*ManuscriptView metadata, citation and similar papers at core.ac.uk brought to you by CORE Click here to view linked References provided by Digital.CSIC 1 2 3 4 5 A model for temperature control of jellyfish (Cotylorhiza tuberculata) 6 7 8 outbreaks: a causal analysis in a Mediterranean coastal lagoon. 9 10 11 12 13 14 *1 * * 15 Javier Ruiz , Laura Prieto and Diana Astorga . 16 17 18 *Department of Coastal Ecology and Management, Instituto de Ciencias Marinas de 19 20 21 Andalucía, Consejo Superior de Investigaciones Científicas, Avda Republica Saharaui 22 23 2, 11519 Puerto Real, Cádiz, Spain 24 25 26 27 28 29 1Corresponding Author: 30 31 Javier Ruiz 32 Departamento de Ecología y Gestión Costera 33 Instituto de Ciencias Marinas de Andalucia (ICMAN-CSIC) 34 Avda Republica Saharaui 2 35 36 11519 Puerto Real (Cádiz) 37 SPAIN 38 Tel: 34-956-832612 39 Fax: 34-956-834701 40 [email protected] 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 1 65 ABSTRACT 1 2 3 4 5 Large outbreaks of jellyfish populations sporadically appear at the Mediterranean coasts 6 7 without any self-evident cause creating public distress because of their impact on local 8 9 10 ecosystems and economies. The exacerbated sensitivity of coastal societies has not been 11 12 paralleled with comparable scientific understanding of the causal mechanisms 13 14 controlling jellyfish population dynamics. Life-cycle and ecosystem complexities 15 16 17 obscure the processes underlying medusa outbursts. Here we present evidence that helps 18 19 explain population outbursts in a common Mediterranean species (Cotylorhiza 20 21 22 tuberculata). Using a population-dynamics model and thermal forcing of its life cycle 23 24 observed abundances of C. tuberculata could be reliably simulated within a coastal 25 26 27 lagoon. Medusa populations fluctuate under the simple rule of “the warmer the better”, 28 29 with collapses after polyp mortality in severe winters and peaks in years with mild 30 31 winters and long summers. Cause and effect are here resolved to seize the mechanics of 32 33 34 climate forcing on jellyfish dynamics, an understanding that can help to explain past 35 36 and future fluctuations of abundance in a thermally-changing ocean. 37 38 39 40 41 42 Key words: jellyfish, medusa, Mediterranean, Cotylorhiza tuberculata, Bayesian 43 44 45 framework, Mar Menor, coastal lagoon. 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 2 65 1. INTRODUCTION 1 2 3 4 2 5 The Mar Menor is a large (135 km ) and shallow (~4 m average depth) lagoon almost 6 7 isolated from the western Mediterranean by a 22 Km long sand bar (Fig. 1). A 8 9 10 progressive increase in both human pressure on the shoreline and agriculture 11 12 modification of the water catchments area modified the original benthic communities 13 14 during the 80s (Pérez-Ruzafa et al. 2002). Coherently with a habitat-degradation 15 16 17 triggering of jellyfish populations (Pagès 2001; Richardson et al. 2009), Cotylorhiza 18 19 tuberculata, first began to manifest within the lagoon as massive outbreaks in early 90s. 20 21 22 C. tuberculata is a scyphomedusa frequently present on the Mediterranean coast with 23 24 pelagic and polyp phases present during warm and cold months respectively (Avian 25 26 27 1986; Kikinger 1986). The dynamics of C. tuberculata abundance in Mar Menor has 28 29 been observed since its first appearance without scientific understanding of the origin of 30 31 fluctuation in the population. Because of the summer occurrence of the medusa phase, 32 33 34 public alarm during blooming years triggered a local management program to reduce 35 36 their impact on bathing activities. This program started in year 2000 and involved 37 38 39 extracting medusa with fishing vessels. It generated a data set of landing and effort 40 41 records similar to those used for modelling exploited fish populations (Punt and Hilborn 42 43 44 1997). Economic information exists for other jellyfish fisheries (e.g. Omori and Nakano 45 46 2001) but reports of medusa catch and effort data able to evaluate dynamics in a medusa 47 48 49 population as commonly done for fish stock assessment are very scarce (Brodeur et al. 50 51 2008). 