Tracking environmental change in seagrass meadows: understanding indicator behaviour across space and time

[eng] Nearshore marine ecosystems like seagrass meadows face a wide range of anthropogenic influences, impacting the system at different spatial and temporal scales. Managing these systems in the face of these pressures requires detailed knowledge of how seagrass habitats respond to these various threats. A plethora of useful indicators have been developed to help managers and policy makers track seagrass meadow health and status, detect environmental impacts or measure the effectiveness of management interventions. However, choosing between these indicators can often be a daunting task since they vary considerably in their overall behaviour in relation to ecosystem and environmental changes. This thesis assesses the most commonly employed seagrass indicators to determine if they are adequate and appropriate to the specific needs of coastal ecosystem management. This assessment is based on evaluating three fundamental characteristics of each indicator – the robustness of its response, the specificity or generality of its response, and the time of response. We use a variety of complementary approaches to explore indicator behaviour. In Chapter 3, we use field-based studies to assess how seagrass indicators respond to the construction of a breakwater in the vicinity of a Posidonia oceanica seagrass meadow. Chapters 4 and 5 examine long-term trends in seagrass indicators to improving water quality conditions after significant regional management interventions. In addition, in Chapter 6, we comprehensively review seagrass indicator responses to multiple stressors. Chapters 3, 4 and 5 focus largely on the Catalan Coast in the Mediterranean with Posidonia oceanica as a target species. Chapter 6 in contrast is a broad review of a wide range of indicators used across several seagrass species worldwide. A central learning across these studies was that the level of biological organisation of the indicator (i.e. Physiological, biochemical, growth, morphological, structural or demographic) is critical in determining the specificity or generality of response: the lower the level (e.g. biochemical), the most specific the response, while the higher the level (e.g. population, community), the wider the response. Thus, biochemical indicators are ideal to determine the identity or even the origin of a pressure while structural indicators, in contrast, are useful as generic indicators of declining conditions. Response times are also heavily determined by the level of organisation, particularly in the detection of improving environmental quality along the Catalan coast. Biochemical indicators responded unequivocally to water quality improvements observed both in the experimental field study (Chapter 3) as well as in the analysis of the long-term data series (Chapters 4 and 5). The meta-analysis confirmed that these trends in specificity and response time were not unique to Posidonia oceanica or the Catalan coast and highlighted the critical role of plant size in determining indicator time responses. Large species take considerably longer to register a response to environmental degradation as well as improvement – a critical factor that needs to be accounted for in designing monitoring programmes and interpreting ecosystem trends. Taken together, these results suggest that differences in the behaviour of seagrass indicators require that they should be carefully selected to match the objectives of management. Based on the results reported in this thesis, where different sets of indicators have been proven successful for given management objectives, we finally develop a simple decision tree to help managers chose the most reliable sets of indicators matching their objectives. Understanding the diversity of responses that seagrass indicators display can make them a powerful set of tools in the ecosystem manager’s toolkit. Carefully employed, they can serve as bespoke solutions to a wide range of management objectives as we seek to monitor and protect these vital ecosystems and coastal water quality in the face of increasing coastal pressures.[cat] Entendre com responen les fanerògames marines a les pressions, és clau per a poder gestionar tant els herbeis com les aigües costaneres. Actualment, disposem d’un gran nombre d’indicadors basats en fanerògames marines. Però, la manca d’informació sobre com responen als canvis ambientals, fa que no sigui fàcil escollir quins indicadors són els més adients per a cada tipus i objectiu de gestió. Aquesta tesi avalua les tres característiques bàsiques de la resposta dels indicadors més utilitzats als canvis ambientals: la robustesa de la resposta, la especificitat dels indicadors a diferents pressions i el temps de resposta. Per analitzar aquestes tres característiques, fem servir diferents aproximacions complementàries. Al capítol 3, analitzem la resposta de diferents indicadors a les obres d’ampliació del port de Blanes, situat just al costat d’un herbei de Posidonia oceanica. Als capítols 4 i 5, estudiem com responen els indicadors a la millora de la qualitat de l’aigua a la costa catalana. Finalment, al capítol 6, presentem una metaanàlisi que estudia com responen els indicadors a diferents factors d’estrès. De totes tres aproximacions, hem pogut comprovar que el nivell d’organització dels indicadors (i.e. bioquímic, estructural) és clau a l’hora de determinar el grau d’especificitat de la resposta dels indicadors a les pressions: generalment, a més baix nivell d’organització (e.g. bioquímic), més específica és la resposta i com més alt (e.g. demogràfic), més ampli és el rang de pressions que un indicador pot detectar. El temps de resposta dels indicadors varia també en funció del nivell d’organització dels indicadors, especialment, quan es tracta de la detecció de millores ambientals. A més a més, la metaanàlisi destaca la importància de la mida de les plantes per determinar el temps de resposta. Les espècies grans triguen més a detectar la degradació de les condicions ambientals i, molt més, a detectar la millora, especialment, si s’utilitzen indicadors estructurals o demogràfics. Basant-nos en els resultats d’aquesta tesi, hem elaborat un esquema per ajudar els gestors a escollir el conjunt d’indicadors que més s’ajusti a cada objectiu de gestió. Utilitzats correctament, aquests indicadors són molt útils per fer el seguiment, tant de l’estat de salut dels herbeis, com de la qualitat del medi

