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Redalyc.Mortality Rate Estimation for Eelgrass Zostera Marina

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Redalyc.Mortality Rate Estimation for Eelgrass Zostera Marina Revista de Biología Tropical ISSN: 0034-7744 [email protected] Universidad de Costa Rica Costa Rica Flores Uzeta, Olga; Solana Arellano, Elena; Echavarría Heras, Héctor Mortality rate estimation for eelgrass Zostera marina (Potamogetonaceae) using projections from Leslie matrices Revista de Biología Tropical, vol. 56, núm. 3, septiembre, 2008, pp. 1015-1022 Universidad de Costa Rica San Pedro de Montes de Oca, Costa Rica Available in: http://www.redalyc.org/articulo.oa?id=44918834004 How to cite Complete issue Scientific Information System More information about this article Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Journal's homepage in redalyc.org Non-profit academic project, developed under the open access initiative Mortality rate estimation for eelgrass Zostera marina (Potamogetonaceae) using projections from Leslie matrices Olga Flores Uzeta, Elena Solana Arellano & Héctor Echavarría Heras Departamento de Ecología Marina, Centro de Investigación Científica y Educación Superior de Ensenada, Ensenada, Baja California México, P.O. Box 430222, San Diego, CA. 92143-0222, USA.Fax: (646) 175 05 00; oflores@cicese. mx; [email protected]; [email protected] Received 28-VIII-2006. Corrected 30-VI-2008. Accepted 31-VII-2008. Abstract: The main goal of this study is to provide estimations of mean mortality rate of vegetative shoots of the seagrass Zostera marina in a meadow near Ensenada Baja California, using a technique that minimizes destruc- tive sampling. Using cohorts and Leslie matrices, three life tables were constructed, each representing a season within the period of monthly sampling (April 1999 to April 2000). Ages for the cohorts were established in terms of Plastochrone Interval (PI). The matrices were projected through time to estimate the mean total number of individuals at time t, n(t) as well as mortality. We found no statistical differences between observed and predicted mean values for these variables (t=-0.11, p=0.92 for n(t) and t=0.69, p=0.5 for mean rate of mortality). We found high correlation coefficient values between observed and projected values for monthly number of individuals (r=0.70, p=0.007) and monthly mortality rates (r=0.81, p=0.001). If at a certain time t a sudden environmental change occurs, and as long as the perturbation does not provoke the killing of all the individuals of a given age i for 0 ≤ i ≤ x – 1, there will be a prevailing number of individuals of age or stage x at a time t+1. This non- destructive technique reduces the number of field visits and samples needed for the demographic analysis of Z. marina, and therefore decreases the disturbance caused by researches to the ecosystem. Rev. Biol. Trop. 56 (3): 1015-1022. Epub 2008 September 30. Key words: matrix models, demography, Zostera marina, mortality rates. Seagrass meadows are very important in Even though seagrasses are widely dis- the ecology of coastal waters (Mann 1982), tributed in temperate waters throughout the but are very susceptible to both anthropogenic northern hemisphere (den Hartog 1970), shoots and climatic perturbations. This means that demography has not been studied is for ter- mortality and recruitment are going to be restrial plants for which the general patterns responsible for changes in density and shoot of shoot density regulation via shoot natality coverage (Olesen and Sand-Jensen 1994) and or shoot mortality are known (Lovett 1981, therefore the study of these processes is crucial Schmid and Harper 1985). Moreover demo- to understand the demography of seagrasses. graphic techniques to explore population have Since these plants are modular, with con- been applied to seagrasses only to evaluate tinuous branching and expansion of rhizomes the potential of a population in terms of den- (Gallegos 1995), it is reasonable to assume that sity increments or decrements at the level of recruitment is constant over time. Moreover the whole meadow dynamics (Patriquin 1973, Solana-Arellano (2004) showed through an Durako and Moffler 1987, Cox and Tomlinson analysis of variance, that recruitment rates for 1988, Duarte and Sand-Jensen 1990, Duarte Zostera marina is constant (F=1.4, p=0.48) at et al. 1994). In addition, the use of these tech- our study site. niques has been restricted to only three sea- Rev. Biol. Trop. (Int. J. Trop. Biol. ISSN-0034-7744) Vol. 56 (3): 1015-1022, September 2008 1015 grass species; Posidonia oceanica (Pergent and through the projection of the Leslie matrix life Pergent-Martini 1990), Thalassia testudinum table with entries given in terms of survival (Patriquin 1973, Gallegos et al. 1993, Durako and fecundity rates. A reasonable correspon- 1994) Cymodocea nodosa (Duarte and Sand- dence of observed and predicted rates would Jensen 1990, Pérez et al. 