate the long-term dynamics of an overexploited population in the Mediterranean Sea, and its link with both fishing-induced demographic changes and hydroclimatic variability. We show that the cyclicity of the catch per unit of effort (CPUE) of Euro- pean hake Merluccius merluccius (EH) vanished in the 1980s, while the correlation between the CPUE and a local environmental index increased. Using simulations, we then show that the cyclicity observed in the EH bio- mass before the 1980s can have an internal origin, while that its disappearance could be due to the fishing- induced erosion of the age structure. Our results suggest that fishing can trigger a switch from internally gen- erated to externally forced population fluctuations, the latter being characterised by an increasing dependency of the population on recruitment and ultimately on envi- ronmental variability. Hydroclimatic modifications oc- curring in the Mediterranean in the early 1980s could have enhanced these changes by leading to a mismatch between early life stages of EH and favorable environ- mental conditions. Our conclusions underline the key effect of the interaction between exploitation and climate on the dynamics of EH and its important consequences for management and conservation.
TL;DR: For the Northeast Arctic stock of cod and the Norwegian Spring-Spawning stock of herring, age truncation was found to be associated with an increasing importance of temperature and a relatively decreasing importance of exploitation, while the population growth rate became increasingly sensitive to recruitment variations.
Abstract: Accumulating evidence shows that environmental fluctuations and exploitation jointly affect marine fish populations, and understanding their interaction is a key issue for fisheries ecology. In particular, it has been proposed that age truncation induced by fisheries exploitation may increase the population's sensitivity to climate. In this study, we use unique long-term abundance data for the Northeast Arctic stock of cod (Gadus morhua) and the Norwegian Spring-Spawning stock of herring (Clupea harengus), which we analyze using techniques based on age-structured population matrices. After identifying time periods with different age distributions in the spawning stock, we use linear models to quantify the relative effect of exploitation and temperature on the population growth rates. For the two populations, age truncation was found to be associated with an increasing importance of temperature and a relatively decreasing importance of exploitation, while the population growth rate became increasingly sensitive to recruitment variations. The results suggested that the removal of older age classes reduced the buffering capacity of the population, thereby making the population growth rate more dependent on recruitment than adult survival and increasing the effect of environmental fluctuations. Age structure appeared as a key characteristic that can affect the response of fish stocks to climate variations and its consequences may be of key importance for conservation and management.
TL;DR: It is concluded that the patterns of variations in fisheries time series of tuna and billfish only poorly reflect the underlying dynamics of these fish populations; they appear to be shaped by several successive embedded processes, each interacting with each other.
Abstract: The patterns of variations in fisheries time series are known to result from a complex combination of species and fisheries dynamics all coupled with environmental forcing (including climate, trophic interactions, etc.). Disentangling the relative effects of these factors has been a major goal of fisheries science for both conceptual and management reasons. By examining the variability of 169 tuna and billfish time series of catch and catch per unit effort (CPUE) throughout the Atlantic as well as their linkage to the North Atlantic Oscillation (NAO), we find that the importance of these factors differed according to the spatial scale. At the scale of the entire Atlantic the patterns of variations are primarily spatially structured, whereas at a more regional scale the patterns of variations were primarily related to the fishing gear. Furthermore, the NAO appeared to also structure the patterns of variations of tuna time series, especially over the North Atlantic. We conclude that the patterns of variations in fisheries time series of tuna and billfish only poorly reflect the underlying dynamics of these fish populations; they appear to be shaped by several successive embedded processes, each interacting with each other. Our results emphasize the necessity for scientific data when investigating the population dynamics of large pelagic fishes, because CPUE fluctuations are not directly attributable to change in species' abundance.
01 Jan 2016
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TL;DR: The basic properties of the wavelet approach for time-series analysis from an ecological perspective are reviewed, notably free from the assumption of stationarity that makes most methods unsuitable for many ecological time series.
