Modelagem hierárquica multi-espécies para dados de comunidades : benefícios e aplicações

A biodiversidade é moldada por distintos processos ecológicos e evolutivos, atuais e passados, e entender como ela se distribui no espaço e no tempo é uma das questões centrais da ecologia de comunidades. Para entender a biodiversidade, precisamos formas de representá-la, para tanto utilizamos métricas de diversidade. As métricas de diversidade descrevem um padrão, seja na ocorrência das espécies ou de riqueza, e é a partir desses padrões que inferimos os principais processos que moldam as comunidades. Distintos processos podem gerar um mesmo padrão, e discriminar quais processos são mais relevantes nos permite compreender a montagem das comunidades, além de aumentar nossa capacidade de predizer como alterações ambientais afetam a biodiversidade. Independente do processo que estrutura as comunidades, quando medimos a biodiversidade contamos com um erro inerente a qualquer estudo ecológico: a detecção imperfeita. Nessa tese, usamos modelos hierárquicos multi-espécies tanto para acessar como a detecção imperfeita pode afetar os padrões de diversidade (Capítulo 1), como para avaliar processos que estruturam as comunidades em escalas distintas (Capítulo 2 e Capítulo 3). Como organismo modelo, utilizamos a guilda de borboletas frugívoras, as quais são representativas das respostas da diversidade às alterações ambientais. Utilizando dados de comunidades de borboletas frugívoras em escala local, no Capítulo 1, avaliamos como falhas na detecção de indivíduos podem confundir o padrão observado em distintas métricas de diversidade, ressaltando a importância do uso desses modelos para avaliar a diversidade sempre que possível. Nos capítulos 2 e 3, apesar de não considerarmos a detecção imperfeita, acessamos como o filtro ambiental (determinado por variáveis climáticas e de paisagem) e biótico modelam a distribuição das espécies. Enquanto no capítulo 2, avaliamos esses processos para comunidades de borboletas frugívoras do Pampa gaúcho, um dos biomas mais desprotegidos do Brasil, no Capítulo 3 usamos um conjunto de dados de comunidades de borboletas frugívoras da Mata Atlântica, a qual é considerada hotspot de diversidade. De maneira geral, demonstro nessa tese a importância da utilização de ferramentas de modelagem que considerem a detecção imperfeita, bem como a não independência (coocorrência) das espécies em modelos de ecologia de comunidade, como os modelos hierárquicos multi- espécies. Dentre as principais vantagens desses modelos destaco a propagação de erro nas estimativas dos parâmetros e a resposta compartilhada das respostas entre as espécies, que permite tanto modelar espécies raras e melhorar a estimativa dos parâmetros quando a confiabilidade da estimativa. Dentre as limitações, destaco a complexidade que esses modelos podem assumir, sendo dispendiosos de tempo e de informações a priori, e também da natureza dos dados, já que modelos como o de detecção precisam de réplicas temporais ou espaciais. Apesar disso, o desenvolvimento de abordagens mais generalizadas e a popularização dos modelos hierárquicos multi- espécies têm muito a contribuir para o entendimento da biodiversidade e dos principais processos que a mantém no tempo e no espaço.Biodiversity is shaped by current and past ecological and evolutionary processes, and understanding how it is distributed in space and time is one of the central questions of community ecology. To understand biodiversity, we need ways of representing it, such as diversity metrics. Diversity metrics describe a pattern, either in species occurrence or richness, and it is from these patterns that we infer the main processes that shape communities. Different processes can generate the same pattern, and decoupling which processes are most relevant gives us a better understanding of community assembly and increases our ability to predict how environmental changes affect biodiversity. Regardless of the process that structures communities, when we measure biodiversity, we rely on an inherent error in all ecological work: imperfect detection. In this thesis, I employ hierarchical multi-species models to assess how imperfect detection affects diversity patterns (Chapter 1) and also to evaluate which processes are responsible for structuring communities in different scales (Chapter 2 and Chapter 3). For this, I use the guild of fruit-feeding butterflies as a model organism, which is highly diverse and sensitive to environmental changes. Using data from local-scale fruit-feeding butterfly communities, in Chapter 1, we evaluated how failures to detect individuals can bias diversity patterns observed in taxonomic, functional, and phylogenetic diversity, highlighting the importance of using these models to obtain more reliable estimates of diversity whenever possible. In Chapters 2 and 3, we assessed how the environmental (determined by climate and landscape variables) and biotic filter shape species distribution. While in Chapter 2, we evaluated these processes for distinct communities of fruit-feeding butterflies in Pampa gaucho, one of the most unprotected biomes in Brazil, in Chapter 3, we used a dataset of fruit-feeding butterfly communities in the Atlantic Forest, which is among the world’s top five biodiversity hotspots. Overall, I demonstrate in this thesis the importance of using modeling tools that consider imperfect detection and species' non-independence (cooccurrence) in community ecology models, such as hierarchical multi-species models. We demonstrated that hierarchical multi-species models are flexible and robust tools and provide an important direction for community analyses. Among its main advantages is the propagation of errors in parameter estimates and the sharing of information among species, allowing both modeling of rare species and improving parameter estimates and estimate uncertainty. Limitations include the complexity that these models can take on, being costly in time and prior information, and the nature of the data, since models, such as N- mixture models, need temporal or spatial replicates. Nevertheless, the development of more generalized approaches and the popularization of hierarchical multi-species models has much to contribute to understanding biodiversity and the main processes that maintain it in time and space