The effect of a centenary storm on the long-lived seagrass Posidonia oceanica

We used the disturbance resulting from a once in a 100‐yr storm on the northwest Mediterranean coast to examine the extent of the disturbance, the tolerance thresholds to burial, and the medium‐term response of the long‐lived Posidonia oceanica seagrass. Sediment burial at 12 surveyed areas was particularly strong in shallow meadows, with 23% of their surfaces buried, on average, under more than 10 cm of sediment. In contrast, less than 5% of the meadow was affected at deeper locations. At three sites, we tracked short‐term mortality along a gradient of sediment burial. Survival response to burial was clearly nonlinear, with a significant threshold at 4-5 cm, beyond which shoot mortality was 100%. To track medium‐term potential recovery, we established permanent plots subject to three sediment burial levels (0-5, 5-10, and > 10 cm burial) in four meadows. Where the initial shoot mortality was 100%, we recorded no shoot recovery over the 4‐yr period. In the remaining plots, where some shoots remained alive, we detected either further mortality or shoot recovery of 7% per year on average. Extreme storm events can result in sudden catastrophic losses of seagrass cover in shallow P. oceanica meadows. In the long term and due to the long return time of such storms, the species may still be able to recover despite its low recovery potential. However, added anthropogenic stressors, including climate change, may seriously test the ability of long‐lived shallow seagrass ecosystems to resist high‐intensity natural disturbances and may be critical for its persistence

Detecting the impacts of harbour construction on a seagrass habitat and its subsequent recovery

