Population dynamics of benthic shellfisheries in the north of Chile: the role of denso-dependent processes and oceanographic forcing Marcelo M. Rivadeneira 1, 2 , Raúl Ulloa 3 , Adolfo Vargas 4,5 & Cristian Hudson 5 1Centro de Estudios Avanzados en Zonas Áridas (CEAZA) & Facultad de Ciencias del Mar, Universidad Católica del Norte, P.O. Box 117, Coquimbo, Chile 2Center for Advanced Studies in Ecology and Biodiversity (CASEB), Departamento de Ecología Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile 3Centro Regional de Investigación Pesquera, Instituto Nacional de Pesca, Dirección General de Investigación Pesquera Pacifico Norte. Miguel Alemán sur Nº605, C.P. 85400, Guaymas, Sonora, México 4Centro de Investigación y Desarrollo de Profesionales Marinos Pacífico Ltda. Vivar 1218, Iquique, Chile 5Programa Magíster en Ciencias Aplicadas mención Biología Pesquera, Departamento Ciencias del Mar, Universidad Arturo Prat, P.O. Box 121, Iquique, Chile Abstract: The need of establish sustainable fishing policies clashes against the incapability of many models to integrate mechanistically, yet in a simple way, the role played by biological ( i.e. endogenous) and physical (i.e. exogenous, oceanographic) forcing in the regulation of population dynamics. In this work we evaluate the importance of endogenous and exogenous factors in the regulation of population dynamic in 10 benthic species commercially exploited by the fishing artisanal fleet along northern coast of Chile. The information was gathered from annual time series of CPUE (captures per unit of effort) between 1998 and 2005. The population growth rate (i.e. interannual changes in the CPUE) was modeled as an autoregressive lineal process, evaluating the importance of first-order lags (1 year) of CPUE, and oceanographic factors (southern oscillation index, sea surface temperature, and upwelling index). In all species, the best models included the effect of both endogenous and exogenous factors, explaining a high percentage of the variance of the population growth rate (in average 88 %). These results support the idea that the studied populations, despite being under an exploitation regime, show a strong regulation seemingly produced by the combined effect of intraspecific interactions and physical forcing molding the abundance during the early stages of the species. Our results highlight the importance of these kinds of models as a powerful tool to evaluate the processes underlying the regulation of natural populations. Key words: artisanal fisheries, Pacific South America, autoregressive model, El Niño, coastal upwelling
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Population dynamics of benthic shellfisheries in the north of Chile: the role of denso-dependent processes
In this framework, the role of environmental forcings (e.g. , the Child, transport offshore) would be made a
manifest through the dense structure-dependence on the population, and could be modeled explicitly, in
linear terms or non-linear (Stenseth et al. 2002). The action of both mechanisms and its time lag would be
causing the populations to vary in the time (short and/or medium-term), although in the long term, the
abundance of the population is stationary (do permanently stationary or determined by the load capacity of
the environment, which may also have different levels? ). Then, the existence of natural cycles in the
abundance of populations, evident also in benthic species, that could and should be considered explicitly in
the fisheries management plans. In the present study raises the explicit use of this approach of analysis is to
allow glimpse possible processes and mechanisms that govern temporary fluctuations in benthic fisheries in
the north of Chile.
In particular, it evaluates the adjustment autoregressive models that consider endogenous and exogenous
effects on the population dynamics of 10 species. This step would be key in the generation of effective
management measures for these resources.
Material y métodos
Obtaining time series of CPUE: information was obtained from a database of the follow-up project of
benthic fisheries executed by the Fisheries Development Institute of Chile (FIFG), where are documented
catches (kg) for various benthic resources in a total of 231 sites (backgrounds) distributed from Africa to the
south of Antofagasta (ca.18 ° -25 °S), covering an area of ca. 800 Km of coastline, between the years 1998-
2005. In order to obtain a synoptic view, chose to ignore trends space as well as temporal trends intra-
annual, by expressing the total annual catch as for each resource. As a measure of fishing effort is used the
number of trips made to that origin for that resource and year. Of the total of 30 species recorded only
analysis was performed with 10 of them, since they correspond to the 98% of this information (Table 1).
