Dinâmica populacional, distribuição espacial e plano de amostragem sequencial de Euschistus heros (Fabricius, 1794) (Heteroptera: Pentatomidae) em cultivares de soja

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Demographic processes in the montane Atlantic rainforest: Molecular and cytogenetic evidence from the endemic frog Proceratophrys boiei

Historical climatic refugia predict genetic diversity in lowland endemics of the Brazilian Atlantic rainforest. Yet, available data reveal distinct biological responses to the Last Glacial Maximum (LGM) conditions across species of different altitudinal ranges. We show that species occupying Brazil's montane forests were significantly less affected by LGM conditions relative to lowland specialists, but that pre-Pleistocene tectonics greatly influenced their geographic variation. Our conclusions are based on palaeoclimatic distribution models, molecular sequences of the cytochrome b, 16S, and RAG-1 genes, and karyotype data for the endemic frog Proceratophrys boiei. DNA and chromosomal data identify in P. boiei at least two broadly divergent phylogroups, which have not been distinguished morphologically. Cytogenetic results also indicate an area of hybridization in southern Sao Paulo. The location of the phylogeographic break broadly matches the location of a NW-SE fault, which underwent reactivation in the Neogene and led to remarkable landscape changes in southeastern Brazil. Our results point to different mechanisms underpinning diversity patterns in lowland versus montane tropical taxa, and help us to understand the processes responsible for the large number of narrow endemics currently observed in montane areas of the southern Atlantic forest hotspot. (C) 2011 Elsevier Inc. All rights reserved.

Environmental suitability of a highly fragmented and heterogeneous landscape for forest bird species in south-eastern Brazil

Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April-September 2006 and January-March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 +/- 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c. 30% in total suitable areas. In average, models predicted a small increase (23.69 +/- 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.

Pollination services at risk: Bee habitats will decrease owing to climate change in Brazil

Native bees are important providers of pollination services, but there are cumulative evidences of their decline. Global changes such as habitat losses, invasions of exotic species and climate change have been suggested as the main causes of the decline of pollinators. In this study, the influence of climate change on the distribution of 10 species of Brazilian bees was estimated with species distribution modelling. We used Maxent algorithm (maximum entropy) and two different scenarios, an optimistic and a pessimistic, to the years 2050 and 2080. We also evaluated the percentage reduction of species habitat based on the future scenarios of climate change through Geographic Information System (GIS). Results showed that the total area of suitable habitats decreased for all species but one under the different future scenarios. The greatest reductions in habitat area were found for Melipona bicolor bicolor and Melipona scutellaris, which occur predominantly in areas related originally to Atlantic Moist Forest. The species analysed have been reported to be pollinators of some regional crops and the consequence of their decrease for these crops needs further clarification. (C) 2012 Elsevier B.V. All rights reserved.

Rekonstruktion der eiszeitlichen Verbreitung und Artbildung vier alpiner Primeln durch Artenverbreitungsmodelle und Phylogeographie

Aim: Previous studies revealed that diversification events in the western clade of the alpine Primula sect. Auricula were concentrated in the Quaternary cold periods. This implies that allopatric speciation in isolated glacial refugia was the most common mode of speciation. In the first part of the present dissertation, this hypothesis is further investigated by locating refugial areas of two sister species, Primula marginata & P. latifolia during the last glacial maximum, 21,000 years ago. In the second part, the glacial and postglacial history of P. hirsuta and P. daonensis is investigated. Location: European Alps. Methods: Glacial refugia were located using species distribution models, which are projected to last glacial maximum climate. These refugia are validated with geographic distribution patterns of intra-specific genetic diversity, rarity and variation. Results 1) Speciation: Glacial refugia of the sister taxa Primula marginata and P. latifolia were largely separated, only a small overlapping zone at the southern margin of the former glacier in the Maritime Alps exists. This overlapping zone is too small to indicate sympatric speciation. The largely separated glacial distribution of both species rather confirms our hypothesis of allopatric speciation in isolated glacial refugia. Results 2) Glacial and postglacial history: Surprizingly, the modelled potential refugia of three out of four Primula species are situated within the former ice-shield, except for P. marginata. This indicates that peripheral and central nunataks played an important role for the glacial survival in P. latifolia, P. hirsuta and P. daonensis, while peripheral refugia outside the maximum extend of the glacier were crucial in P. marginata. In P. hirsuta and P. latifolia SDMs allowed to exclude several hypothetical refugial areas that overlap with today’s distribution as potential refugia for the species. In P. marginata, hypothetical refugial areas at the periphery of the former ice-shield that overlap with today’s distribution were confirmed by the models. The results from the SDMs are confirmed by population genetic patterns in three out of four species. P. daonensis represents an exception, where population genetic data contradict the SDMs. Main conclusions: Species distribution models provide species specific scenarios of glacial distribution and postglacial re-colonization, which can be validated using population genetic analyses. This combined approach is useful and helps to understand the complex processes that have lead to the genetic and floristic patterns of biodiversity that is found today in the Alps.