Managing coastal development requires a set of tools to adequately detect ecosystem and water column degradation, but it also demands tools to detect any post-disturbance improvement. Structural seagrass indicators (such as shoot density or cover) are often used to detect or assess disturbances, but while they may be very sensitive to the impact itself, it is unclear if those indicators on their own can effectively reflect recovery at time scales relevant to managers. We used the construction of a harbour affecting a nearby Posidonia oceanica seagrass community to test the ability of a set of indicators (structural and others) to detect alterations and to evaluate their sensitivity to recovery of environmental quality after harbour construction was complete and the disturbance ceased. We used a Beyond Before After Control Impact (BBACI) design to evaluate effects on one impacted and three control meadows where we used structural, morphological, community and physiological indicators (26 in total) to asses disturbance impacts. Additionally, we measured some of the potential environmental factors that could be altered during and after the construction of the harbour and are critical to the survival of the seagrass meadow (light, sediment organic matter, sediment accrual). Harbour construction caused a clear increase in sediment organic matter and in sediment deposition rates, especially fine sand. Light availability was also reduced due to suspended sediments. Sediment and light conditions returned to normal levels 5 and 15 months after the construction began. As expected, seagrass structural indicators responded unequivocally to these environmental changes, with clear reductions in shoot density. Additionally, reduced light conditions quickly resulted in a decline in carbohydrate content in affected meadows. Unexpectedly, we also recorded a significant increase in metal content in plant tissues. No response was detected in the physiological indicators related to eutrophication (e.g. N and P content in tissues) and in morphological (shoot biomass) and community (epiphyte biomass) indicators. More than three years after the completion of the harbour, structural indicators did not show any sign of recovery. In contrast, physiological indicators, mainly heavy metal and carbohydrates content, were much better in detecting the improvement of the environmental conditions over the fairly short period of this study. These results indicate that while structural indicators are critical to evaluate the immediate effect of disturbances and the recovery on impacted systems, specific physiological indicators may be much better suited to determining the timing of environmental quality recovery. The design of impact and monitoring protocols in the wake of coastal developmental projects need to consider the differential effectiveness and time-response of measured indicators carefully

Metodologies per ensenyar ciències. Principis, tipus i aplicació

[cat] Amb l’objectiu de treballar un major nombre de competències educatives i de fer les classes més interessants, durant les darreres dècades s’han desenvolupat un gran nombre de metodologies docents que busquen alternatives a les metodologies de transmissió clàssiques. Avui en dia trobem informació sobre metodologies docents innovadores, però sovint la informació es troba força dispersa i es fa difícil trobar un catàleg on els docents puguin cercar i escollir aquelles metodologies més adients per a realitzar les classes. Els objectius d’aquest treball són: recopilar i classificar les noves metodologies docents segons els seus principis i les competències que permeten treballar, buscar evidències científiques de la seva efectivitat i esbrinar en quina mesura i com les utilitzen els professors de ciències a l’actualitat. A més a més, per tal de poder comprovar el funcionament d’algunes de les metodologies docents, hem dissenyat un conjunt d’activitats, combinant diferents metodologies, per a treballar la unitat didàctica de la hidrosfera

Dataset: Experimental carbon emissions from degraded Mediterranean seagrass (Posidonia oceanica) meadows under current and future summer temperatures.

