This thesis explores some important practical considerations concerning the use of species distribution models in marine conservation planning. Using geo-referenced gorgonian distribution data, together with explanatory environmental variables, predictive models have been used to map the spatial distribution of suitable gorgonian (sea fan) habitat in two study sites; Hatton Bank, in the Northeast Atlantic, and Lyme Bay on the south coast of Devon. Generalized Linear Models (GLMs), Generalized Additive Models (GAMs) and a Maximum Entropy (Maxent) model have been used to support critical investigation into important model considerations that have received inadequate attention in the marine environment. The influence of environmental data resolution on model performance has been explored with specific reference to available datasets in the nearshore and offshore environments. The transferability of deep-sea models has been similarly appraised, with recommendations as to the appropriate use of transferred models. Investigating these practical issues will allow managers to make informed decisions with respect to the best and most appropriate use of existing data. This study has also used novel approaches and investigated their suitability for marine conservation planning, including the use of model classification error in the spatial prioritisation of monitoring sites, and the adaptation of an existing presence-only modelling method to include absence data. Together, these studies contribute both practical recommendations for marine conservation planning and novel applications within the wider species distribution modelling discipline, and consider the implications of these developments for managers, to ensure the ongoing improvement and development of models to support conservation planning.

Ecological patterns and processes influence ecosystem function at scales from nanometres to global scales depending on the organisms involved. Predicting the presence and abundance of species, at scales appropriate to the organisms and the underlying processes, is central to ecology. Models of species’ distributions can provide important insights into pattern-process-scale relationships including the relative importance of various environmental factors and their interactions that influence habitat selection at the individual and population levels. Mapping current and potential distributions informs the conservation of threatened species by providing spatial information on where a species is likely to occur and the identification of habitat elements and their spatial configurations which influence occupancy and persistence. The aim of this thesis was to incorporate the principles of pattern, process and scale in the identification of habitat associations for threatened species within a species’ distribution modelling framework. Accurate modelling of species’ distributions depends on robust sampling designs, reliable data input and appropriate statistical methodologies that align with the ecological model. I applied a range of innovative statistical methods to various sources of data to identify important habitat associations for a threatened species at different scales and tested the discriminative ability of the resultant models. I integrated the results from extensive field sampling and expert elicitation to build connectivity networks using graph theory algorithms to identify important conservation priorities for threatened species. The threatened brush-tailed rock-wallaby (Petrogale penicillata) was chosen as a suitable study species for quantifying habitat relationships at multiple spatial scales using species’ distribution modelling. The distribution of brush-tailed rock-wallabies is restricted to a set of suitable habitat characteristics related to rocky terrain supporting cliffs and boulder piles that occur infrequently across a landscape. At the site scale, they require suitable resting and refuge sites provided by rocky habitats, while at a landscape scale their dispersal is dependent on the connectivity of suitable habitats. The species is listed as threatened throughout eastern Australia and endangered in some states. Information about its current distribution and occupancy status is essential to support habitat conservation and threat management. The first chapter provides a broad view of the literature on modelling of species’ distributions and the thesis aims and structure. In chapter 2, I assess the ecological scale relevant to habitat modelling for the brush-tailed rock-wallaby. In chapter 3 I test whether habitat models from one region can be extrapolated to neighbouring regions. I use a novel approach and elicitation tool in chapter 4 to collect expert knowledge and assess it with a comprehensive set of field data in a Bayesian framework. In chapter 5 I assess whether landscape connectivity is a determinant of site occupancy by using graph theory algorithms to identify important habitat patches and dispersal pathways for rock-wallaby movement in fragmented landscapes. The final chapter synthesises the individual chapters’ findings within the context of species’ distribution modelling. Management implications are discussed for the conservation of the brush-tailed rock-wallaby and its habitat network. Wider implications are also suggested for other rock-wallaby species and species living in similar environments. The results of the thesis showed the habitat of the brush-tailed rock-wallaby was affected by site-scale and landscape-scale factors, supporting the need for a multi-scale approach when investigating species-environment associations. I found that models performed well within a region at both scales. Extrapolating the models to neighbouring regions resulted in good predictive performance at the site scale but substantially poorer predictive performance at the landscape scale. When there is insufficient field data to build robust data models, management bodies would benefit from incorporating expert knowledge. The study demonstrates the potential errors in using experts with knowledge gained from outside the area of interest. Finally, I highlight the importance of accounting for the landscape connectivity between patches from the perspective of the individual animal. Least cost analysis, using graph theory algorithms, provides a cost-efficient and effective framework for identifying landscape connectivity patterns and key paths and patches to help inform suitable land management strategies for conservation of threatened species. There is much pressure from conservation and management agencies to produce models of species’ distributions that could be potentially be used in other regions or with similar species. The thesis combines ecological theory with rigorous statistical methodology to test different modelling techniques for species distribution modelling. It demonstrates how a combination of expert knowledge, extensive field data and landscape connectivity measures successfully predicts ecological relationships at a number of scales. Species’ distribution models can benefit from applying a robust sampling design and suitable modelling techniques to various data sources to generate ecologically-based information to improve our understanding of species-habitat associations and provide a reliable component to incorporate into conservation planning. This thesis therefore provides important advances to spatial ecology and ecological modelling of species distributions and management of threatened species.