Characterization of fold-related fractures in the carbonate rocks of the Cingoli anticline, northern Apennines, Italy

Thrust fault-related folds in carbonate rocks are characterized by deformation accommodated by different structures, such as joints, faults, pressure solution seams, and deformation bands. Defining the development of fracture systems related to the folding process is significant both for theoretical and practical purposes. Fracture systems are useful constrains in order to understand the kinematical evolution of the fold. Furthermore, understanding the relationships between folding and fracturing provides a noteworthy contribution for reconstructing the geodynamic and the structural evolution of the studied area. Moreover, as fold-related fractures influence fluid flow through rocks, fracture systems are relevant for energy production (geothermal studies, methane and CO2 , storage and hydrocarbon exploration), environmental and social issues (pollutant distribution, aquifer characterization). The PhD project shows results of a study carried out in a multilayer carbonate anticline characterized by different mechanical properties. The aim of this study is to understand the factors which influence the fracture formation and to define their temporal sequence during the folding process. The studied are is located in the Cingoli anticline (Northern Apennines), which is characterized by a pelagic multilayer characterized by sequences with different mechanical stratigraphies. A multi-scale analysis has been made in several outcrops located in different structural positions. This project shows that the conceptual sketches proposed in literature and the strain distribution models outline well the geometrical orientation of most of the set of fractures observed in the Cingoli anticline. On the other hand, the present work suggests the relevance of the mechanical stratigraphy in particular controlling the type of fractures formed (e.g. pressure solution seams, joints or shear fractures) and their subsequent evolution. Through a multi-scale analysis, and on the basis of the temporal relationship between fracture sets and their orientation respect layering, I also suggest a conceptual model for fracture systems formation.

Landscape ecology and genetics of the wolf in Italy

This PhD Thesis includes five main parts on diverse topics. The first two parts deal with the trophic ecology of wolves in Italy consequently to a recent increase of wild ungulates abundance. Data on wolf diet across time highlighted how wild ungulates are important food resource for wolves in Italy. Increasing wolf population, increasing numbers of wild ungulates and decreasing livestock consume are mitigating wolf-man conflicts in Italy in the near future. In the third part, non-invasive genetic sampling techniques were used to obtain genotypes and genders of about 400 wolves. Thus, wolf packs were genetically reconstructed using diverse population genetic and parentage software. Combining the results on pack structure and genetic relatedness with sampling locations, home ranges of wolf packs and dispersal patterns were identified. These results, particularly important for the conservation management of wolves in Italy, illustrated detailed information that can be retrieved from genetic identification of individuals. In the fourth part, wolf locations were combined with environmental information obtained as GIS-layers. Modern species distribution models (niche models) were applied to infer potential wolf distribution and predation risk. From the resulting distribution maps, information pastures with the highest risk of depredation were derived. This is particularly relevant as it allows identifying those areas under danger of carnivore attack on livestock. Finally, in the fifth part, habitat suitability models were combined with landscape genetic analysis. On one side landscape genetic analyses on the Italian wolves provided new information on the dynamics and connectivity of the population and, on the other side, a profound analysis of the effects that habitat suitability methods had on the parameterization of landscape genetic analyses was carried out to contributed significantly to landscape genetic theory.

Comparative phylogeography of two co-distributed arctic-alpine freshwater insect species in Europe