A discussion on corruption and political risks in Latin American countries: a general view using chaos theory

info:eu-repo/semantics/acceptedVersio

Quantifying ecological variation across jurisdictional boundaries in a management mosaic landscape

Context Large landscapes exhibit natural heterogeneity. Land management can impose additional variation, altering ecosystem patterns. Habitat characteristics may reflect these management factors, potentially resulting in habitat differences that manifest along jurisdictional boundaries. Objectives We characterized the patchwork of habitats across a case study landscape, the Grand Canyon Protected Area-Centered Ecosystem. We asked: how do ecological conditions vary across different types of jurisdictional boundaries on public lands? We hypothesized that differences in fire and grazing, because they respond to differences in management over time, contribute to ecological differences by jurisdiction. Methods We collected plot-scale vegetation and soils data along boundaries between public lands units surrounding the Grand Canyon. We compared locations across boundaries of units managed differently, accounting for vegetation type and elevation differences that pre-date management unit designations. We used generalized mixed effects models to evaluate differences in disturbance and ecology across boundaries. Results Jurisdictions varied in evidence of grazing and fire. After accounting for these differences, some measured vegetation and soil properties also differed among jurisdictions. The greatest differences were between US Forest Service wilderness and Bureau of Land Management units. For most measured variables, US Forest Service non-wilderness units and National Park Service units were intermediate. Conclusions In this study, several ecological properties tracked jurisdictional boundaries, forming a predictable patchwork of habitats. These patterns likely reflect site differences that pre-date jurisdictions as well as those resulting from different management histories. Understanding how ecosystem differences manifest at jurisdictional boundaries can inform resource management, conservation, and cross-boundary collaborations

A Double Machine Learning Trend Model for Citizen Science Data

1. Citizen and community-science (CS) datasets have great potential for estimating interannual patterns of population change given the large volumes of data collected globally every year. Yet, the flexible protocols that enable many CS projects to collect large volumes of data typically lack the structure necessary to keep consistent sampling across years. This leads to interannual confounding, as changes to the observation process over time are confounded with changes in species population sizes. 2. Here we describe a novel modeling approach designed to estimate species population trends while controlling for the interannual confounding common in citizen science data. The approach is based on Double Machine Learning, a statistical framework that uses machine learning methods to estimate population change and the propensity scores used to adjust for confounding discovered in the data. Additionally, we develop a simulation method to identify and adjust for residual confounding missed by the propensity scores. Using this new method, we can produce spatially detailed trend estimates from citizen science data. 3. To illustrate the approach, we estimated species trends using data from the CS project eBird. We used a simulation study to assess the ability of the method to estimate spatially varying trends in the face of real-world confounding. Results showed that the trend estimates distinguished between spatially constant and spatially varying trends at a 27km resolution. There were low error rates on the estimated direction of population change (increasing/decreasing) and high correlations on the estimated magnitude. 4. The ability to estimate spatially explicit trends while accounting for confounding in citizen science data has the potential to fill important information gaps, helping to estimate population trends for species, regions, or seasons without rigorous monitoring data.Comment: 28 pages, 6 figure