Experimental carbon emissions from degraded Mediterranean seagrass (Posidonia oceanica) meadows. Guillem Roca, Javier Palacios, Sergio Ruíz-Halpern, Núria Marbà Contact details: Guillem Roca, [email protected] Issue date: Identifier: Citation: Roca, Guillem; Palacios, Javier; Ruíz-Halpern, Marbà, Núria; Experimental carbon emissions from degraded Mediterranean seagrass (Posidonia oceanica) meadows. [Dataset] Abstract: The dataset provides data on sediment C02 efflux rates (μmol CO2 m-2 s-1), carbon emissions during the experiment (gm-2), % Organic Carbon, Organic Matter content (g m-2) of the Posidonia oceanica seagrass sediments collected in Pollença bay (North of Mallorca Island). Sediments were cultivated in 5 different seawater temperature treatments and two different agitation conditions. Keywords: C02 efflux rates, C02 emissions, Sediment, Seagrass, Posidonia Oceanica, experiment, temperature treatment, Sediment suspension Blue carbon, Organic Carbon. Description: The dataset contains data on sediment C02 efflux rates, carbon emissions during the experiment (gm-2), % Organic Carbon, Organic Matter content of the Posidonia oceanica seagrass sediments collected in Pollença bay (North of Mallorca Island). Sediments were cultivated in 5 different seawater temperature treatments and two different agitation conditions. Sediments used in the experiment were extracted in October 2017 from the P. Oceanica meadow of Pollença in Mallorca Island at six-meter depth Figure (1). Sediments were sampled in October 2017 using sediment cores (9 cm ID and 30cm long) and directly transported to the laboratory. Only the top 10 cm of the sediment cores were used since this fraction is the most susceptible to erosion. Living seagrass tissues (roots, rhizomes, and leaves) were removed and sediment was mixed and homogenized. 40ml of sediments were poured into glass containers of 750ml with 500ml of seawater. Finally, each recipient contained a sediment layer of approximately 1.1cm in each container. Containers were placed at five different temperature baths (26,27.5, 29, 30.5, 32 ºC) simulating summer temperatures in the bay (Garcias-Bonet et al., 2019) at different agitation regimes (agitation/repose) to simulate exposed and sheltered conditions.10 containers were sampled right after the experiment started to provide initial sediment conditions. Five containers per temperature and agitation treatment were removed 7, 21, 43, 67, and 98 days from the experiment start, to analyse sediment organic matter and CaCO3 content. CO2 incubations were run 5, 14, 56, and 91 days from the experiment start. Sampling times were distributed considering that organic matter remineralisation was likely to follow an exponential trend, including a rapid phase of loss of the more labile material followed by a slower loss of more recalcitrant substrates (Arndt et al., 2013). The experiment was run in the dark to avoid photosynthesis in an isothermal chamber at 21ºC. Organic Carbon analysis In each sampling time, organic matter content in sediments (OM %DW) was estimated as the percentage weight loss of dry sediment sample after combustion at 550ºC for 4 hours. Organic carbon (Corg) was calculated from OM content using the relation described in (Mazarrasa et al., 2017b) y = 0.29x – 0.64; (R2=0.98, p< 0.0001, n=60) OM and POC stocks along the experiment (mg OM ml-1 and mg POC ml-1) were estimated by multiplying the OM and POC (%DW) by the sediment dry weight (mg) remaining in each experimental unit and standardized to the initial volume of sediment (40 ml) introduced in every glass container. Inorganic carbon was estimated as the percentage weight loss of already combusted sediment (550ºC) after combustion at 1000ºC. Sediment CO2 production Container headspace CO2 gas concentration was measured during 20 minutes continuum incubations (4 replicates) in each temperature and agitation treatment in all sampling times. CO2 air concentration measures were carried out using an Infra Red Gas Analyser EGM4 from PPSystems. Concentration of dissolved CO2 in seawater (in μmol CO2 L−1) was calculated from the concentration of CO2 (in ppm) measured in headspace air samples after equilibration as described in (Garcias-Bonet and Duarte, 2017; Wilson et al., 2012). Briefly, we calculate the dissolved CO2 remaining in seawater after equilibration with the air phase ([CO2]SW−eq) by, [CO2]SW−eq = 10−6 β [C CO2]Air P where β is the Bunsen solubility coefficient of CO2, calculated according to Wiesenburg and Guinasso (1979), as a function of seawater temperature and salinity; [CO2]Air is the CO2 concentration measured in containers headspace air (in ppm) and P is the atmospheric pressure (in atm) of dry air that was corrected by the effect of multiple sampling applying Boyle’s Law. Then, the initial CO2 concentration in seawater before the equilibrium ([CO2]SW−before eq) was calculated (in ml CO2 /ml H2O) by, [CO2]SW−before eq = ([CH4]SW−eq VSw + 10−6 ([CO2]Air −[CO2]Air background) VAir)/VSW Where VSw is the volume of seawater in the core or in the seawater closed circuit, [CO2]Air background is the atmospheric CO2 background level and VAir is the volume of the headspace or the closed air circuit. Finally, the initial CO2 concentration was transformed to µmol CH4 L−1 by applying the ideal gas law. CO2 efflux values were calculated from CO2 variation per time unit. Then, we converted the rates to aerial (taking in account container surface) base, and thickness (in μmol m-2 s-1)