1994, Vidondo et al. allow us calculate some characteristic of the 1997). population without the use of destructive sam- Specifically for C. nodosa, Pérez et al. plings. Besides contributing to the knowledge (1994) gave an estimate of mean mortality of demographic strategies, our findings would rates (in logarithmic units) from the exponen- justify drastically reduce the number of field tial reduction of shoots density grouped in samplings needed per year. consecutive annual cohorts structured by age. This relatively easy method, besides being MATERIALS AND METHODS destructive, gives no details of the mathemati- cal assumptions necessary to obtain mortality Field, laboratory and statistical methods: rates for C. nodosa. On the other hand, the data were generated biweekly from February powerful reconstructive methods proposed by 1999 to April 2000 in a Z. marina meadow. At Pergent and Pergent-Martini (1990) and Duarte Punta Banda Estuary on the Pacific coast of et al. (1994), which are non-destructive, are Baja California, México (31°40’- 31°48’ N, and only suitable for long-lived seagrasses. For Z. 116°37’ -116°40’ W). For a complete descrip- marina, the study of Olesen and Sand-Jensen tion of the sample site see Solana-Arellano (1994) is the first work based on cohorts struc- (2004). On each sampling date, all shoots on 20 tured by age. They describe the relationship randomly selected rhizomes were marked using between growth and age of a shoot in terms the technique of Kentula and McIntire (1986). of plastochrones, seasonal production, above After fifteen days, we harvested the previously ground biomass, and shoot density regulation marked shoots, and marked a new set. Samples through recruitment and mortality. Solana- were taken to the laboratory where the fol- Arellano (2004) used cohorts and the Pérez et lowing measurements where made: number al. (1994) method to describe the demography of leaves per shoot, number shoots per meter of a Mexican Z. marina meadow. of rhizome, number of new shoots and leaves. To study shoot demography, it is neces- Age of each shoot and biweekly Plastochrone sary to construct life history tables, defined by Interval (PI) were calculated. The projections Ebert (1999), as the schedule of probabilities of the Leslie matrices were developed using the of things that may happen to individuals with program Maple V (1998) for symbolic manipu- particular attributes. The most general choice lation. The STATISTICA (1999) package was for attribute is age. We then projected these life used for the data analysis. tables to visualize trends in population demog- raphy, given parameters of birth and death. The Data management: the mean annual projection of a life table matrix for a popula- Plastochrone Interval (PI) was calculated using tion was defined by Keyfitz (1972) as an assay the criteria Jacobs (1979). The PI is defined that describes what is going to happen with the as the time interval between the initiation of population density given certain parameters. two successive leaves on one shoot. For Z. According with Chapman (1986), life tables marina, Jacobs (1979) introduced a formula can be applied to plants and even marine algae for the calculation of the PI which consists of if individuals can be differentiated. multiplying the total number of marked shoots The purpose of this work is to compare by times days of exposure and dividing by the a series of observed mortality rates with pro- number of new leaves on marked shoots. The jected rates based on only one or a few field age of each shoot, in Plastochrone Intervals, samples. These rate estimations were obtained was calculated adding the number of standing 1016 Rev. Biol. Trop. (Int. J. Trop. Biol. ISSN-0034-7744) Vol. 56 (3): 1015-1022, September 2008 n l = x x nx n0 lx = n0 leaves plus leaf scars from shed leaves (Duarte l + l p x x + l and Sand-Jensen 1990). Monthly cohorts and x = l + l (2) p x x + l the life tables were constructed using 1999 x = lx - l + lx l l data as a preliminary analysis. Based on the nx - l + x l = nx result of this analysis, (see result section), we x nlx + l (3) lx = 0 l p0 = constructed three life tables: Life table I, with nl0 + ll p0 = 2 data gathered on April 1999 and projecting the l +2 l and p = x x + l interval of May-August 1999, Life table II, x lx + lx + l p * = lm +l p m with data based on August 1999 and projecting mx x -x l - l+ x x x x = m p m (4) * lx -x l - l++lx x x the interval September-December 1999 and m x = 2 Life table III, with data of December 1999 that The recruitmentl + l 2 rate was calculated as: p 0 l 0 = l + l projected the time interval of January-April p 0 l 0 = number2 of new born at time t 2000. With each projection, mean monthly b = number2 of new born at time t (5) mortality rates were calculated and compared b = number of survivors from t - l to t * numbermx - l + ofp xsurvivorsmx from t - l to t statistically with observed values.
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