52 53 54 55 56 Although the available information on C. tuberculata life cycle is not as extensive as 57 58 other scyphozoa (e.g. Aurelia aurita; Lucas, 2001), this shows strong components of 59 60 61 62 63 64 3 65 environmental forcing. All life cycle phases are insensitive to the range of salinities 1 2 found within the lagoon and polyp survival is not significantly affected by a wide range 3 4 5 of light, macronutrients and food conditions (Prieto et al. 2010). Conversely, polyp 6 7 mortality is strongly linked to low temperatures (Prieto et al. 2010). Like other 8 9 10 scyphozoa species, e.g. Aurelia aurita (Lucas 2001) or Chrysaora quinquecirrha 11 12 (Purcell et al. 1999), cold waters prevent strobilation (Kikinger 1992). However, in 13 14 contrast to other scyphozoa, C. tuberculata polyps only produce one ephyra (Kikinger 15 16 17 1986) and strobilation is triggered at a narrow temperature range (Prieto et al. 2010). 18 19 This response of their life cycle to environmental forcing, particularly to temperature, 20 21 22 makes it plausible that the thermal-regime of the lagoon controls population dynamics. 23 24 Although the link between environment and scyphozoa populations has been explored 25 26 27 (Anderson and Piatt 1999; Raskoff 2001; Lynam et al. 2004; Attrill et al. 2007; Purcell 28 29 et al. 2007; Gibbons and Richardson 2008), most studies investigate statistical 30 31 correlations between environmental indices and abundance, rather than identifying the 32 33 34 mechanisms forcing the population dynamics of jellyfish through their impact on the 35 36 life-cycle. 37 38 39 40 41 The isolated nature of the Mar Menor presents an outstanding situation for examining 42 43 44 C. tuberculata dynamics, as migration or advection of the population can be essentially 45 46 neglected. Bayesian models can perform this analysis because they consistently 47 48 49 combine fishery data, environmental records and the knowledge of the exploited-species 50 51 life-cycle to account for the origin of population fluctuations (Ruiz et al. 2009). This is 52 53 possible even when available data and knowledge are highly divergent in their 54 55 56 characteristics; ranging from meteorological records or laboratory experiments to in situ 57 58 observations or landing reports. In this manuscript we implement a Bayesian model to 59 60 61 62 63 64 4 65 evaluate the hypothesis that the population dynamics of the jellyfish C. tuberculata in 1 2 the Mar Menor is controlled by the sensitivity of its life cycle to the thermal regime 3 4 5 within the lagoon. Our modelling analysis documents the significant role that 6 7 temperature has in unravelling the underlying causal mechanisms leading to years of 8 9 10 high or low C. tuberculata abundance in Mar Menor. This provides strong insights into 11 12 the factors driving past changes in scyphozoan populations and a foresight into the 13 14 future of warming oceans. 15 16 17 18 19 2. LIFE-CYCLE CONTROL OF POPULLATION DYNAMICS 20 21 22 23 24 Methods to simulate population dynamics by state-space models under the Bayesian 25 26 27 framework are described elsewhere (Meyer and Millar 1999; Millar and Meyer 2000; 28 29 Rivot et al. 2004; Ibaibarriaga et al. 2008; Ruiz et al. 2009). Succinctly, a process model 30 31 is defined for the population dynamics and its control by the environmental forcing of 32 33 34 the life-cycle. An observational model is additionally defined to connect unobserved 35 36 (latent) variables (e.g. stock size) with available records (e.g. landing and effort). 37 38 39 Numerical techniques implement Bayes’ theorem to update the prior probability of 40 41 model parameters with the likelihood of the observations, i.e. to obtain the posteriors. A 42 43 44 directed acyclic graph is frequently produced as the conceptual scheme for the joint 45 46 process and observational models. This section describes the process and observational 47 48 49 models for C. tuberculata as its life-cycle evolve between pelagic and benthic phases as 50 51 well as the data included in the approach and the numerical procedures implemented. 52 53 54 55 56 57 58 59 60 61 62 63 64 5 65 2.1 PROCESS MODEL FOR THE BENTHIC PHASE 1 2 3 4 5 When planulae become polyps they fix and live in the benthos from fall to spring 6 7 (Kikinger 1992). Polyps have the ability to increase population through asexual 8 9 10 reproduction (budding) but their numbers are mainly driven by their mortality in cold 11 12 waters; when temperature drops below ~16ºC mortality increases (Prieto et al. 2010). 13 14 Survival in cold waters can be modelled through a decay equation with a coefficient (m, 15 16 -1 17 d ) for the mortality rate of the polyp population (P, number of individuals) that is 18 19 dependent on water temperature (Tw, ºC): 20 21 22 23 24 dP dt m T P [1] 25 w 26 27 28 29 30 Polyp mortality by cold temperature is negligible for waters above 16ºC (Prieto et al., 31 32 2010). On the contrary, the values for mTw derived from the mortality curves in Prieto 33 34 35 et al.