The distribution pattern of European arctic-alpine disjunct species is of growing interest among biogeographers due to the arising variety of inferred demographic histories. In this thesis I used the co-distributed mayfly Ameletus inopinatus and the stonefly Arcynopteryx compacta as model species to investigate the European Pleistocene and Holocene history of stream-inhabiting arctic-alpine aquatic insects. I used last glacial maximum (LGM) species distribution models (SDM) to derive hypotheses on the glacial survival during the LGM and the recolonization of Fennoscandia: 1) both species potentially survived glacial cycles in periglacial, extra Mediterranean refugia, and 2) postglacial recolonization of Fennoscandia originated from these refugia. I tested these hypotheses using mitochondrial sequence (mtCOI) and species specific microsatellite data. Additionally, I used future SDM to predict the impact of climate change induced range shifts and habitat loss on the overall genetic diversity of the endangered mayfly A. inopinatus.rnI observed old lineages, deep splits, and almost complete lineage sorting of mtCOI sequences between mountain ranges. These results support the hypothesis that both species persisted in multiple periglacial extra-Mediterranean refugia in Central Europe during the LGM. However, the recolonization of Fennoscandia was very different between the two study species. For the mayfly A. inopinatus I found strong differentiation between the Fennoscandian and all other populations in sequence and microsatellite data, indicating that Fennoscandia was recolonized from an extra European refugium. High mtCOI genetic structure within Fennoscandia supports a recolonization of multiple lineages from independent refugia. However, this structure was not apparent in the microsatellite data, consistent with secondary contact without sexual incompability. In contrast, the stonefly A. compacta exhibited low genetic structure and shared mtCOI haplotypes among Fennoscandia and the Black Forest, suggesting a shared Pleistocene refugium in the periglacial tundrabelt. Again, there is incongruence with the microsatellite data, which could be explained with ancestral polymorphism or female-biased dispersal. Future SDM projects major regional habitat loss for the mayfly A. inopinatus, particularly in Central European mountain ranges. By relating these range shifts to my population genetic results, I identified conservation units primarily in Eastern Europe, that if preserved would maintain high levels of the present-day genetic diversity of A. inopinatus and continue to provide long-term suitable habitat under future climate warming scenarios.rnIn this thesis I show that despite similar present day distributions the underlying demographic histories of the study species are vastly different, which might be due to differing dispersal capabilities and niche plasticity. I present genetic, climatic, and ecological data that can be used to prioritize conservation efforts for cold-adapted freshwater insects in light of future climate change. Overall, this thesis provides a next step in filling the knowledge gap regarding molecular studies of the arctic-alpine invertebrate fauna. However, there is continued need to explore the phenomenon of arctic-alpine disjunctions to help understand the processes of range expansion, regression, and lineage diversification in Europe’s high latitude and high altitude biota.

Counterbalancing effects of competition for resources and facilitation against grazing in alpine snowbed communities

Alpine snowbeds are habitats where the major limiting factors for plant growth are herbivory and a small time window for growth due to late snowmelt. Despite these limitations, snowbed vegetation usually forms a dense carpet of palatable plants due to favourable abiotic conditions for plant growth within the short growing season. These environmental characteristics make snowbeds particularly interesting to study the interplay of facilitation and competition. We hypothesised an interplay between resource competition and facilitation against herbivory. Further, we investigated whether these predicted neighbour effects were species-specific and/or dependent on ontogeny, and whether the balance of positive and negative plant–plant interactions shifted along a snowmelt gradient. We determined the neighbour effects by means of neighbour removal experiments along the snowmelt gradient, and linear mixed model analyses. The results showed that the effects of neighbour removal were weak but generally consistent among species and snowmelt dates, and depended on whether biomass production or survival was considered. Higher total biomass and increased fruiting in removal plots indicated that plants competed for nutrients, water, and light, thereby supporting the hypothesis of prevailing competition for resources in snowbeds. However, the presence of neighbours reduced herbivory and thereby also facilitated survival. For plant growth the facilitative effects against herbivores in snowbeds counterbalanced competition for resources, leading to a weak negative net effect. Overall the neighbour effects were not species-specific and did not change with snowmelt date. Our finding of counterbalancing effects of competition and facilitation within a plant community is of special theoretical value for species distribution models and can explain the success of models that give primary importance to abiotic factors and tend to overlook interrelations between biotic and abiotic effects on plants.

Correspondence establishment in statistical modeling of shapes with arbitrary topology

Correspondence establishment is a key step in statistical shape model building. There are several automated methods for solving this problem in 3D, but they usually can only handle objects with simple topology, like that of a sphere or a disc. We propose an extension to correspondence establishment over a population based on the optimization of the minimal description length function, allowing considering objects with arbitrary topology. Instead of using a fixed structure of kernel placement on a sphere for the systematic manipulation of point landmark positions, we rely on an adaptive, hierarchical organization of surface patches. This hierarchy can be built on surfaces of arbitrary topology and the resulting patches are used as a basis for a consistent, multi-scale modification of the surfaces' parameterization, based on point distribution models. The feasibility of the approach is demonstrated on synthetic models with different topologies.