Analysing effects of spatiotemporally distributed species interactions in Maculinea systems

We analyse effects of species-interaction and spatiotemporal host distribution on persistence of Maculinea populations at isolated habitat sites. Maculinea butterflies are parasites of Myrmica ants. The butterfly caterpillars infest host ant nest in the vicinity of their initial oviposition plant. Thus, spatial distribution of initial host plants (oviposition plants), implies a spatial distribution of parasitism. We develop a generic spatially-explicit rule-based simulation model for a Maculinea systems, to analyse the influence of different spatially relevant parameters on the performance of a Maculinea population. Parameter variation considers spatial host plant distribution, initial spatial host ant distribution and budding-range, which defines the probability distribution of colonising distances of ants. In simulation runs, it can be seen that the spatial distribution of host ants adapts to the spatially distributed parasitism from Maculinea caterpillars. Areas without host plants (unexploited areas) are completely inhabited by host ants. In areas with host plants (exploited areas) mean density of host ants is lower. Ant nests show dynamics. They are abandoned or nest sites are recolonised. Because of spatial segregation of exploitable and non-exploitable areas and by small scale dispersal of host ants (budding), areas of different effectiveness for Maculinea population performance can be distinguished on a Maculinea habitat site: These are reproductive area, buffer, sink and non-contributing area. Consequently, number of host plants is not the only decisive factor for performance of a Maculinea population. As well it is important how well empty nest sites in the vicinity of host plants can be colonised by host ants. We find two different mechanisms, which limit re-growth of the Maculinea butterfly population and lead to different types of dynamics. Population viability analysis (PVA) is a standard method for single species systems. However, the Maculinea system consists of interacting species with more complex dynamics. There is still no standardised methodology for PVA of multi-species systems. We derive a phenomenological description of distributions of extinction times for populations in a large class of systems of interacting species. We find in analytical calculations that the long term behaviour of distributions of times to extinction in multi-species systems can be analysed with the ln(1-P_{0})-method suggested for single species systems. Thus, this method can be transferred. Comparing distributions of times to extinction of single and interacting species, we find that long term extinction of established populations follows a similar process. However, on short time-scales, population cycles modulate extinction risk. In systems of interacting species, an initial transient phase can have strong influence on persistence of the population. In simulations of the Macu model, we observe that it takes up to 50 generations until the system reaches its established state. This can lead to a bottleneck of the population. We develop a landscape analysis method for multi-species systems. For that purpose, suitability of different landscapes is assessed for their ability to sustain particular populations. Suitability is measured by population persistence. Therefore, dynamics of the system and requirements of the populations are taken into account when assessing suitability. This method is applied to assess effects of the influence of different spatially relevant parameters. No major effects of initial host ant distribution on persistence of Maculinea populations can be found. In contrast, spatial distribution of host plants has a main effect. Thus, the host plant distribution can be considered as landscape structure of the Maculinea system on the site. Rules of thumb for suitable structures of host plant distributions and a spatial index are given. In general heterogeneous host plant distributions of intermediate density are a good option

Public Value under Chaotic Conditions

Economic interpretation of public value was elaborated in welfare theory and public choice literature. Nowadays public value describes the value that an organization contributes to society (Moore 1995). The authors discuss this definition and look for a more focused concept of value. The chaotic conditions can be defined according to chaos theory or as conditions of disorder. The authors show conditions for chaos’ situations. Even in situations that are characterized by deterministic model, the model solutions and public value may become unpredictable because of non-linear relations between variables or of initial conditions prevailing. Disorder situations occur in case of natural disasters, extreme population changes, economic crises, transformation situations and a breakdown of unions and national states. The difficulty to formulate public values are discussed for different kinds of disorders and evaluation scheme

Nature’s Stories Preserved in Museums: The value and utility of Natural History Collections for Ecology, Biogeography, and Biodiversity.