Obtaining of oceanographic information: synoptic oceanographic information was obtained in the form of
annual averages for the entire region considering the period 1998-2005. Three oceanographic variables
were analyzed: sea surface temperature (SST), index of Southern Oscillation (SOI), and index of upwelling
(UPW). It generated an average annual regional TSM using the information obtained for three main ports
(Arica, Iquique, Antofagasta) using in-situ measurements (CENDOHC-SHOA). The average annual value of
SOI and UPW (transport offshore Ekman) was obtained from time series available at NOAA, and were
recovered in your web site (http://www.pfeg.noaa.gov:16080/products/PFEL/) finally these values were
obtained by averaging the values of 3 stations that are available for each fishing site in the region of study.
Analysis of population dynamics: We evaluated the population dynamics at the regional level of each of the
species, by modeling the time series of population growth rates (Lima 2001, Stenseth et al. 2002, Belgrano
et al. 2004B):
Where: it is the intrinsic rate of population growth in the t year, y, and corresponds to the CPUE in the t and
the previous year, respectively.
If this is a feature that gives an account of the relationship between y and , and the delays, then:
Where: It is a linear relationship of dependency between and the delays of abundance.
Due to the short length of the time series (8 years) were evaluated only dynamic of first order (delay for 1
year). In this way, in his simpler version (linear) population dynamics could be modeled on the basis of:
Where:
y are parameter to find the estimate of y
Where: ENV is from any of the oceanographic variables evaluated (TSM, SOI, and UPW).
The choice of the best models was carried out using the Akaike Information Criterion (AIC), where all the
models with a ∆AIC<2 and AIC weighted>0.2 , were considered equally probable. All analysis were carried
out using routines written in the program R (Team 2008).
Results
The populations studied showed different temporal dynamics (Fig 2). The cholga mussel, crab and the hairy
octopus fluctuations showed relatively small populations during the period of analysis. Species such as the
locate and the choro showed sharp increases in the CPUE, whereas the piure, culengue showed drops and
clam population. Other species exhibited fluctuations with more marking, such as the scarlet macaw black,
whose abundance ranged over 2 orders of magnitude in the study. Of the total of 11 models evaluated for
each species (110 in total), only 1-2 were selected in each case (Table 2). The selected models in general
accounted for much of the variance of the population growth (R² average =0.88 [0.46 , 0.99 ], Table 2), so
that the population dynamics of these species was generally well captured by such models (Fig 2). All the
models selected incorporated at the same time effects density-dependent and at least one variable
oceanographic. More than half of the selected models (8 of 15) incorporated delays of first order in the CPUE
and the three variables studied oceanographic. The sign and intensity of the coefficients auto-regressive
associated was variable between species. While the ratio of density-dependence was always negative, the
coefficients associated with the TSM, SOI, and UPW were positive or negative.
Discusión
The results confirm the existence of a marked population regulation in the 10 species of benthic
analysis. This regulation would emerge from the joint action of density-dependent processes and
oceanographic forcing through the feedback of population structure. Traditionally it has been
argued that the oceanographic forcing would have a leading role in fluctuations in abundance of
fisheries (Yañez et al. 2001, Yáñez et al. 2002, Lehodey et al. 2006, Friedemann & Wolff 2008).
However, oceanographic modeling of radiative forcing to the interior structure of the density-
dependent is somewhat recent (Belgrano et al. 2004A, 2004b, Pedraza-Garc ia & Cubillos 2008).
The results give evidence that there are endogenous and exogenous mechanisms that regulate the
overall dynamics of the populations studied. On the one hand, the existence of an endogenous
regulation density-dependent is evident by the negative sign of the coefficients of density-
dependence, α, of all the autoregressive models (Table 2), suggesting that feedback processes of
population of first order would be key in the population dynamics.
. In this sense, a large number of empirical studies validated the importance of larval settlement and
recruitment as a determinant of the structure of populations and marine communities on the coast of
Chile (Lakes et al. 2005, Navarrete et al. 2005). However, it cannot be ruled out a priori in the
existence of delays of higher order ( Pedraza-Garc ia & Cubillos 2008), which would reflect inter-
specific processes (e.g. competition and predation) whose relevance as mechanisms of population
regulation is suggested by empirical evidence (Castile 1999, Gaymer et al. 2004, Vásquez et al.
2006, Gaymer & Himmelman 2008, Navarrete & Manzur 2008). Time Series of greater extension
(> 10 years) would make possible the implementation of these models. On the other hand, these
processes of feedback also would be forced by exogenous factors (i.e. , oceanography) that would
work together by regulating populations, as has been observed in species of marine phytoplankton
(Belgrano et al. 2004A, 2004b).
