Aim To understand how the integration of contextual spatial data on land cover and human infrastructure can help reduce spatial bias in sampling effort, and improve the utilization of citizen science‐based species recording schemes. By comparing four different citizen science projects, we explore how the sampling design's complexity affects the role of these spatial biases. Location Denmark, Europe. Methods We used a point process model to estimate the effect of land cover and human infrastructure on the intensity of observations from four different citizen science species recording schemes. We then use these results to predict areas of under‐ and oversampling as well as relative biodiversity ‘hotspots’ and ‘deserts’, accounting for common spatial biases introduced in unstructured sampling designs. Results We demonstrate that the explanatory power of spatial biases such as infrastructure and human population density increased as the complexity of the sampling schemes decreased. Despite a low absolute sampling effort in agricultural landscapes, these areas still appeared oversampled compared to the observed species richness. Conversely, forests and grassland appeared undersampled despite higher absolute sampling efforts. We also present a novel and effective analytical approach to address spatial biases in unstructured sampling schemes and a new way to address such biases, when more structured sampling is not an option. Main conclusions We show that citizen science datasets, which rely on untrained amateurs, are more heavily prone to spatial biases from infrastructure and human population density. Objectives and protocols of mass‐participating projects should thus be designed with this in mind. Our results suggest that, where contextual data is available, modelling the intensity of individual observation can help understand and quantify how spatial biases affect the observed biological patterns.

The theoretical underpinnings of the assessment of invasive alien species impacts need to be improved. At present most approaches are unreliable to quantify impact at regional scales and do not allow for comparison of different invasive species. There are four basic problems that need to be addressed: (1) Some impacted ecosystem traits are spatially not additive; (2) invader effects may increase non-linearly with abundance or there may be effect thresholds impairing estimates of linear impact models; (3) the abundance and impact of alien species will often co-vary with environmental variation; and (4) the total invaded range is an inappropriate measure for quantifying regional impact because the habitat area available for invasion can vary markedly among invasive species. Mathematical models and empirical data using an invasive alien plant species (Heracleum mantegazzianum) indicate that ignoring these issues leads to impact estimates almost an order of magnitude from the real values. Thus, we propose a habitatsensitive formula for regional impact assessment that is unaffected by non-linearity. Furthermore, we make some statistical suggestions on how to assess invader effects properly and we discuss the quantification of the invaded range. These improvements are crucial for impact assessment with the overall aim of prioritizing management of invasive species.

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BackgroundHaemostatic alterations are commonly detected in human and canine cancer patients. Previous studies have described haemostatic dysfunction in canine patients with haemangiosarcomas and carcinomas, and haemostasis has been assessed in dogs with various malignant and benign neoplasias. Few studies have addressed the effect of cancer type and progression of disease on the presence of haemostatic alterations in canine patients. The objective of the present study was to evaluate haemostatic variables of coagulation and fibrinolysis in a group of canine cancer patients, and to compare haemostatic changes to the cancer type and progression of disease.MethodsThe study population consisted of 71 dogs with malignant neoplasia presented to the University Hospital for Companion Animals, Faculty of Life Sciences, University of Copenhagen, Denmark. The study was designed as a prospective observational study evaluating the haemostatic function in canine cancer patients stratified according to type of cancer disease and disease progression. The coagulation response was evaluated by thromboelastrography (TEG), platelet count, activated partial thromboplastin time (aPTT), prothombin time (PT), fibrinogen and antithrombin (AT); and fibrinolysis by d-dimer and plasminogen.ResultsHypercoagulability was the most common haemostatic dysfunction found. Non mammary carcinomas had increased clot strength (TEG G), aPTT and fibrinogen compared to the other groups. When stratifying the patients according to disease progression dogs with distant metastatic disease exhibited significantly increased fibrinogen, and d-dimer compared to dogs with local invasive and local non-invasive cancers.ConclusionHypercoagulability was confirmed as the most common haemostatic abnormality in canine cancer patients and haemostatic dysfunction in canine cancer patients was found related to the cancer type and progression of disease. Increase in TEG G, aPTT and fibrinogen were observed in non-mammary carcinomas and were speculated to overall represent a proinflammatory response associated with the disease. Dogs with distant metastatic disease exhibited increased fibrinogen and d-dimer. Future studies are needed to elucidate the clinical importance of these results.

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Prenatal malnutrition differentially programmed glucose-lactate metabolic pathways and cholesterol homeostasis. Prenatal overnutrition predisposed for hyperglycaemia and hyperlactataemia, whereas undernutrition predisposed for hypercholesterolaemia upon exposure to an obesogenic diet. Prenatal overnutrition (not undernutrition) interfered with pancreatic insulin secretion by non-glucose-dependent mechanisms.

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