Meadows are critical in arid and semi-arid Argentinean Patagonia because of their importance for regional biodiversity. Despite this, little information on the spatial distribution of meadows is available and no analysis of the potential effect of climate change on meadows has been performed, which hampers conservation planning. In this study, I modeled the spatial distribution of meadows and investigated how climate change may affect the current distribution of meadows in arid and semiarid Patagonia by 2050. In addition, I investigated conservation status and areas of desertification vulnerability of those areas predicted to contain meadows. I used high-resolution imagery available in Google Earth software to visually estimate presence and absence of meadows. To model current and future distribution of meadows I used these observations and different socio-environmental predictor variables. I implemented generalized linear, additive, boosting, and random forest models, as the basis for a mean ensemble technique. I predicted future distribution of meadows using four different general circulation models and the A2 SERES scenario. The final ensemble model was an accurate representation of the current distribution of meadows in Patagonia and indicates they are severely under-represented within protected areas. I determined that overall meadow abundance is going to decrease by 2050 given the changes in climate. However, there were two contrasting trends: severe reduction of meadows in northwest Patagonia and Tierra del Fuego Island, and an expansion of suitable areas for meadows in the south and a small section in the northwest. This first regional map of meadow distribution across Argentinean Patagonia and information on meadows vulnerability to climate change represent key information for planning actions to conserve this critical habitat.

Speciation can be understood as a continuum occurring at different levels, from population to species. The recent molecular revolution in population genetics has opened a pathway towards understanding species evolution. At the same time, speciation patterns can be better explained by incorporating a geographic context, through the use of geographic information systems (GIS). Phaedranassa (Amaryllidaceae) is a genus restricted to one of the world’s most biodiverse hotspots, the Northern Andes. I studied seven Phaedranassa species from Ecuador. Six of these species are endemic to the country. The topographic complexity of the Andes, which creates local microhabitats ranging from moist slopes to dry valleys, might explain the patterns of Phaedranassa species differentiation. With a Bayesian individual assignment approach, I assessed the genetic structure of the genus throughout Ecuador using twelve microsatellite loci. I also used bioclimatic variables and species geographic coordinates under a Maximum Entropy algorithm to generate distribution models of the species. My results show that Phaedranassa species are genetically well-differentiated. Furthermore, with the exception of two species, all Phaedranassa showed non-overlapping distributions. Phaedranassa viridiflora and P. glauciflora were the only species in which the model predicted a broad species distribution, but genetic evidence indicates that these findings are likely an artifact of species delimitation issues. Both genetic differentiation and non-overlapping geographic distribution suggest that allopatric divergence could be the general model of genetic differentiation. Evidence of sympatric speciation was found in two geographically and genetically distinct groups of P. viridiflora. Additionally, I report the first register of natural hybridization for the genus. The findings of this research show that the genetic differentiation of species in an intricate landscape as the Andes does not necessarily show a unique trend. Although allopatric speciation is the most common form of speciation, I found evidence of sympatric speciation and hybridization. These results show that the processes of speciation in the Andes have followed several pathways. The mixture of these processes contributes to the high biodiversity of the region

Climate change is an important contributor to the modification of many bumblebee species’ range boundaries. It was linked to widespread decline at the southern edge of their distribution and to their inability to colonize new areas at the northern edge. Additionally, bumblebee decline is aggravated by other anthropogenic threats like land use change, agricultural practices and pathogen spillover. Predicted consequences are numerous, and could lead to severe economic and ecological impacts on human populations. A species-specific assessment of potential climate change impacts on North American bumblebees, based on the most recent global change scenarios as used in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), was done for the first time. Using a massive dataset of georeferenced bumblebee observations and general circulation models, a series of species distribution models explore the impact of different climate change scenarios on climatically suitable areas of 30 bumblebee species. Northward range shifts occur in most bumblebee species’ projected climatic niches, revealing potential hotspots – places projected to be climatically suitable to multiple species – under future climate scenarios. Areas where species are likely to be lost in the absence of intervention are substantial, particularly in eastern parts of the continent. Models showed significant contractions of current ranges even under the very optimistic scenario in which all species disperse at 10 km/year. Results indicate that managed relocation as well as habitat management should be considered as a conservation strategy for some species. This research serves as a foundation for broader discussion and research in a nascent research area. It may assist in establishing localities where first conservation efforts could be directed for vulnerable bumblebee species.

Invasive plant species are an increasing global threat to native biodiversity. Effective management depends on accurate predictions of their spread. However, modelling the geographic distribution of invasive species, particularly with methods like correlative species distribution models (SDMs), is challenging. SDMs operate under the assumption that species are in equilibrium with their environment (i.e., they occur in all suitable environments); this assumption is more likely to be violated for a species that is still in the process of colonizing suitable environments. SDMs also assume that environmental constraints are the most important factors determining a species' distribution. However, these assumptions are not commonly assessed, and when violated can have consequences for model reliability. I investigated SDM performance and equilibrium in the invasive Vincetoxicum rossicum vine in northeastern North America. Vincetoxicum rossicum has a long, detailed history of occurrence records in its invaded range, which enabled me to observe trends in equilibrium and model performance over a relatively long time scale. I tested the hypotheses that: 1) invasive species approach equilibrium in environmental and geographic space over time; 2) SDM performance will increase as V. rossicum approaches environmental equilibrium; and 3) range expansion in the early stages of an invasion is primarily a function of dispersal rather than environmental constraints, while the reverse is true in later stages. I found that V. rossicum has reached equilibrium in environmental space, but is still expanding its geographic range. SDM performance was poor in the first 30 years following introduction, but then improved as V. rossicum approached environmental equilibrium. SDMs were outperformed by spatial dispersal models in the earliest time period, however, the reverse was true for all subsequent time periods. Overall, these results suggest that V. rossicum’s distribution is becoming more stable and more predictable over time and that models built using the most recent data for this species, will be the most transferable across time and space. Additionally, my findings highlight the need for researchers modelling invasive species’ distributions to consider the inherent assumptions, biases, and unique features related to SDMs and SDMs of invasive species.

Studies of the occurrence of montane and boreomontane species in ravines of the sandstone landscape are scarce and the occurrence of these species are explained by the presence of temperature inversion. The question is, which factors limit the occurrence ofthese species in ravines with temperature inversion. The aim of this diploma thesis is to reveal factors that influence the occurrence of Huperzia selago in inverse ravines of sandstone landscape. This work uses a habitat variables recorded directly for populations of H. selago and variables derived from a digital elevation model. These derived variables are also used for creation of two predictive models of geographic distribution of H. selago in the National Park Bohemian Switzerland. When we summarize the most informative variables of predictive models and habitat conditions significantly different from control sites, we get the typical habitat of H. selago. Such sites will likely be found on the rock at the bottom of the valley. Factors that influence the suitability of habitat are: moisture, vegetation type, slope, and distance to the bottom of the valley.

A relação entre a paisagem e a distribuição da ocorrência e abundância das espécies no espaço é uma das questões centrais em ecologia, com importantes aplicações diretas em tempos de intenso uso da terra e mudanças climáticas por atividades humanas. Contudo, para inferirmos sobre essas relações, temos que descrever a paisagem da forma mais próxima possível de como as espécies realmente a percebem. Uma paisagem pode ser descrita em diferentes níveis hierárquicos de organização do ambiente (e.g. quantidade de um mineral no solo, número de plantas em uma parcela, área de cobertura de floresta...), e cada nível pode ser descrito em diferentes escalas (resolução e extensão de descrição). Os níveis e escalas com maior poder de previsão da ocorrência/abundância de uma espécie são chamados de nível de efeito e escala (extensão) de efeito. Nesta tese, utilizo armadilhas fotográficas e modelos hierárquicos para avaliar relações entre a paisagem e espécies de mamíferos e aves. Meus objetivos são: (1) avaliar se existe relação entre nível e extensão de efeito para prever a abundância de espécies e a área de vida ou massa das mesmas; (2) investigar características do solo que possam ser determinantes da distribuição de mamíferos e aves que consumem solo (geofagia); e (3) a partir de ralações espécie-paisagem, estimar a distribuição da densidade de uma espécie, o veado-catingueiro, para diferentes datas. Não há suporte para que a área de vida ou a massa de uma espécie sejam relevantes para o nível ou extensão em que uma paisagem deva ser descrita a fim de prever a abundância de uma espécie. Isso implica na importância de se avaliar diferentes níveis e extensões de uma paisagem quando na busca por relações espécie-paisagem. Fatores locais, como a argila ou minerais do solo, podem ser importantes para algumas espécies. Descobri que o veado-mateiro e o caititu selecionam solos para consumo com base na quantidade e tipo de argila. O caititu também seleciona solos com base na concentração de microminerais, assim como a juriti-azul, a arara-azul-grande, o mutum, o aracuã e a pomba-galega. Uma descrição da paisagem em nível de composição do solo pode ser relevante para avaliar a distribuição destas e outras espécies. Relações espécie-paisagem podem ser usadas para prever a abundância de espécies no espaço. Estimei a densidade do veado-catingueiro em 1992 (2,07 ind/km2) e em 2011 (7,31 ind/km2), para uma região de pecuária extensiva no nordeste do Pantanal onde foi criada uma reserva em 1997. A densidade desta espécie aumentou 3,5 vezes entre 1992 e 2011, com o fim da pecuária no local. Investigações multinível e multiescala de relações espécie-paisagem ainda são incipientes, embora importantes aplicações destas relações já venham sendo feitas há décadas. / The relationship between the landscape and the distribution of species’ occurrence and abundance is one of the main questions in ecology, with important applications for the current period of intense land use and climate change. However, to infer about these relationships, we have to describe the landscape as closely as possible to how species actually realize it. We can describe landscapes at different hierarchical levels of the environment (e.g. mineral amount in soil, number of plants in a plot, forest cover area…), and each level can be described at different scales (resolution and extent). The best levels and scales to predict species’ occurrence/abundance are known as level of effect and scale (extent) of effect. In this PhD thesis, I use camera traps and hierarchical models to assess relationships between the landscape and mammals or birds. My goals are: (1) to evaluate possible relationships between the level and extent of effect to predict species’ abundance and species’ home range or mass; (2) to investigate soil features important to the distribution of mammals and birds engaged on geophagy (soil consumption); and (3) from species-landscape relations, to estimate the density of a species, the Gray Brocket in space for different dates. There is no support for species’ home range or mass as relevant traits related to the level and scale that a landscape should be described in order to predict species’ abundance. This highlight the importance of evaluating different levels and scales of a landscape when searching for species-landscape relationships. Local factors such as clay or minerals may be important for some species. I found that the Red Brocket and Collared Peccary select soils for consumption based on clay amount and type. The Collared Peccary also selects soil based on the concentration of trace minerals, as well as Blue Ground-dove, Hyacinth Macaw, Bare-faced Curassow, Chaco Chachalaca, and Pale-vented Pigeon. Describing the landscape at soil composition level may be important to evaluate the distribution of these and another species. Species-landscape relationships can be used to predict the abundance of species in space at different dates. I estimated the density of the Gray Brocket in 1992 (2.07 ind/km2) and 2011 (7.31 ind/km2), in a livestock region in northeastern Brazilian Pantanal where a reserve was established in 1997. Gray Brocket density increased 3.5 times between 1992 and 2011, after livestock ban. Multi-level and multi-scale approaches to investigate species-landscape relationships are still emerging, though important applications of such relationships have been done for decades.

Several aspects of plant-pollinator interactions are presented in the thesis. It contains a review on the open questions of plant-pollinator interactions from single species to complex networks. The following sections document novel results. Firstly, the conservation of complex pollination networks is addressed through the hierarchy of species' importance. In addition, the habitat requirements and interactions of a threatened rare pollinator species are explored. In the following chapters, the results from manipulative approaches applied in the field to plant-pollinator interactions are presented. The effect of pollinator's population decline on pollinators' foraging for pollen is investigated. Moreover, the way plant species loss impact several aspects of pollinator visitation is presented. Lastly, the impact of species removal on plant-pollinator network topology and on species ability of establishing new interactions is investigated.

Invasive plant species impact ecosystems by altering native plant community composition and modifying ecosystem properties such as fire and nutrient cycles. We used species distribution models to address both theoretical and applied questions regarding invasive plants in an ecosystem particularly vulnerable to invasion, riparian areas. In our first study, we asked whether a native species is closer to equilibrium than a functionally similar invasive species and determined drivers of invasion for an aggressive invader of riparian areas, Phalaris arundinacea (reed canarygrass). We modeled the presence of P. arundinacea and a comparable native species using four techniques and compared model fit between species and between models with and without dispersal processes incorporated. Non-dispersal model fit for our invasive species was lower than for the native species and improvement in fit with the addition of the dispersal constraint was greater for the invasive species than the native species. These results provide evidence that invasive species are further from equilibrium than native species and suggest that dispersal processes should be considered when modeling invasive species. In our second study, we addressed whether there was a set of site traits that make some sites more prone to invasion by non-native plants than others. We used Random Forests to individually model the presence of 11 invasive plant species that are designated as noxious weeds in our study area. We used model results to identify general patterns of invasion and to provide management recommendations for the study area. We found that a particular site type was more likely to be invaded by the majority of study species: hot, dry sites with high grass or shrub cover near roads with high nutrient levels and high stream baseflow values. Management recommendations to combat invasion by P. arundinacea in particular and invasive species in general are the same: limiting species’ spread along roads, lowering site nutrient levels, and anticipating increased spread with climate change.