Experimental studies show that the structure and dynamics of populations and marine communities
in the southeastern coast of the Pacific is heavily governed by stressors of low frequency as El
Niño(Chavez et al. 1999, Thiel et al. 2007) As well as by the larval dispersal patterns generated by
the cells of coastal upwelling (Lakes et al. 2005, Navarrete et al. 2005, Lakes et al. 2008). However
the population effects of these factors track structure density-dependent only have been evident in
the present study. The underlying mechanisms are much less well known, but it is possible that
factors such as SOI indirectly affect recruitment rates of the species, track changes in the intensity
of the transport offshore (Connolly & Roughgarden 1999), or changes in vital rates induced by the
temperature of the sea (Urban 1994, Wolff et al. 2007). However, the direction and intensity of the
coefficients associated with each variable oceanographic was highly variable between species,
which is not strange as there is empirical evidence that indicates that the responses of marine
populations to ENSO events would be species-specific (Díaz & System 1993). The foregoing
suggests that ecological features and/or the history of life could also play a predominant role in
population dynamics. Time series analysis more extensive and the explicit inclusion of the space
(e.g. , analyzing the spatial synchrony of population dynamics) in species with different life
strategies could shed more light on the mechanisms that govern the different population responses
to oceanographic forcing.
The present study demonstrated the feasibility of applying simple autoregressive models for
understanding the role of biological interactions and oceanographic stressors in the regulation of
marine populations. Similar models or more complex (i.e. , non-linear, second-order delays,
explicitly including interactions predator-prey, Pedraza-Garc ia & Cubillos 2008) could be applied
to other stocks for which there are estimates of relative abundance of species. The results obtained
by these simple models could serve as a basis for the development of more sophisticated models
with a view to a sustainable management of marine ecosystems.
Table 1. Main characteristics of the species in this study. Status of holdings according to SubPesca (PE: full exploitation, THE: free access, LAC: free access to administrative restrictions).
Table 1. Main characteristics of the species this study. The exploitation status according SubPesca Chile (PE: fully exploited, THE: open access, LAC: open access with administrative restrictions).
Fig 2. Population Dynamics of 10 marine species commercially extracted by the artisanal fishing
fleet between 1998-2005. The expected values were estimated using the parameters of the
autoregressive model with the best fit for each species (see Table 2).
Fig 2. Population dynamics of 10 marine species exploited by artisanal shellfisheries between
1998-2005. The expected values were estimated using the parameters yielded by the best
autoregressive model for each species (see Table 2).
Agradecimientos
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Tabla 1. Principales características de las especies de este estudio. Estatus de explotación de acuerdo a SubPesca (PE: plena explotación, LA: libre acceso, LAC:
libre acceso con restricciones administrativas).
Table 1. Main characteristics of the species this study. The exploitation status according SubPesca Chile (PE: fully exploited, LA: open access, LAC: open access
with administrative restrictions).
CPUE (kg
viaje-1)
N° de procedencias por año
Taxa Nombre científico Nombre
común
Estatus de
explotació
n
Promedio Promedio Mínimo Máximo
Gastropoda Thais chocolata (Duclos, 1832) Caracol
locate
LAC 390 73 52 90
Echinoidea Loxechinus albus (Molina, 1782) Erizo PE 228 77 28 126Bivalvia Aulacomya atra (Molina, 1782) Cholga PE 208 63 45 71Tunicata Pyura chilensis Molina, 1782 Piure LA 199 65 31 83Bivalvia Gari solida (Gray, 1828) Culengue PE 76 25 5 47Bivalvia Protothaca thaca (Molina, 1782) Almeja PE 70 52 40 69Bivalvia Mytilus chilensis (Hupé 1854) Choro PE 62 16 11 23Decapoda Cancer setosus Fabricius, 1798 Jaiba peluda LAC 54 58 14 74Gastropoda Fissurella latimarginata Lesson,
Tabla 2. Evaluación de los 11 Modelos auto-regresivos de primer orden de análisis de las dinámicas poblacionales de cada especie (retraso de 1 año en la señal).
Table 2. Summary if the autoregressive models used to analyze the population dynamics of each species. 11 first-order autoregressive models (1 year lag) were