Tritrophic Consequences of Host Range Expansion: The Impacts of Exotic Host Plants on Infection and Immunity in Native Insect Herbivores

Species introductions are a pervasive aspect of global change. Exotic plants, in particular, are present in nearly all terrestrial environments and have been incorporated into the diets of many native herbivores, giving rise to novel multitrophic interactions. These recent examples of host range evolution provide naturally occurring experiments through which to investigate the complex ecological factors that facilitate, or constrain, herbivore persistence within novel niches. Though adoption of exotic plants into the diets of native insect herbivores is common, their use is often associated with negative effects on herbivore growth and performance, relative to native host plants. However, herbivore fitness on different host plants is context-dependent and shaped by a multitude of factors beyond suitability for development, including interactions with diverse natural enemies. Consideration of herbivore performance within a tritrophic framework, including attack by and defense against these enemies, may be essential for understanding the outcomes of dietary expansion for native herbivores. In particular, entomopathogens represent critical agents of mortality for insect herbivores, yet their ecological impacts and importance in mediating diet breadth evolution remain poorly understood in many natural systems.In this dissertation, I combined approaches from the fields of eco-immunology, chemical ecology, and disease ecology to investigate the consequences of exotic host plant use for immune performance, chemical defense (i.e., phytochemical sequestration), and vulnerability to a viral pathogen in two North American herbivores: Euphydryas phaeton, the Baltimore checkerspot (Lepidoptera: Nymphalidae), and Anartia jatrophae, the white peacock (Lepidoptera: Nymphalidae). These herbivores provide compelling systems in which to compare the tritrophic outcomes of host range expansion, as they: (1) recently incorporated the same exotic plant, Plantago lanceolata (Plantaginaceae), into their diets, (2) exhibit reduced growth on the exotic plant, relative to native host plants, (3) are infected by the same entomopathogen, Junonia coenia densovirus, across wild populations, and (4) differ in their degree of dietary specialization and relationships with plant secondary chemistry, which can impact immunity and susceptibility to pathogens. Employing a combination of field-based surveys and manipulative laboratory experiments, I found that the outcomes of dietary expansion for herbivore infection and immunity differed across the two focal species. In E. phaeton, use of the exotic plant was associated with suppression of multiple immune parameters, differential sequestration of defensive phytochemicals (iridoid glycosides), and higher viral burdens during certain stages of development, representing potential costs of host range expansion. However, E. phaeton’s ability to survive densovirus infection was not reduced on the exotic host plant, suggesting that additional factors (e.g., phytochemical sequestration) may contribute to defense against this pathogen even when immunity is compromised. In contrast, use of the exotic plant dramatically increased resistance to viral infection in A. jatrophae, likely through suppression of replication, though immune performance did not vary based on host plant use. Together, this research demonstrates that, in certain systems, exotic host plants may represent equally suitable or even superior resources for supporting herbivore development, relative to native host plants, when the impacts of pathogen infection are considered. Moving forward, evaluation of the role of host plant use in mediating defense against infectious diseases across wild populations may provide a deeper understanding of the complex ecological factors shaping host range evolution in herbivorous species

All Is Not Loss: Plant Biodiversity in the Anthropocene

Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems

Relação da vegetação de caatinga com a condição geomorfométrica local

Objetivou-se, com o presente trabalho, avaliar o potencial das variáveis geomorfométricas extraídas de dados SRTM (Shuttle Radar Topographic Mission) para identificação de tipos vegetacionais da Reserva Particular do Patrimônio Natural de Serra das Almas, CE. Em estudo conduzido na escala de 1:100.000, as variáveis geomorfométricas (elevação, declividade, orientação de vertente, curvatura vertical e curvatura horizontal) foram confrontadas com o mapa de vegetação referência, através de análises de histogramas e análises discriminantes. As variáveis mais importantes na distinção entre os tipos vegetacionais, foram a elevação, a declividade e a curvatura vertical, embora se pudesse observar preferências de tipos mapeados em relação às demais variáveis. Apesar dos dados geomorfométricos mostrarem potencial indicativo das classes de vegetação pela interpretação dos padrões, as análises sob abordagem numérica resultaram em discriminação em um nível aquém do detalhamento temático do mapa referência. Concluiu-se que os dados geomorfométricos representaram significativos insumos para o mapeamento fitogeográfico, devendo ser explorados de forma integrada, em complementaridade às demais variáveis já utilizadas.The objective of this work was to assess the potential of geomorphometric variables, derived from SRTM (Shuttle Radar Topographic Mission) data, to help in identifying vegetation types in the Serra das Almas National Park (CE). A 1:100.000 survey vegetation map was used as reference and the geomorphometric variables (elevation, slope, aspect and profile and plan curvatures) were compared to the mapped units. The variables elevation, slope and profile curvature were shown as the most important for their high discrimination power of the vegetation types. Although geomorphometric data had strong potential for characterizing vegetation through map comparisons, the achieved thematic detail levels were under those of the reference map when data was analyzed under a numerical approach. It was concluded that geomorphometric data were important input for vegetation mapping, and should be employed together with currently used data

Supervised Pattern Recognition

Pattern recognition is the scientific discipline that focuses on the classification of data, objects or, in general terms, patterns into categories or classes. To achieve this goal, the methodology uses the extraction of information from the data observation, learn to recognize the different patterns contained within the data and make a decision based on the category of the patterns. This involves supervised classification methods, which are based on external knowledge of the area within the sample to be studied, and therefore, requires some a priori information before the chosen classification algorithm can be applied. The supervised methods are implemented using two main paradigms, statistical algorithms, and neural algorithms. The statistical approach uses parameters that are derived from sampled data in the form of training classes. The neural approach does not rely on statistical information derived from the sample data but is trained directly on the sample data