Benthic trophic interactions in an Antarctic shallow water ecosystem affected by recent glacier retreat

The western Antarctic Peninsula is experiencing strong environmental changes as a consequence of ongoing regional warming. Glaciers in the area are retreating rapidly and increased sediment-laden meltwater runoff threatens the benthic biodiversity at shallow depths. We identified three sites with a distinct glacier-retreat related history and different levels of glacial influence in the inner part of Potter Cove (King George Island, South Shetland Islands), a fjord-like embayment impacted since the 1950s by a tidewater glacier retreat. We compared the soft sediment meio- and macrofauna isotopic niche widths (delta C-13 and delta N-15 stable isotope analysis) at the three sites to investigate possible glacier retreat-related influences on benthic trophic interactions. The isotopic niches were locally shaped by the different degrees of glacier retreat-related disturbance within the Cove. Wider isotopic niche widths were found at the site that has become ice-free most recently, and narrower niches at the older ice-free sites. At an intermediate state of glacier retreat-related disturbance (e.g. via ice-growler scouring) species with different strategies could settle. The site at the earliest stage of post-retreat development was characterized by an assemblage with lower trophic redundancy. Generally, the isotopic niche widths increased with increasing size spectra of organisms within the community, excepting the youngest assemblage, where the pioneer colonizer meiofauna size class displayed the highest isotopic niche width. Meiofauna at all sites generally occupied positions in the isotopic space that suggested a detrital-pool food source and/or the presence of predatory taxa. In general ice scour and glacial impact appeared to play a two-fold role within the Cove: i) either stimulating trophic diversity by allowing continuous re-colonization of meiofaunal species or, ii) over time driving the benthic assemblages into a more compact trophic structure with increased connectedness and resource recycling

Network analysis suggests changes in food web stability produced by bottom trawl fishery in Patagonia

Demersal fisheries are one of the top anthropic stressors in marine environments. In the long term, some species are more vulnerable to fishery impacts than others, which can lead to permanent changes on the food web. The trophic relationships between predator and prey constitute the food web and it represents a network of the energy channels in an ecosystem. In turn, the network structure influences ecosystem diversity and stability. The first aim of this study was to describe for the first time the food web of the San Jorge Gulf (Patagonia Argentina) with high resolution, i.e. to the species level when information is available. The San Jorge Gulf was subject to intense fisheries thus our second aim is to analyse the food web structure with and without fishery to evaluate if the bottom-trawl industrial fishery altered the network structure and stability. We used several network metrics like: mean trophic level, omnivory, modularity and quasi-sign stability. We included these metrics because they are related to stability and can be evaluated using predator diets that can weight the links between predators and prey. The network presented 165 species organized in almost five trophic levels. The inclusion of a fishery node adds 69 new trophic links. All weighted and unweighted metrics showed differences between the two networks, reflecting a decrease in stability when fishery was included in the system. Thus, our results suggested a probable change of state of the system. The observed changes in species abundances since the fishery was established, could represent the state change predicted by network analysis. Our results suggests that changes in the stability of food webs can be used to evaluate the impacts of human activity on ecosystems.Fil: Funes, Manuela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Saravia, Leonardo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento; ArgentinaFil: Cordone, Georgina Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Iribarne, Oscar Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Galvan, David Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentin

Un algoritmo para la identificación de unidades taxonómicas indicadoras y su uso en análisis del estado del ecosistemas