The effect of a centenary storm on the long-lived seagrass Posidonia oceanica

We used the disturbance resulting from a once in a 100‐yr storm on the northwest Mediterranean coast to examine the extent of the disturbance, the tolerance thresholds to burial, and the medium‐term response of the long‐lived Posidonia oceanica seagrass. Sediment burial at 12 surveyed areas was particularly strong in shallow meadows, with 23% of their surfaces buried, on average, under more than 10 cm of sediment. In contrast, less than 5% of the meadow was affected at deeper locations. At three sites, we tracked short‐term mortality along a gradient of sediment burial. Survival response to burial was clearly nonlinear, with a significant threshold at 4-5 cm, beyond which shoot mortality was 100%. To track medium‐term potential recovery, we established permanent plots subject to three sediment burial levels (0-5, 5-10, and > 10 cm burial) in four meadows. Where the initial shoot mortality was 100%, we recorded no shoot recovery over the 4‐yr period. In the remaining plots, where some shoots remained alive, we detected either further mortality or shoot recovery of 7% per year on average. Extreme storm events can result in sudden catastrophic losses of seagrass cover in shallow P. oceanica meadows. In the long term and due to the long return time of such storms, the species may still be able to recover despite its low recovery potential. However, added anthropogenic stressors, including climate change, may seriously test the ability of long‐lived shallow seagrass ecosystems to resist high‐intensity natural disturbances and may be critical for its persistence

Habitat and Scale Shape the Demographic Fate of the Keystone Sea Urchin Paracentrotus lividus in Mediterranean Macrophyte Communities

Demographic processes exert different degrees of control as individuals grow, and in species that span several habitats and spatial scales, this can influence our ability to predict their population at a particular life-history stage given the previous life stage. In particular, when keystone species are involved, this relative coupling between demographic stages can have significant implications for the functioning of ecosystems. We examined benthic and pelagic abundances of the sea urchin Paracentrotus lividus in order to: 1) understand the main life-history bottlenecks by observing the degree of coupling between demographic stages; and 2) explore the processes driving these linkages. P. lividus is the dominant invertebrate herbivore in the Mediterranean Sea, and has been repeatedly observed to overgraze shallow beds of the seagrass Posidonia oceanica and rocky macroalgal communities. We used a hierarchical sampling design at different spatial scales (100 s, 10 s and <1 km) and habitats (seagrass and rocky macroalgae) to describe the spatial patterns in the abundance of different demographic stages (larvae, settlers, recruits and adults). Our results indicate that large-scale factors (potentially currents, nutrients, temperature, etc.) determine larval availability and settlement in the pelagic stages of urchin life history. In rocky macroalgal habitats, benthic processes (like predation) acting at large or medium scales drive adult abundances. In contrast, adult numbers in seagrass meadows are most likely influenced by factors like local migration (from adjoining rocky habitats) functioning at much smaller scales. The complexity of spatial and habitat-dependent processes shaping urchin populations demands a multiplicity of approaches when addressing habitat conservation actions, yet such actions are currently mostly aimed at managing predation processes and fish numbers. We argue that a more holistic ecosystem management also needs to incorporate the landscape and habitat-quality level processes (eutrophication, fragmentation, etc.) that together regulate the populations of this keystone herbivore

Response of seagrass indicators to shifts in environmental stressors: A global review and management synthesis

Although seagrass-based indicators are widely used to assess coastal ecosystem status, there is little universality in their application. Matching the plethora of available indicators to specific management objectives requires a detailed knowledge of their species-specific sensitivities and their response time to environmental stressors. We conducted an extensive survey of experimental studies to determine the sensitivity and response time of seagrass indicators to ecosystem degradation and recovery. We identified seagrass size and indicator type (i.e. level of biological organization of the measure) as the main factors affecting indicator sensitivity and response time to degradation and recovery. While structural and demographic parameters (e.g. shoot density, biomass) show a high and unspecific sensitivity, biochemical/physiological indicators present more stressor-specific responses and are the most sensitive detecting early phases of environmental improvement. Based on these results we present a simple decision tree to assist ecosystem managers to match adequate and reliable indicators to specific management goals