Isolation and characterization of nine polymorphic microsatellite markers for the deep-sea shrimp Nematocarcinus lanceopes (Crustacea: Decapoda: Caridea)

Background: The shrimp Nematocarcinus lanceopes Bate, 1888 is found in the deep sea around Antarctica and sub-Antarctic islands. Previous studies on mitochondrial data and species distribution models provided evidence for a homogenous circum-Antarctic population of N. lanceopes. However, to analyze the fine-scale population genetic structure and to examine influences of abiotic environmental conditions on population composition and genetic diversity, a set of fast evolving nuclear microsatellite markers is required. Findings: We report the isolation and characterization of nine polymorphic microsatellite markers from the Antarctic deep-sea shrimp species Nematocarcinus lanceopes (Crustacea: Decapoda: Caridea). Microsatellite markers were screened in 55 individuals from different locations around the Antarctic continent. All markers were polymorphic with 9 to 25 alleles per locus. The observed heterozygosity ranged from 0.545 to 0.927 and the expected heterozygosity from 0.549 to 0.934. Conclusions: The reported markers provide a novel tool to study genetic structure and diversity in Nematocarcinus lanceopes populations in the Southern Ocean and monitor effects of ongoing climate change in the region on the populations inhabiting these.

A model-data comparison of Holocene timberline changes in the Swiss Alps reveals past and future drivers of mountain forest dynamics

Mountain vegetation is strongly affected by temperature and is expected to shift upwards with climate change. Dynamic vegetation models are often used to assess the impact of climate on vegetation and model output can be compared with paleobotanical data as a reality check. Recent paleoecological studies have revealed regional variation in the upward shift of timberlines in the Northern and Central European Alps in response to rapid warming at the Younger Dryas/Preboreal transition ca. 11700years ago, probably caused by a climatic gradient across the Alps. This contrasts with previous studies that successfully simulated the early Holocene afforestation in the (warmer) Central Alps with a chironomid-inferred temperature reconstruction from the (colder) Northern Alps. We use LandClim, a dynamic landscape vegetation model to simulate mountain forests under different temperature, soil and precipitation scenarios around Iffigsee (2065m a.s.l.) a lake in the Northwestern Swiss Alps, and compare the model output with the paleobotanical records. The model clearly overestimates the upward shift of timberline in a climate scenario that applies chironomid-inferred July-temperature anomalies to all months. However, forest establishment at 9800 cal. BP at Iffigsee is successfully simulated with lower moisture availability and monthly temperatures corrected for stronger seasonality during the early Holocene. The model-data comparison reveals a contraction in the realized niche of Abies alba due to the prominent role of anthropogenic disturbance after ca. 5000 cal. BP, which has important implications for species distribution models (SDMs) that rely on equilibrium with climate and niche stability. Under future climate projections, LandClim indicates a rapid upward shift of mountain vegetation belts by ca. 500m and treeline positions of ca. 2500m a.s.l. by the end of this century. Resulting biodiversity losses in the alpine vegetation belt might be mitigated with low-impact pastoralism to preserve species-rich alpine meadows.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Phytogeography of New Guinean orchids: richness, turnover, collection density

The aims of this study were (1) to assess the spatial distribution of orchid species richness in New Guinea, and (2) to examine patterns of species turnover in the orchid community through phytogeographical regionalization. We aimed to achieve these goals using botanical collection records, species distribution models (SDMs) and partitioning around medoids (PAM) clustering.

Bases metodológicas para un sistema de apoyo a la selección de especies en la restauración de la vegetación