Biological community structure can be used as an ecological state descriptor, and the sensitivity of some taxonomic groups or biological entities to environmental conditions allows for their use as ecological state indicators. This work describes an algorithm developed for the identification of such taxonomic units when comparing environments or ecosystems under different anthropic impacts. Based solely on presence or absence information in a database, the algorithm identifies indicator taxonomic units for each environment, estimates the belonging of any additional samples to a given environment, approximates the ecological niche of any taxonomic unit based on two or more selected environmental factors, and analyzes the frequency of any taxonomic unit in a selected combination of the environmental factors chosen. By using the approximation to the ecological niche of the taxonomic units present, given a new sample, the physicochemical parameters of the environment it was taken can be estimated by the units present in the sample. These analyses can be performed simultaneously for two or more taxonomic units. This work provides a description of how the mathematical method was developed. Based on this methodology, a freely downloadable R package for easy use was developed, (Ecoindicators, DOI: https://github.com/lsaravia/EcoIndicators). One of the advantages of this method, and the R-package mentioned is that it can be used for any ecosystem for which there is a suitable biological dataset associated with environmental factors. In addition, both this mathematical procedure and the package referred to, can be tailored by other researchers to fit their own needs.La estructura de una comunidad biológica puede usarse como un descriptor del estado ecológico, y la sensibilidad de algunos grupos taxonómicos o entidades biológicas a las condiciones ambientales, permite que sean usados como indicadores de dicho estado. Este trabajo describe el desarrollo de un algoritmo para la identificación de tales unidades taxonómicas al comparar ambientes o ecosistemas bajo diferentes impactos antrópicos. Basado únicamente en información de presencia o ausencia en una base de datos, el algoritmo identifica unidades taxonómicas indicadoras de cada ambiente, estima la pertenencia de cualquier muestra adicional a un ambiente dado, aproxima el nicho ecológico de cualquier unidad taxonómica con base en dos o más factores ambientales seleccionados y analiza la frecuencia de cualquier unidad taxonómica en la combinación de los factores ambientales elegidos. Utilizando la aproximación al nicho ecológico de las unidades taxonómicas presentes en la base de datos, dada una nueva muestra, se pueden estimar ciertos parámetros fisicoquímicos del ambiente de donde provino tal muestra a partir de las especies presentes en la misma. Estos análisis se pueden realizar simultáneamente para dos o más unidades taxonómicas. Este trabajo proporciona una descripción de cómo se desarrolló este procedimiento matemático. Con base en la metodología aquí descripta, se desarrolló un paquete R de fácil descarga y uso gratuito (Ecoindicators, DOI: https://github.com/lsaravia/EcoIndicators). Una de las ventajas de este método, y del paquete R mencionado, es que puede usarse para cualquier ecosistema para el que exista un conjunto de datos biológicos adecuados asociados con factores ambientales. Además, tanto este procedimiento matemático como el paquete al que se hace referencia, pueden ser adaptados por otros investigadores para que se ajusten a sus propias necesidades.Fil: de la Vega, Darío Hernán. Universidad Nacional de Luján. Departamento de Ciencias Básicas; ArgentinaFil: Falco, Liliana. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; Argentina. Universidad Nacional de Luján. Departamento de Ciencias Básicas. Laboratorio de Ecología; ArgentinaFil: Saravia, Leonardo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaFil: Sandler, Rosana Veronica. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; ArgentinaFil: Duhour, Andrés Esteban. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; Argentina. Universidad Nacional de Luján. Departamento de Ciencias Básicas. Laboratorio de Ecología; ArgentinaFil: Velazco, Victor Nicolás. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; Argentina. Universidad Nacional de Luján. Departamento de Ciencias Básicas. Laboratorio de Ecología; ArgentinaFil: Coviella, Carlos Eduardo. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; Argentina. Universidad Nacional de Luján. Departamento de Ciencias Básicas. Laboratorio de Ecología; Argentin

