Multi-level impacts of introduced wild boar on Patagonian ecosystems

Biological invasions are a pervasive global change that threatens biodiversity and the functioning of natural ecosystems, yet most studies focus on population impacts. Furthermore, the effects of invasive species on ecosystems are greatest when they introduce a novel disturbance. In this dissertation I reviewed the impact of wild boar (Sus scrofa) on native communities worldwide, identifying research needs. Wild boar overturns extensive areas of vegetation to feed on belowground plant parts, insects and fungi, thus altering native ecosystems integrity. By means of observational and experimental studies I addressed some of the research gaps on the impact of wild boar invasions on native communities and ecosystem functioning in Patagonia, Argentina. I evaluated the impact of wild boar on native plant community composition and structure, on soil properties, and on facilitating further invasion. I found that wild boar significantly alters aboveground ecosystem properties by reducing plant biomass and altering plant community composition. Furthermore, wild boar rooting disturbance significantly reduce litter decomposition rates, while soil properties were influenced by plant community more than by boar rooting disturbance. Lastly, I found that rooting disturbance rather than seed dispersal by wild boar facilitates further invasion by plants. Overall, these findings indicate that wild boar can have profound impacts on native ecosystems

Disparate responses of above- and belowground properties to soil disturbance by an invasive mammal

Introduced mammalian herbivores can negatively affect ecosystem structure and function if they introduce a novel disturbance to an ecosystem. For example, belowground foraging herbivores that bioturbate the soil, may alter process rates and community composition in ecosystems that lack native belowground mammalian foragers. Wild boar (Sus scrofa) disturb the soil system and plant community via their rooting behavior in their native range. Given their size and the numbers in their populations, this disturbance can be significant in forested ecosystems. Recently, wild boar were introduced to Patagonian forests lacking native mammalian herbivores that forage belowground. To explore how introduced wild boar might alter forested ecosystems, we conducted a large-scale wild boar exclusion experiment in three different forest types (Austroducedrus chilensis forest, Nothofagus dombeyi forest, and shrublands). Wild boar presence altered plant composition and structure, reducing plant biomass 3.8-fold and decreasing both grass and herb cover relative to areas where wild boar were excluded. Decomposition rates and soil compaction also declined by 5% in areas where boar had access; however, rooting had no effect on soil nutrient stocks and cycling. Interestingly, there were no differences in wild boar impacts on different forest types. We found that after 3-years of exclusion, belowground foraging by wild boar had a larger impact on plant community structure and biomass than it did on soil nutrient processes.Fil: Barrios Garcia Moar, Maria Noelia. Administración de Parques Nacionales. Delegación Regional Patagonia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Classen, Aimee T.. University of Tennessee; Estados UnidosFil: Simberloff, Daniel. University of Tennessee; Estados Unido

Mismatch between media coverage and research on invasive species: The case of wild boar (Sus scrofa) in Argentina

Invasive species are a pervasive driver of global change with increasing media coverage. Media coverage and framing can influence both invasive species management and policies, as well as shed light on research needs. Using the wild boar (Sus scrofa) invasion in Argentina as a case study, we conducted a content analysis of media coverage and scientific articles. Specifically, we compared news and scientific articles based on their emphasis: ecological, economic, and health impacts and the overall perception portrayed in the news: “positive” when the articles emphasized benefits from wild boar and “negative” when focused on damage and/or loss. A literature search using Google news, Web of Science, Scielo, and Google Scholar yielded a total of 194 news articles and 37 research papers on wild boar in Argentina. More than half of the news articles focused on economic impacts of wild boar (56%) such as sport hunting, illegal hunting, and road accidents; while 27% focused on ecological impacts, and 10% on health impacts. In contrast, the majority of the scientific articles (65%) focused on ecological impacts of wild boar on native species and ecosystems; while 21% were related to health impacts and only 8.3% of scientific articles were related to economic impacts. This mismatch between media and science reveals a disconnection between social and scientific interests in wild boar and their management in Argentina, and it provides insights to research needs and prevention of management conflicts. Additionally, we found that 66.8% of news articles focused on “negative” aspects of wild boar, while 33.2% of news articles portrayed “positive” perceptions. This finding is very important because the management of invasive species such as wild boar usually requires lethal techniques, and the success of the programs depend on favorable social and political support. Good science communication is therefore key to helping scientists and managers perform more effective management actions.Fil: Ballari, Sebastián A.. Administración de Parques Nacionales. Parque Nacional "Nahuel Huapi"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; ArgentinaFil: Barrios Garcia Moar, Maria Noelia. Administración de Parques Nacionales. Parque Nacional "Nahuel Huapi"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentin

Node-by-node disassembly of a mutualistic interaction web driven by species introductions

Interaction webs summarize the diverse interactions among species in communities. The addition or loss of particular species and the alteration of key interactions can lead to the disassembly of the entire interaction web, although the nontrophic effects of species loss on interaction webs are poorly understood. We took advantage of ongoing invasions by a suite of exotic species to examine their impact in terms of the disassembly of an interaction web in Patagonia, Argentina. We found that the reduction of one species (a host of a keystone mistletoe species) resulted in diverse indirect effects that led to the disassembly of an interaction web through the loss of the mistletoe, two key seed-dispersers (a marsupial and a bird), and a pollinator (hummingbird). Our results demonstrate that the gains and losses of species are both consequences and drivers of global change that can lead to underappreciated cascading coextinctions through the disruption of mutualisms.Fil: Rodriguez Cabal, Mariano Alberto. University Of Tennessee; Estados Unidos. University Of British Columbia; CanadáFil: Barrios Garcia Moar, Maria Noelia. University Of Tennessee; Estados Unidos. University Of British Columbia; CanadáFil: Amico, Guillermo Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; ArgentinaFil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; ArgentinaFil: Sanders, Nathan J.. University Of Tennessee; Estados Unidos. Natural History Museun Of Copenhague; Dinamarc

Global Invader Impact Network (GIIN): toward standardized evaluation of the ecological impacts of invasive plants

Terrestrial invasive plants are a global problem and are becoming ubiquitous components of most ecosystems. They are implicated in altering disturbance regimes, reducing biodiversity, and changing ecosystem function, sometimes in profound and irreversible ways. However, the ecological impacts of most invasive plants have not been studied experimentally, and most research to date focuses on few types of impacts, which can vary greatly among studies. Thus, our knowledge of existing ecological impacts ascribed to invasive plants is surprisingly limited in both breadth and depth. Our aim was to propose a standard methodology for quantifying baseline ecological impact that, in theory, is scalable to any terrestrial plant invader (e.g., annual grasses to trees) and any invaded system (e.g., grassland to forest). The Global Invader Impact Network (GIIN) is a coordinated distributed experiment composed of an observational and manipulative methodology. The protocol consists of a series of plots located in (1) an invaded area; (2) an adjacent removal treatment within the invaded area; and (3) a spatially separate uninvaded area thought to be similar to pre-invasion conditions of the invaded area. A standardized and inexpensive suite of community, soil, and ecosystem metrics are collected allowing broad comparisons among measurements, populations, and species. The method allows for one-time comparisons and for long-term monitoring enabling one to derive information about change due to invasion over time. Invader removal plots will also allow for quantification of legacy effects and their return rates, which will be monitored for several years. GIIN uses a nested hierarchical scale approach encompassing multiple sites, regions, and continents. Currently, GIIN has network members in six countries, with new members encouraged. To date, study species include representatives of annual and perennial grasses; annual and perennial forbs; shrubs; and trees. The goal of the GIIN framework is to create a standard yet flexible platform for understanding the ecological impacts of invasive plants, allowing both individual and synthetic analyses across a range of taxa and ecosystems. If broadly adopted, this standard approach will offer unique insight into the ecological impacts of invasive plants at local, regional, and global scales.Fil: Barney, Jacob N. Virginia Tech. Department of Plant Pathology, Physiology, and Weed Science; Estados UnidosFil: Tekiela, Daniel R. Virginia Tech. Department of Plant Pathology, Physiology, and Weed Science; Estados UnidosFil: Barrios Garcia Moar, Maria Noelia. Consejo Nacional de Investigaciones Científicas y Técnicas. CENAC-APN; ArgentinaFil: Dimarco, Romina Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas-Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Grupo de Ecología de Poblaciones de Insectos; ArgentinaFil: Hufbauer, Ruth A. Colorado State University. Department of Bioagricultural Sciences and Pest Management and Graduate Degree Program in Ecology; Estados UnidosFil: Leipzig-Scott, Peter. Colorado State University. Department of Bioagricultural Sciences and Pest Management and Graduate Degree Program in Ecology; Estados UnidosFil: Nuñez, Martin A. Consejo Nacional de Investigaciones Científicas y Técnicas-Universidad del Comahue. INIBIOMA. Laboratorio de Ecotono; ArgentinaFil: Pauchard, Anibal. Universidad de Concepción. Facultad de Ciencias Forestales. Laboratorio de Invasiones Biolóogicas; Chile. Institute of Ecology and Biodiversity (IEB); ChileFil: Pysek, Petr. The Czech Academy of Sciences. Institute of Botany. Department of Invasion Ecology; República Checa. Charles University in Prague. Faculty of Science. Department of Ecology; República ChecaFil: Viıtkov, Michaela. The Czech Academy of Sciences. Institute of Botany. Department of Invasion Ecology; República ChecaFil: Maxwell, Bruce D. Montana State University. Department of Land Resources and Environmental Sciences; Estados Unido