Abstract: Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The versatility and attractiveness of the wavelet approach lie in its decomposition properties, principally its time-scale localization. It is especially relevant to the analysis of non-stationary systems, i.e., systems with short-lived transient components, like those observed in ecological systems. Here, we review the basic properties of the wavelet approach for time-series analysis from an ecological perspective. Wavelet decomposition offers several advantages that are discussed in this paper and illustrated by appropriate synthetic and ecological examples. Wavelet analysis is notably free from the assumption of stationarity that makes most methods unsuitable for many ecological time series. Wavelet analysis also permits analysis of the relationships between two signals, and it is especially appropriate for following gradual change in forcing by exogenous variables.
TL;DR: Mark A. Hixon et al. as discussed by the authors proposed a method to identify the most likely species for a particular species of fish in the Pacific Ocean, based on the results of a study conducted at the University of Hawaii at Mānoa.
Abstract: Mark A. Hixon1*, Darren W. Johnson2, and Susan M. Sogard3 Department of Biology, University of Hawai’i at Mānoa, Hawai’i, HI, USA Department of Biology, California State University, Long Beach, CA, USA Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, CA, USA *Corresponding Author: tel: +1 808 956 6437; e-mail: email@example.com
TL;DR: It is shown that winter weather and snow conditions, together with density dependence in the net population growth rate, account for the observed population dynamics of the rodent community dominated by lemmings in an alpine Norwegian core habitat between 1970 and 1997, and predict the observed absence of rodent peak years after 1994.
Abstract: Norwegian lemmings (Lemmus lemmus) are well known for their population cycles, which are thought, at their peak, to influence other ecosystem components. In fact the role of the physical environment — climate included — in determining rodent cycle dynamics has remained largely a matter of conjecture. Now from a combination of long-term (1970–2007) data on rodent density, bird densities and field estimates of snow pack conditions together with meteorological data, a clearer picture of the lemming cycle has been obtained. What emerges is a marked shift away from the familiar 3–5-year rodent cycles to an aperiodic, mostly low-amplitude state, which can be explained and predicted by the between-year variations in winter climate. There is strong evidence for the hypothesis that climate effects on rodent dynamics are transmitted to other parts of the ecosystem. The population cycles of rodents at northern latitudes have puzzled people for centuries1,2, and their impact is manifest throughout the alpine ecosystem2,3. Climate change is known to be able to drive animal population dynamics between stable and cyclic phases4,5, and has been suggested to cause the recent changes in cyclic dynamics of rodents and their predators3,6,7,8,9. But although predator–rodent interactions are commonly argued to be the cause of the Fennoscandian rodent cycles1,10,11,12,13, the role of the environment in the modulation of such dynamics is often poorly understood in natural systems8,9,14. Hence, quantitative links between climate-driven processes and rodent dynamics have so far been lacking. Here we show that winter weather and snow conditions, together with density dependence in the net population growth rate, account for the observed population dynamics of the rodent community dominated by lemmings (Lemmus lemmus) in an alpine Norwegian core habitat between 1970 and 1997, and predict the observed absence of rodent peak years after 1994. These local rodent dynamics are coherent with alpine bird dynamics both locally and over all of southern Norway, consistent with the influence of large-scale fluctuations in winter conditions. The relationship between commonly available meteorological data and snow conditions indicates that changes in temperature and humidity, and thus conditions in the subnivean space, seem to markedly affect the dynamics of alpine rodents and their linked groups. The pattern of less regular rodent peaks, and corresponding changes in the overall dynamics of the alpine ecosystem, thus seems likely to prevail over a growing area under projected climate change.
TL;DR: In this paper, the authors review how exploitation, by altering the structure of populations and ecosystems, can modify their ability to respond to climate and show that demographic effects of fishing (removal of large-old individuals) can have substantial consequences on the capacity of populations to buffer climate variability through various pathways (direct demographic effects, effects on migration, parental effects).