The Food Web of Potter Cove (Antarctica): complexity, structure and function

Knowledge of the food web structure and complexity are central to better understand ecosystem functioning. A food-web approach includes both species and energy flows among them, providing a natural framework for characterizing species’ ecological roles and the mechanisms through which biodiversity influences ecosystem dynamics. Here we present for the first time a high-resolution food web for a marine ecosystem at Potter Cove (northern Antarctic Peninsula). Eleven food web properties were analyzed in order to document network complexity, structure and topology. We found a low linkage density (3.4), connectance (0.04) and omnivory percentage (45), as well as a short path length (1.8) and a low clustering coefficient (0.08). Furthermore, relating the structure of the food web to its dynamics, an exponential degree distribution (in- and out-links) was found. This suggests that the Potter Cove food web may be vulnerable if the most connected species became locally extinct. For two of the three more connected functional groups, competition overlap graphs imply high trophic interaction between demersal fish and niche specialization according to feeding strategies in amphipods. On the other hand, the prey overlap graph shows also that multiple energy pathways of carbon flux exist across benthic and pelagic habitats in the Potter Cove ecosystem. Although alternative food sources might add robustness to the web, network properties (low linkage density, connectance and omnivory) suggest fragility and potential trophic cascade effects.Fil: Marina, Tomas Ignacio. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; ArgentinaFil: Salinas, Vanesa Anabella. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cordone, Georgina Florencia. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Campana, Gabriela Laura. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; Argentina. Ministerio de Relaciones Exteriores, Comercio Interno y Culto. Dirección Nacional del Antártico. Instituto Antártico Argentino; ArgentinaFil: Moreira, María Eugenia. Ministerio de Relaciones Exteriores, Comercio Interno y Culto. Dirección Nacional del Antártico. Instituto Antártico Argentino; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Deregibus, Dolores. Ministerio de Relaciones Exteriores, Comercio Interno y Culto. Dirección Nacional del Antártico. Instituto Antártico Argentino; ArgentinaFil: Torre, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; ArgentinaFil: Sahade, Ricardo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; ArgentinaFil: Tatian, Marcos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; ArgentinaFil: Barrera Oro, Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales ; ArgentinaFil: De Troch, Marleen. University College Ghent; BélgicaFil: Doyle, Santiago Raúl. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Quartino, Maria Liliana. Ministerio de Relaciones Exteriores, Comercio Interno y Culto. Dirección Nacional del Antártico. Instituto Antártico Argentino; ArgentinaFil: Saravia, Leonardo Ariel. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaFil: Momo, Fernando Roberto. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina. Universidad Nacional de Luján. Instituto de Ecología y Desarrollo Sustentable. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ecología y Desarrollo Sustentable; Argentin

Multifractal Spatial Patterns and Diversity in an Ecological Succession

We analyzed the relationship between biodiversity and spatial biomass heterogeneity along an ecological succession developed in the laboratory. Periphyton (attached microalgae) biomass spatial patterns at several successional stages were obtained using digital image analysis and at the same time we estimated the species composition and abundance. We show that the spatial pattern was self-similar and as the community developed in an homogeneous environment the pattern is self-organized. To characterize it we estimated the multifractal spectrum of generalized dimensions Dq. Using Dq we analyze the existence of cycles of heterogeneity during succession and the use of the information dimension D1 as an index of successional stage. We did not find cycles but the values of D1 showed an increasing trend as the succession developed and the biomass was higher. D1 was also negatively correlated with Shannon's diversity. Several studies have found this relationship in different ecosystems but here we prove that the community self-organizes and generates its own spatial heterogeneity influencing diversity. If this is confirmed with more experimental and theoretical evidence D1 could be used as an index, easily calculated from remote sensing data, to detect high or low diversity areas

Some spatial questions in ecology. Models, data and aplications

El espacio es un factor que ha sido históricamente dejado de lado pero en los últimos tiempos ha desmostrado ser fundamental para la ecología, tanto teórica como de campo. La utilización de modelos para el estudio de las interacciones espaciales es una herramienta impresindible que puede aportar soluciones tanto en casos en que la experimentacion no es posible como para realizar aportes teóricos. Los modelos espaciales plantean nuevos problemas, tanto de índole práctica como teórica. En la parte práctica, la simulación de este tipo de modelos posibilita la utilización de diferentes técnicas cuyas consecuencias no han sido exploradas. La comparación de los datos obtenidos con estos modelos y datos de campo requiere el uso de técnicas que no han sido completamente estudiadas. Usualmente en modelos de sistemas ecológicos se estudia su comportamiento en el equilibrio y se extraen hipótesis sobre el funcionamiento del sistema. En el caso de los modelos espaciales parece ser muy importante su comportamiento transitorio, es decir lo que pasa antes de llegar al equilibrio. Debido a la enorme cantidad de componentes de los ecosistemas la teoria de sistemas complejos y los fractales pueden ser utilizados para la interpretación de los mismos. En esta tesis se plantea el estudio de estos nuevos desafíos teóricos y prácticos y su aplicación a distintos ecosistemas.Space is a factor that has historically been neglected but has recently become fundamental for ecology, both theoretical and field. The use of models for the study of spatial interactions is an essential tool that can provide solutions in cases where experimentation is not possible and to make theoretical contributions. Spatial models pose new problems, both practical and theoretical. In the practical side, the simulation of such models allows the use of different techniques whose consequences have not been completely explored. The comparison of these models with field data requires the use of techniques that have not been fully studied. Is usual to study the equilibrium behavior of models to draw hypotheses about the functioning of the system. In the case of the spatial models seems to be very important to the transient behavior, ie without reaching equilibrium. Because of diversity of structures and interactions that we see in ecosystems complex systems theory and fractals can be used for the interpretation of them.This thesis presents the study of these new theoretical and practical challenges and their application to different ecosystems.Fil:Saravia, Leonardo Ariel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Output of multifractal analysis software mfSBA

This is the output of multifractal analysis applied to each image The software used mfSBA is available at: . The output are ASCII files pasted in an spreadsheet. The output for each image is labeled as the file name. The columns named R- are the coefficient of determination. The columns named SD are the standard deviations. Tau is the slope of log(Zq) vs log(epsilon) and is used to calculate Dq

Periphyton Spatial Biomass distribution

Tiff Images of biomass spatial distribution of periphyton colonization at different times. The brigthness of each pixel represent the chlorophyl-a content estimated using the method described in: Saravia LA, Giorgi A, Momo FR (1999) A photographic method for estimating chlorophyll in periphyton on artificial substrata. Aquatic Ecology 33: 325–330. The initial letter of the file name correspond to the different tanks used in the experiment, then the number of the plate, and finally the date YYMMDD

Data from: Multifractal growth in periphyton communities

Periphyton is an aquatic community composed by algae, bacteria, fungi, and other microorganisms that can develop a complex architecture comparable to tropical forests. We analyzed the spatial pattern of a periphyton community along a succession developed in experimental tanks. Our aim was to identify regularities that may help us to explain the patchiness of this community. Therefore, we estimated the spatial pattern of periphyton biomass using a non-destructive image analysis technique to obtain a temporal series of the spatial distribution. These were analyzed using multifractal techniques. Multifractals are analogous to fractals but they look at the geometry of quantities instead of the geometry of pattern. To use these techniques the object of study must show scale invariance and then can be characterized by a spectra of fractal dimensions. Self-organization describes the evolution of complex structures that emerge spontaneously driven internally by variations of the system itself. The spatial distribution of biomass showed scale invariance at all stages of succession and as the periphyton developed in a homogeneous landscape, in a demonstration of self-organized behavior. Self-organization to a critical state (SOC) is presented in the complex systems literature as a general explanation for scale invariance in nature. SOC requires a mechanism where the history of past events in a place influence the actual dynamics, this was termed ecological memory. The scale invariance was found from the very beginning of the succession thus self-organized criticality is a very improbable explanation for the pattern because there would be not enough time for the build-up of ecological memory. Positive interactions between algae and bacteria, and the existence of different spatial scales of colonization and growth are the likely causes of this pattern. Our work is a demonstration of how large scale patterns emerge from local biotic interactions