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Contains fulltext : 292309.pdf (Publisher’s version ) (Open Access) Macroecological research has grown rapidly over the last few decades, investing most of its efforts on describing patterns of biodiversity and human-induced threats using correlative- based approaches. Although correlative studies have provided important insights, they are unable to discern correlations from causal relationships. This limits our ability to generate reliable projections outside the spatio-temporal and taxonomic domains of the input data. In contrast, process-based models attempt to replicate the dynamics of a system, modeling directly its underlying mechanisms. As such, process-based methods have the potential to provide more reliable predictions under novel conditions. Despite recent advancements in ecological theory, increases in data availability and the growth of computational power, it remains a significant challenge to construct and further develop process-based ecosystem models that are widely applicable to different questions and ecological contexts. The main aim of this thesis was to develop and apply processed-based ecological models to better understand and improve their functioning, expand current ecological theory as well as increase the support of process-based modeling. To increase the accessibility and reproducibility of the Madingley model, I developed a user-friendly and transparent R interface called MadingleyR. I also assessed the applicability of General Ecosystem Models (GEMs), in particular the Madingley model, for interpreting ecological hypotheses as well as exploring conservation scenarios. In this context, I investigated the roles large-bodied mammals in regulating the trophic structure and maintaining ecosystem functioning. Considering the limitations that follow from the global-scale scope of the Madingley model, I developed and validated a new GEM, focusing on landscape-level simulations, though the integration of species identity, species-specific interactions and animal movement. Radboud University, 03 mei 2023 Promotor : Huijbregts, M.A.J. Co-promotores : Santini, L., Tucker, A.

Contains fulltext : 287548.pdf (Publisher’s version ) (Open Access) Motivation: Home range is a common measure of animal space use as it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of animal space use. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has been historically biased toward terrestrial mammals. The use of aggregated numbers and terrestrial focus limits our ability to examine home range patterns across different environments, variation in time and between different levels of organisation. Here we introduce HomeRange, a global database with 75,611 home-range values across 960 different mammal species, including terrestrial, as well as aquatic and aerial species. Main types of variable contained: The dataset contains mammal home-range estimates, species names, methodological information on data collection, home-range estimation method, period of data collection, study coordinates and name of location, as well as species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit. Spatial location and grain: The collected data is distributed globally. Across studies, the spatial accuracy varies, with the coarsest resolution being 1 degree. Time period and grain: The data represent information published between 1939 and 2022. Across studies, the temporal accuracy varies, some studies report start and end dates specific to the day. For other studies, only the month or year is reported. Major taxa and level of measurement: Mammal species from 24 of the 27 different taxonomic orders. Home-range estimates range from individual-level values to population-level averages. Methods Mammalian home range papers were compiled via an extensive literature search. All home range values were extracted from the literature including individual, group and population-level home range values. Associated values were also compiled including species names, methodological information on data collection, home-range estimation method, period of data collection, study coordinates and name of location, as well as species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit. Here we include the database, associated metadata and reference list of all sources from which home range data was extracted from. We also provide an R package, which can be installed from https://github.com/SHoeks/HomeRange. The HomeRange R package provides functions for downloading the latest version of the HomeRange database and loading it as a standard dataframe into R, plotting several statistics of the database and finally attaching species traits (e.g. species average body mass, trophic level) from the COMBINE (Soria et al. 2021) for statistical analysis. 09 januari 2023

Contains fulltext : 250448.pdf (Publisher’s version ) (Open Access)

Additional file 2. Description of outcome scales used in the study.

Additional file 1. Supporting tables and figures.

Additional file 3. Formula and rationale behind the rankability.

Introdução: O tratamento endovascular representa o método de eleição para o tratamento de Aneurismas da Aorta Abdominal (AAA). Existem endopróteses disponíveis com diâmetros do colo proximal até 36mm, que permitem o tratamento de colos proximais até 32 mm. Contudo, a existência de colos largos representa um conhecido preditor de complicações. O objetivo deste estudo é avaliar os resultados a médio-prazo de doentes que requereram endopróteses de 34-36mm. Métodos: Foi realizada uma análise retrospetiva de uma base de dados prospetiva, incluindo todos os pacientes submetidos a EVAR por AAA degenerativo numa instituição terciária na Holanda. Todas as medições foram realizadas em reconstruções center-lumen line em software dedicado. Os pacientes foram classificados como “diâmetro largo” (LD), se a endoprótese implantada tivesse diâmetro superior a 32 mm.. Os restantes pacientes foram classificados como diâmetro normal (ND). O endpoint primário foi complicações relacionadas com o colo (combinação de endoleak tipo IA, migração>5mm ou qualquer intervenção no colo proximal). Alterações morfológicas no colo e sobrevida foram também analisadas. Diferenças entre grupos foram ajustadas por regressão multivariável. Resultados: O estudo incluiu 502 pacientes (90 no grupo LD e 412 no grupo ND). O follow-up mediano foi de 3.5 anos IQR (1.5–6.2) e 4.5 anos IQR (2.1–7.3) para os grupos LD e ND, respetivamente, P=.008. Relativamente às características basais, os doentes no grupo LD, apresentavam maior incidência de hipertensão arterial (83% vs 69.7%, P=.012) e tabagismo (86% vs 84.1%, P=.018). Além de colos mais largos (colo Proximal Ø > 28 mm: 75% vs 3.3%, P45º: 21% vs 9%, P=.002), cónicos (39.8% vs 20.3%, P25%: 42% vs 32.3%, P5 mm ocorreu similarmente entre grupos (7.8% vs 5.1%, P=.32). Reintervenções relacionadas com colo o foram também mais frequentes no grupo LD (13.3% vs 8.7%, P=.027). info:eu-repo/semantics/publishedVersion

OBJECTIVE: To determine if mid-term outcome following endovascular aneurysm repair (EVAR) with the Endurant Stent Graft (Medtronic, Santa Rosa, CA, USA) is influenced by severe proximal neck angulation. METHODS: A retrospective case-control study was performed using data from a prospective multicenter database. All measurements were obtained using dedicated reconstruction software and center-lumen line reconstruction. Patients with neck length >15 mm, infrarenal angle (β) >75°, and/or suprarenal angle (α) >60°, or neck length >10 mm with β >60°, and/or α >45° were compared with a matched control group. Primary endpoint was primary clinical success. Secondary endpoints were freedom from rupture, type 1A endoleak, stent fractures, freedom from neck-related reinterventions, and aneurysm-related adverse events. Morphological neck variation over time was also assessed. RESULTS: Forty-five patients were included in the study group and were compared with a matched control group with 65 patients. Median follow-up time was 49.5 months (range 30.5-58.4). The 4-year primary clinical success estimates were 83% and 80% for the angulated and nonangulated groups (p = .42). Proximal neck angulation did not affect primary clinical success in a multivariate model (hazard ratio 1.56, 95% confidence interval 0.55-4.41). Groups did not differ significantly in regard to freedom from rupture (p = .79), freedom from type 1A endoleak (p = .79), freedom from neck-related adverse events (p = .68), and neck-related reinterventions (p = .68). Neck angle reduction was more pronounced in patients with severe proximal neck angulation (mean Δα -15.6°, mean Δβ -30.6°) than in the control group (mean Δα -0.39°, mean Δβ -5.9°) (p < .001). CONCLUSION: Mid-term outcomes following EVAR with the Endurant Stent Graft were not influenced by severe proximal neck angulation in our population. Despite the conformability of the device, moderate aortic neck remodeling was identified in the group of patients with angulated neck anatomy on the first computed tomography scan after implantation with no important further remodeling afterwards. No device integrity failures were encountered.