Natural history collections are hosed in very important institutions called museums, and they play an essential role in documenting species and to let people be educated about ecology, biogeography, and conservation processes. Through the use and digitation of collections, I worked on projects that utilized digitized data using scientific collections from Ecuador and the US (UNRMNH and the McGuire Center) to examine traits related to thermoregulation processes. I also examined land use and habitat change of Lepidoptera and Coleoptera (Scarabaeidae: Scarabaeinae) across different gradients based on museum specimens. I have identified the main variables influencing dung beetle distribution in Ecuador based on a niche model, finding also high turnover levels in functional groups at larger scales, suggesting that dung beetles show high levels of habitat specialization in Ecuador, providing an essential framework for evaluating potential dung beetle habitat and diversity at different scales. We also implemented an analysis to determine if agroforestry systems support biodiversity in the tropics, using Dung Bettles as a model, we determined that agroforestry production systems are potentially important for maintenance of insect species richness and ecosystem functioning and could be viable alternative conservation systems and biological corridors. Also, by using digitation methods I was able to determine that western Skippers (Hesperiidae) do not follow Bogert’s rule which states that dark coloration in ectotherms becomes beneficial when ambient temperatures are low, allowing faster heating rates and higher body temperatures than in lighter‐colored individuals; instead, their color could be an immune response or crypsis for predator protection. The same digitation methos allowed me to create a workflow for specimens at the UNRMNH that provides a framework for efficient and faster digitization protocols

The landscape ecology of butterflies in traditionally managed Norwegian farmland

The modernisation of agriculture has lead to changes in Norwegian farming landscapes that have consequences for butterfly distribution and abundance. Particularly important is the abandonment of traditionally managed grasslands and the consequent increase in potential barriers of scrub and trees in the landscape. In this thesis I use a landscape ecological perspective to explore the effects of abandonment on butterfly dispersal. I demonstrate that landscape elements influence butterfly movement behaviour: tall structures were significant barriers for a range of species and even low features, such as roads, elicited significant behavioural responses which shaped the movement patterns of butterflies. Behavioural differences between species were related to ecological and physiological characteristics. Movement patterns of Scarce Coppers (Lyceana virgaureae) were recorded by mark-release- recapture (MRR) techniques. Of 1711 recorded displacements, over 90 % were under 150 m. Exchange rates between meadows were dependent upon distance and the structure of intervening vegetation. A simple spatial model, parameterised with data from the behavioural experiments, was validated using MRR observations. This confirmed that the behaviour of individuals responding to single landscape elements has consequences at the level of populations and entire landscapes. The life history and movement behaviour of the endangered Apollo (Parnassius apollo), were examined using MRR. The butterfly is well adapted to a mosaic landscape structure; however, inter-meadow movement declined exponentially with increasing distance between meadows. Abandonment of hay meadows on steep slopes, with consequent forest succession, will adversely affect the Apollo by increasing the distances between open habitat. Genetic analyses support the findings of MMR studies and add a wider spatial and temporal perspective. As a conservation management priority, I recommend population mapping to identify key sites in regional networks of populations. Finally, I consider the links between empirical studies, modelling and the practical application of theory, and discuss the implications of landscape change for the butterflies of Norwegian farmland

Patterns of visual adaptation in tropical mimetic butterflies

Species diversity within an ecosystem can be supported by favouring microhabitat specialisation. In complex habitats, like tropical rainforests, spatial and temporal segregation across microhabitats can expose species to distinct sensory realms. For many animals, visual systems serve as the primary conduit for perceiving biologically relevant sensory information, and the structural and functional variety of eyes and sensory brain regions reflects their critical role in diverse animal behaviours. However, little is known of their role in mediating niche segregation across subtle ecological scales, particularly in terrestrial environments. I explore the role of microhabitat partitioning in driving predictable patterns of adaptive visual system evolution within two diverse radiations of mimetic Neotropical butterfly, the Heliconius and Ithomiini. By taking a comparative approach, I investigate whether dual patterns of habitat divergence and convergence is manifested in the visual system at the perceptual, processing, and molecular level. I find extensive evidence of heritable, habitat-associated visual system variation, particularly for neural processing structures, hinting at the evolutionary lability of these systems to rapidly accommodate local adaptations to visual ecologies. My research also empirically demonstrates, for the first time, how variation in forest structure can give rise to distinct photic environments, highlighting the role of spectral variation as a major driver of adaptive community assemblage within a terrestrial forest radiation. In addition, evidence of visual morphological convergence offers a mechanistic insight into the evolvability of visual adaptations when confronted with similar ecological challenges, shedding light on their significance in promoting ecological diversification and speciation