RESUMEN El apoyo a la selección de especies a la restauración de la vegetación en España en los últimos 40 años se ha basado fundamentalmente en modelos de distribución de especies, también llamados modelos de nicho ecológico, que estiman la probabilidad de presencia de las especies en función de las condiciones del medio físico (clima, suelo, etc.). Con esta tesis se ha intentado contribuir a la mejora de la capacidad predictiva de los modelos introduciendo algunas propuestas metodológicas adaptadas a los datos disponibles actualmente en España y enfocadas al uso de los modelos en la selección de especies. No siempre se dispone de datos a una resolución espacial adecuada para la escala de los proyectos de restauración de la vegetación. Sin embrago es habitual contar con datos de baja resolución espacial para casi todas las especies vegetales presentes en España. Se propone un método de recalibración que actualiza un modelo de regresión logística de baja resolución espacial con una nueva muestra de alta resolución espacial. El método permite obtener predicciones de calidad aceptable con muestras relativamente pequeñas (25 presencias de la especie) frente a las muestras mucho mayores (más de 100 presencias) que requería una estrategia de modelización convencional que no usara el modelo previo. La selección del método estadístico puede influir decisivamente en la capacidad predictiva de los modelos y por esa razón la comparación de métodos ha recibido mucha atención en la última década. Los estudios previos consideraban a la regresión logística como un método inferior a técnicas más modernas como las de máxima entropía. Los resultados de la tesis demuestran que esa diferencia observada se debe a que los modelos de máxima entropía incluyen técnicas de regularización y la versión de la regresión logística usada en las comparaciones no. Una vez incorporada la regularización a la regresión logística usando penalización, las diferencias en cuanto a capacidad predictiva desaparecen. La regresión logística penalizada es, por tanto, una alternativa más para el ajuste de modelos de distribución de especies y está a la altura de los métodos modernos con mejor capacidad predictiva como los de máxima entropía. A menudo, los modelos de distribución de especies no incluyen variables relativas al suelo debido a que no es habitual que se disponga de mediciones directas de sus propiedades físicas o químicas. La incorporación de datos de baja resolución espacial proveniente de mapas de suelo nacionales o continentales podría ser una alternativa. Los resultados de esta tesis sugieren que los modelos de distribución de especies de alta resolución espacial mejoran de forma ligera pero estadísticamente significativa su capacidad predictiva cuando se incorporan variables relativas al suelo procedente de mapas de baja resolución espacial. La validación es una de las etapas fundamentales del desarrollo de cualquier modelo empírico como los modelos de distribución de especies. Lo habitual es validar los modelos evaluando su capacidad predictiva especie a especie, es decir, comparando en un conjunto de localidades la presencia o ausencia observada de la especie con las predicciones del modelo. Este tipo de evaluación no responde a una cuestión clave en la restauración de la vegetación ¿cuales son las n especies más idóneas para el lugar a restaurar? Se ha propuesto un método de evaluación de modelos adaptado a esta cuestión que consiste en estimar la capacidad de un conjunto de modelos para discriminar entre las especies presentes y ausentes de un lugar concreto. El método se ha aplicado con éxito a la validación de 188 modelos de distribución de especies leñosas orientados a la selección de especies para la restauración de la vegetación en España. Las mejoras metodológicas propuestas permiten mejorar la capacidad predictiva de los modelos de distribución de especies aplicados a la selección de especies en la restauración de la vegetación y también permiten ampliar el número de especies para las que se puede contar con un modelo que apoye la toma de decisiones. SUMMARY During the last 40 years, decision support tools for plant species selection in ecological restoration in Spain have been based on species distribution models (also called ecological niche models), that estimate the probability of occurrence of the species as a function of environmental predictors (e.g., climate, soil). In this Thesis some methodological improvements are proposed to contribute to a better predictive performance of such models, given the current data available in Spain and focusing in the application of the models to selection of species for ecological restoration. Fine grained species distribution data are required to train models to be used at the scale of the ecological restoration projects, but this kind of data are not always available for every species. On the other hand, coarse grained data are available for almost every species in Spain. A recalibration method is proposed that updates a coarse grained logistic regression model using a new fine grained updating sample. The method allows obtaining acceptable predictive performance with reasonably small updating sample (25 occurrences of the species), in contrast with the much larger samples (more than 100 occurrences) required for a conventional modeling approach that discards the coarse grained data. The choice of the statistical method may have a dramatic effect on model performance, therefore comparisons of methods have received much interest in the last decade. Previous studies have shown a poorer performance of the logistic regression compared to novel methods like maximum entropy models. The results of this Thesis show that the observed difference is caused by the fact that maximum entropy models include regularization techniques and the versions of logistic regression compared do not. Once regularization has been added to the logistic regression using a penalization procedure, the differences in model performance disappear. Therefore, penalized logistic regression may be considered one of the best performing methods to model species distributions. Usually, species distribution models do not consider soil related predictors because direct measurements of the chemical or physical properties are often lacking. The inclusion of coarse grained soil data from national or continental soil maps could be a reasonable alternative. The results of this Thesis suggest that the performance of the models slightly increase after including soil predictors form coarse grained soil maps. Model validation is a key stage of the development of empirical models, such as species distribution models. The usual way of validating is based on the evaluation of model performance for each species separately, i.e., comparing observed species presences or absence to predicted probabilities in a set of sites. This kind of evaluation is not informative for a common question in ecological restoration projects: which n species are the most suitable for the environment of the site to be restored? A method has been proposed to address this question that estimates the ability of a set of models to discriminate among present and absent species in a evaluation site. The method has been successfully applied to the validation of 188 species distribution models used to support decisions on species selection for ecological restoration in Spain. The proposed methodological approaches improve the predictive performance of the predictive models applied to species selection in ecological restoration and increase the number of species for which a model that supports decisions can be fitted.