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

Distribución de humedales en la República Argentina

Los humedales, que representan aproximadamente el 7% de la superficie de la tierra (Ramsar, 2018) se encuentran entre los ecosistemas más valiosos no sólo en términos socioeconómico-productivos, sino también ambientales, dada su importancia en la provisión de servicios ecosistémicos y biodiversidad. La extensión de humedales naturales viene disminuyendo en todo el mundo y cada vez con mayor celeridad. El crecimiento poblacional previsto para las próximas décadas generará un incremento en la demanda de servicios ecosistémicos provenientes de esto socio-agroecosistemas, con lo cual el maximizar oportunidades productivas y al mismo tiempo minimizar potenciales impactos ambientales y sociales negativos, constituye el gran desafío para los tomadores de decisión. Esto requiere del análisis, aplicación y evaluación de herramientas y tecnologías que contribuyan a la gestión sostenible de los humedales. En los últimos años, el incremento de flujos de datos satelitales de libre acceso, el surgimiento de la computación en la nube y el creciente uso de algoritmos de aprendizaje automatizado han facilitado la integración y procesamiento de grandes volúmenes de datos permitiendo acortar tiempos y mejorar productos cartográficos. En Argentina son escasos los trabajos de abordaje a nivel nacional en relación a la ubicación de los humedales en el territorio nacional. El objetivo de nuestro trabajo fue, por un lado, generar un mapa actualizado de la probabilidad de ocurrencia y distribución de humedales en todo el país a partir de un análisis multitemporal de 20 años de imágenes satelitales, así como desarrollar un marco metodológico que permita establecer dicha ocurrencia en todo el territorio nacional, a través de una plataforma de fácil acceso y de fuente abierta. Para esto, se procesó 26.000 sitios de entrenamiento, 54720 imágenes satelitales de los sensores Landsat 5 y 8 y el Modelo Digital de Elevaciones de Argentina (MDE_Ar), a partir de los cuales se derivaron 43 variables predictoras, se aplicó el algoritmo Random Forest (RF) dentro del Google Earth Engine (GEE). El mapa resultante presenta una muy buena precisión en términos de análisis de campo, visual y estadístico, teniendo en cuenta la gran superficie del país (2,78 millones km2). La exactitud global de la determinación fue del 89%, mientras que la exactitud del productor y usuario (especificidad y precisión, respectivamente) para la clase humedal fue, en ambos casos, del 94%. Basándonos en el mapa final de determinación, estimamos que el 9,5% (265.200 km2) de Argentina está cubierto por humedales.Fil: Navarro, Marí­a Fabiana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Navarro, Carlos S. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Reconquista. ArgentinaFil: Barrios, Raúl. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes, ArgentinaFil: Dieta, Victorio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Delta del Paraná. Agencia De Extensión Rural Delta Frontal; ArgentinaFil: Garcia Martinez, Guillermo Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Esquel; ArgentinaFil: Iturralde, Rosario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Agencia de Extensión Rural Olavarría; Argentina.Fil: Iturralde Ortegui, María del Rosario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Agencia de Extensión Rural Olavarría; Argentina.Fil: Kurtz, Ditmar Bernardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; Argentina.Fil: Michard, Nicole Jacqueline. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Paredes, Paula Natalia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Saucedo, Griselda Isabel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; ArgentinaFil: Alday, Silvina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Juan; Argentina.Fil: Cianfagna, Francisco. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas, Departamento de Hidrología; ArgentinaFil: Curcio, Matías Hernán. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agroforestal Esquel; ArgentinaFil: Enriquez, Andrea Soledad. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área Recursos Naturales. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Lopez, Astor Emilio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Sáenz Peña; ArgentinaFil: Miranda, Federico Waldemar. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria El Colorado. Agencia de Extensión Rural Formosa; ArgentinaFil: Pezzola, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Umaña, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Laboratorio de Teledetección; ArgentinaFil: Vidal, Claudia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Reconquista; Argentina.Fil: Winschel, Cristina Ines. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Gavier Pizarro, Gregorio Ignacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Calamari, Noelia Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentin

A review of wild boar Sus scrofa diet and factors affecting food selection in native and introduced ranges

1. The wild boar Sus scrofa is an omnivore with one of the largest geographical ranges of all species. However, no synthesis exists on its diet, feeding behaviour and factors affecting food selection in its native and introduced ranges. 2. A literature review and a test of effect size revealed significant differences in wild boar diet composition in native and introduced ranges. Wild boar diet is dominated by plant material (∼90%) in both ranges, but animal matter and fungi are consumed in greater proportions in the introduced range than in the native range. Food items frequently include agricultural crops (especially in the native range) and endangered animal species (especially in the introduced range). Energy requirements, food availability, and seasonal and geographical variations are major factors influencing food selection by wild boar. These factors may also interact with human activities (e.g. agricultural crops, supplementary feeding) to influence diet composition further. 3. Dietary studies should be more rigorous and consistent across ranges to allow better comparisons. A detailed study of diet in combination with seasonal patterns of habitat use could provide key information such as target species and susceptible habitats on which management efforts should focus.Fil: Barrios Garcia Moar, Maria Noelia. University Of Tennessee; Estados UnidosFil: Ballari, Sebastián A.. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; Argentin

Patterns of use and damage by exotic deer on native plant communities in northwestern Patagonia

Ungulate overabundance can strongly alter composition and structure of forest communities through selective damage independently of the herbivory history of the recipient system. In the early 1900s, red and fallow deer (Cervus elaphus and Dama dama, respectively) were introduced to northwestern Patagonia. We studied patterns of relative habitat use, damage, and species selection by introduced deer populations in three major plant communities that have the longest history of invasion in the region. We also evaluated community structure and composition characteristics as possible explanatory factors for the observed patterns of browsing, fraying, and bark-stripping. At the species level, exotic deer browsed more than expected on two evergreen species (Austrocedrus chilensis and Schinus patagonicus) and two spiny species (Colletia hystrix and Dasyphyllum diacanthoides), while one dominant shrubland tree (Lomatia hirsuta) was selected for fraying and bark-stripping. Browsing was the more widespread damage in all plant communities, while fraying and bark-stripping occurred at low incidence. Furthermore, species identity was found as the main driver of deer damage over plant community type. Finally, variation in damage and in habitat use was explained by community structure and composition characteristics. Bark-stripping and fraying are best predicted by community composition, whereas browsing and habitat use are best predicted by structural properties including understory cover, cover of fallen logs, and tree density. The patterns of damage and the association with community structure characteristics reported here provide insight for developing management strategies.Fil: Barrios Garcia Moar, Maria Noelia. University of Tennessee; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; ArgentinaFil: Relva, Maria Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; ArgentinaFil: Kitzberger, Thomas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentin