Landscape change and biodiversity decline is a global problem and has sparked world-wide initiatives promoting biological conservation techniques such as reintroductions, protected area networks, and both preservation and restoration of landscape connectivity. Despite the increasing abundance of such working landscapes (i.e. “human-modified” landscapes), we know relatively little about their ecological mechanics; these landscapes can be vast, encompassing areas too large to obtain high resolution ecological data to test ecological process. To investigate the ecological mechanics of working landscapes, I use a small, tractable, landscape mesocosm situated in east-central Alberta, Canada, The Cooking Lake Moraine (a.k.a. the Beaver Hills Biosphere). The chapters within this dissertation quantify biodiversity across a hierarchy of measurements (from genes to communities) and investigate consistencies in ecological processes generating patterns in these biodiversity measurements across spatial scales. As a result, I investigate both a depth, and breadth, of spatial ecological processes underlying the efficacy of biodiversity conservation techniques in heterogeneous working landscapes. In Chapter I, I explore between-landscape functional connectivity by investigating the genetic contribution of reintroduced individuals to an ostensibly successfully reintroduced population within the mesocosm. I find that contemporary animals are the result of recolonization from adjacent sources rather than putative reintroduction founding individuals, indicating greater mesocosm functional connectivity to adjacent landscapes than previously thought. In Chapter II, I probe within-landscape functional connectivity by quantifying the contribution of protected areas, natural, and anthropogenic landscape features to animal movement across the mesocosm. I find that natural features had the largest effect on animal movements, despite the presence of protected areas. Chapter III investigates protected area network efficacy on biodiversity conservation by quantifying the contribution of protected areas, natural, and anthropogenic landscape features to mammalian functional diversity across multiple spatial scales within the mesocosm. I find that protected areas rarely predict functional diversity across spatial scales; instead natural features positively predict functional diversity at small spatial scales while anthropogenic features are negatively associated with biodiversity at large spatial scales. Finally, Chapter IV ties the previous three chapters together by testing implicit assumptions of the species occurrence data collected in each. I compare GPS collar data (Chapter II) to species occurrence data collected on wildlife cameras (Chapter III) to demonstrate that the magnitude of animal movements better predict species occurrence than the commonly assumed proximity of animal space use. Across chapters, two central themes emerge from this dissertation. First, the importance of natural features at small spatial scales, and anthropogenic features at large spatial scales, within the landscape matrix is predominant in predicting multiple measures of biodiversity. And second, we cannot assume predictable efficacy of conservation strategies or even the ecological process inferred from the data collected to test these strategies. / Graduate

Oaks (Quercus robur) are an important substrate for many epiphytic lichens, and with increasing age the bark of oaks becomes suitable for red-listed species. These species may respond to environmental and landscape factors differently, and at different spatial scales. We tested the effect of tree, environmental and land use factors on the occurrence and richness patterns of lichens species at various spatial scales (circles with radius ranging from 28 to 1225 m), in a heterogeneous landscape in South Eastern Sweden. The occurrence patterns of Cliostomum corrugatum and Chaenotheca phaeocephala were best explained by the density of oaks within radii of 400 and 302 m, respectively. In contrast, Ramalina baltica was best explained at smaller scale (263 m) as was species richness (302 m). This study shows that the most important factor for the occurrence and richness patterns of lichens was oak density at almost all the considered scales. Tree circumference also positively affected all four response variables.

Species conservation initiatives play an important role in ecological studies. Occupancy models have been a useful tool for ecologists to make inference about species distribution and occurrence. Bayesian methodology is a popular framework used to model the relationship between species and environmental variables. In this dissertation we develop a Gibbs sampling method using a logit link function in order to model posterior parameters of the single-season spatial occupancy model. We incorporate the widely used Intrinsic Conditional Autoregressive (ICAR) prior model to specify the spatial random effect in our sampler. We also develop OccuSpytial, a statistical package implementing our Gibbs sampler in the Python programming language. The aim of this study is to highlight the computational efficiency that can be obtained by employing several techniques, which include exploiting the sparsity of the precision matrix of the ICAR model and also making use of Polya-Gamma latent variables to obtain closed form expressions for the posterior conditional distributions of the parameters of interest. An algorithm for efficiently sampling from the posterior conditional distribution of the spatial random effects parameter is also developed and presented. To illustrate the sampler's performance a number of simulation experiments are considered, and the results are compared to those obtained by using a Gibbs sampler incorporating Restricted Spatial Regression (RSR) to specify the spatial random effect. Furthermore, we fit our model to the Helmeted guineafowl (Numida meleagris) dataset obtained from the 2nd South African Bird Atlas Project database in order to obtain a distribution map of the species. We compare our results with those obtained from the RSR variant of our sampler, those obtained by using the stocc statistical package (written using the R programming language), and those obtained from not specifying any spatial information about the sites in the data. It was found that using RSR to specify spatial random effects is both statistically and computationally more efficient that specifying them using ICAR. The OccuSpytial implementations of both ICAR and RSR Gibbs samplers has significantly less runtime compared to other implementations it was compared to.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2018-03-27T19:45:32Z No. of bitstreams: 1 carlosmarianoalvesvalles.pdf: 5972976 bytes, checksum: 908806a8077c5751983d6b9690d566cd (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-04-09T19:22:27Z (GMT) No. of bitstreams: 1 carlosmarianoalvesvalles.pdf: 5972976 bytes, checksum: 908806a8077c5751983d6b9690d566cd (MD5) / Made available in DSpace on 2018-04-09T19:22:27Z (GMT). No. of bitstreams: 1 carlosmarianoalvesvalles.pdf: 5972976 bytes, checksum: 908806a8077c5751983d6b9690d566cd (MD5) Previous issue date: 2018-02-22 / - / Palms are abundant in tropical forests and are recognized as effective bioindicators of hot climates. Moreover, play an important ecological and economic role for local populations. Though palms remain relatively well-conserved, they are under increasing pressure from deforestation. Therefore, endemicity is important for the delimitation of conservation areas. The purposes of the study is 1) to synthesize available information in the literature on species diversity, ecological aspects, use and conservation of Amazon palms (Chapter 1); to analyse palms species richness patterns relative to the latitudinal gradient, sample efforts, and deforestation in the Amazon region (Chapter 2); to compare richness and floristic similarities patterns among the Amazonian sub-regions (Chapter 2); to detect endemic areas for palms in the Amazon region (Chapter 3); and to determine whether the species that define these endemic areas are protected within conservation units (Chapter 3). Records of occurrences were extracted from the Global Biodiversity Information Facility (GBIF). The final dataset consisted of 17,310 records, for 177 species of Amazonian palms. The areas with the greatest richness were in the western, central and northeastern Amazon, principally at latitudes 0–5ºS. Most palms species grow in different habitats, but the highest species richness are found in terra firme forest. Palms are widely used with different category of use according to the regions and species, principally are used for human consumption, elaboration of utensils and tools, and construction of houses. Highest rates of deforestation (>2000 km2) were found in the southern and eastern brazilian Amazon, which coincide with low species richness and gaps in records. Similarity analysis resulted in two groups of sub-regions: the first included the Amazon s.s., Andes and Guiana, and the other group included the Plateau and Gurupi sub-region. The combination of PAE and NDM-VNDM analyses resulted in eight endemic palm areas in western Amazon shared with Andean sub-region. Of the species that define the endemic areas, five are threatened with extinction in one of three IUCN categories (EN, VU, NT), and they are not protected in any conservation units. In conclusion, the western Amazon, besides having high palm richness, also has palm endemic areas, especially, near the Andean sub-region and the Peruvian Amazon, and areas with low species richness, especially those areas with data deficiency, need to be further researched for a better knowledge of their diversity and richness patterns.

In der Dissertation wird untersucht, ob die bereits eingetretenen Änderungen des Klimas und weiterer Standortsfaktoren im Erzgebirge und vorgelagertem Hügelland zu Verlagerungen der Verbreitungsschwerpunkte von Pflanzenarten in ihrer Höhenverbreitung geführt haben. Eine weitere Untersuchungsfrage ist die Begünstigung oder Gefährdung bestimmter Arten infolge der Standortsänderungen. Betrachtet werden 27 Pflanzenarten, sowohl Baum- und Straucharten als auch krautige Pflanzen. Zur Klärung der Fragen werden die Zeiträume 1946 – 1980 und 1981 – 2015 verglichen. Die Auswertung erfolgt auf der Basis von Messtischblatt-Viertelquadranten für die Standortsfaktoren mittlere Meereshöhe, Jahresmitteltemperatur, durchschnittlicher Jahresniederschlag sowie vorherrschender Bodentyp. In der Diskussion werden zusätzlich die Veränderungen in der Land-, Forst- und Jagdwirtschaft sowie die Wirkungen der Immissionsbelastungen und Bodenschutzkalkungen betrachtet. Schwerpunkte umfangreicher statistischer Auswertungen sind die Analyse der Verbreitung in den Untersuchungszeiträumen und die Ermittlung der Wahrscheinlichkeit von Artvorkommen. Eine gesonderte Fragestellung ist die genetische Untersuchung von Prunus padus. Dazu wurden Vorkommen im Tief-, Hügel- und Bergland ausgewählt. Der bisherige Anstieg der Jahresmitteltemperaturen hat nicht grundsätzlich zu einer Verschiebung der Verbreitungsschwerpunkte in höhere Gebirgslagen geführt. Die Pflanzenarten können hinsichtlich ihrer Verbreitung sowie im Vergleich der Untersuchungsperioden in Gruppen geordnet werden. Bei einigen Pflanzenarten, die in höhere Lagen des Untersuchungsgebietes vordringen, fällt eine enge Bindung der Vorkommenswahrscheinlichkeit an den Faktor Jahresmitteltemperatur auf. Andererseits werden bislang submontan bis montan verbreitete Arten nicht generell in die Hochlagen zurückgedrängt. Die Wirkungen der Klimaänderung können deshalb nicht losgelöst von anderen Faktoren beurteilt werden.

In der Dissertation wird untersucht, ob die bereits eingetretenen Änderungen des Klimas und weiterer Standortsfaktoren im Erzgebirge und vorgelagertem Hügelland zu Verlagerungen der Verbreitungsschwerpunkte von Pflanzenarten in ihrer Höhenverbreitung geführt haben. Eine weitere Untersuchungsfrage ist die Begünstigung oder Gefährdung bestimmter Arten infolge der Standortsänderungen. Betrachtet werden 27 Pflanzenarten, sowohl Baum- und Straucharten als auch krautige Pflanzen. Zur Klärung der Fragen werden die Zeiträume 1946 – 1980 und 1981 – 2015 verglichen. Die Auswertung erfolgt auf der Basis von Messtischblatt-Viertelquadranten für die Standortsfaktoren mittlere Meereshöhe, Jahresmitteltemperatur, durchschnittlicher Jahresniederschlag sowie vorherrschender Bodentyp. In der Diskussion werden zusätzlich die Veränderungen in der Land-, Forst- und Jagdwirtschaft sowie die Wirkungen der Immissionsbelastungen und Bodenschutzkalkungen betrachtet. Schwerpunkte umfangreicher statistischer Auswertungen sind die Analyse der Verbreitung in den Untersuchungszeiträumen und die Ermittlung der Wahrscheinlichkeit von Artvorkommen. Eine gesonderte Fragestellung ist die genetische Untersuchung von Prunus padus. Dazu wurden Vorkommen im Tief-, Hügel- und Bergland ausgewählt. Der bisherige Anstieg der Jahresmitteltemperaturen hat nicht grundsätzlich zu einer Verschiebung der Verbreitungsschwerpunkte in höhere Gebirgslagen geführt. Die Pflanzenarten können hinsichtlich ihrer Verbreitung sowie im Vergleich der Untersuchungsperioden in Gruppen geordnet werden. Bei einigen Pflanzenarten, die in höhere Lagen des Untersuchungsgebietes vordringen, fällt eine enge Bindung der Vorkommenswahrscheinlichkeit an den Faktor Jahresmitteltemperatur auf. Andererseits werden bislang submontan bis montan verbreitete Arten nicht generell in die Hochlagen zurückgedrängt. Die Wirkungen der Klimaänderung können deshalb nicht losgelöst von anderen Faktoren beurteilt werden.