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Context Cities are a challenging habitat for obligate nocturnal mammals because of the ubiquitous use of artificial light at night (ALAN). How nocturnal animals move in an urban landscape, particularly in response to ALAN is largely unknown. Objectives We studied the movement responses, foraging and commuting, of common noctules (Nyctalus noctula) to urban landscape features in general and ALAN in particular. Methods We equipped 20 bats with miniaturized GPS loggers in the Berlin metropolitan area and related spatial positions of bats to anthropogenic and natural landscape features and levels of ALAN. Results Common noctules foraged close to ALAN only next to bodies of water or well vegetated areas, probably to exploit swarms of insects lured by street lights. In contrast, they avoided illuminated roads, irrespective of vegetation cover nearby. Predictive maps identified most of the metropolitan area as non-favoured by this species because of high levels of impervious surfaces and ALAN. Dark corridors were used by common noctules for commuting and thus likely improved the permeability of the city landscape. Conclusions We conclude that the spatial use of common noctules, previously considered to be more tolerant to light than other bats, is largely constrained by ALAN. Our study is the first individual-based GPS tracking study to show sensitive responses of nocturnal wildlife to light pollution. Approaches to protect urban biodiversity need to include ALAN to safeguard the larger network of dark habitats for bats and other nocturnal species in cities.
Color matters
(2018)
Concerning standardization of laboratory animal husbandry, only exiguous changes of habitat can potentially influence animal physiology or results of behavioral tests. Routinely, mice chow is dyed when different types of diets are dispensed. Given the fact that the dye itself has no effects on food odor or flavor, we wanted to test the hypothesis that the color of chow has an impact on food uptake in mice. Twelve-week-old male mice of different strains (C57BL/6J, DBA/2J, C3H/HeJ, BALB/cJ; n = 12/strain) were single-housed in PhenoMaster (R) cages. After acclimatization standard mice chow in different colors was administered. Food intake was monitored as a two-alternative choice test of different color combinations. All animals had an average food intake of 3 g/d and no preferences were observed when a combination of identically colored food was offered. Preference tests yielded significant aversion to blue food and significant attraction to yellow and green food in C57BL/6 and DBA/2J mice. In C3H/HeJ and BALB/cJ mice no color-related pattern occurred. Selected mice strains have known differences concerning functionality of their visual sense. C57BL/6 and DBA/2 mice are considered to be normal sighted at testing age, BALB/c is representative for albino strains and C3H mice carry mutations resulting in retinal alterations. Results suggesting that normal-sighted mice would be selective concerning food color when given the choice. Nevertheless, this does not influence overall quantity of food intake when animals were provided solely with food colored with a single dye. Moreover, visually impaired mice showed no color-related food preferences.
This case report addresses the problem of underreporting negative results and adverse side effects in animal testing. We present our findings regarding a hyperphagic mouse model associated with unforeseen high mortality. The results outline the necessity of reporting detailed information in the literature to avoid duplication. Obese mouse models are essential in the study of obesity, metabolic syndrome and diabetes mellitus. An experimental model of obesity can be induced by the administration of gold thioglucose (GTG). After transcending the blood-brain barrier, the GTG molecule interacts with regions of the ventromedial hypothalamus, thereby primarily targeting glucose-sensitive neurons. When these neurons are impaired, mice become insensitive to the satiety effects of glucose and develop hyperphagia. In a pilot study for optimising dosage and body weight development, C57BL/6 mice were treated with GTG (0.5 mg/g body weight) or saline, respectively. Animals were provided a physiological amount of standard diet (5 g per animal) for the first 24 hours after treatment to prevent gastric dilatation. Within 24 hours after GTG injection, all GTG-treated animals died of gastric overload and subsequent circulatory shock. Animals developed severe attacks of hyperphagia, and as the amount of provided chow was restricted, mice exhibited unforeseen pica and ingested bedding material. These observations strongly suggest that restricted feeding is contraindicated concerning GTG application. Presumably, the impulse of excessive food intake was a strong driving force. Therefore, the actual degree of suffering in the GTG-induced model of hyperphagia should be revised from moderate to severe.
Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are hepatic manifestations of the metabolic syndrome. Many currently used animal models of NAFLD/NASH lack clinical features of either NASH or metabolic syndrome such as hepatic inflammation and fibrosis (e.g., high-fat diets) or overweight and insulin resistance (e.g., methionine-choline-deficient diets), or they are based on monogenetic defects (e.g., ob/ob mice). In the current study, a Western-type diet containing soybean oil with high n-6-PUFA and 0.75% cholesterol (SOD + Cho) induced steatosis, inflammation and fibrosis accompanied by hepatic lipid peroxidation and oxidative stress in livers of C57BL/6-mice, which in addition showed increased weight gain and insulin resistance, thus displaying a phenotype closely resembling all clinical features of NASH in patients with metabolic syndrome. In striking contrast, a soybean oil-containing Western-type diet without cholesterol (SOD) induced only mild steatosis but not hepatic inflammation, fibrosis, weight gain or insulin resistance. Another high-fat diet, mainly consisting of lard and supplemented with fructose in drinking water (LAD + Fru), resulted in more prominent weight gain, insulin resistance and hepatic steatosis than SOD + Cho, but livers were devoid of inflammation and fibrosis. Although both LAD + Fru-and SOD + Cho-fed animals had high plasma cholesterol, liver cholesterol was elevated only in SOD + Cho animals. Cholesterol induced expression of chemotactic and inflammatory cytokines in cultured Kupffer cells and rendered hepatocytes more susceptible to apoptosis. In summary, dietary cholesterol in the SOD + Cho diet may trigger hepatic inflammation and fibrosis. SOD + Cho-fed animals may be a useful disease model displaying many clinical features of patients with the metabolic syndrome and NASH.
AimAdvancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better-surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet Viverra tangalunga in Borneo.
LocationBorneo, Southeast Asia.
MethodsWe collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range-restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north-eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas.
ResultsSpatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased.
Main ConclusionsWe conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.
Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade‐offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual‐based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open‐source software, our model can coevolve with the collection and analysis of new data on energy budget and movement into a generic tool for sea turtle research and conservation. Our modeling approach could also be useful for supporting the conservation of other migratory marine animals.
Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species-specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi-dimensional assessments are still to be recommended.
Non-consumptive effects of predators within ecosystems can alter the behavior of individual prey species, and have cascading effects on other trophic levels. In this context, an understanding of non-consumptive predator effects on the whole prey community is crucial for predicting community structure and composition, hence biodiversity patterns. We used an individual-based, spatially-explicit modelling approach to investigate the consequences of landscapes of fear on prey community metrics. The model spans multiple hierarchical levels from individual home range formation based on food availability and perceived predation risk to consequences on prey community structure and composition. This mechanistic approach allowed us to explore how important factors such as refuge availability and foraging strategy under fear affect prey community metrics. Fear of predators affected prey space use, such as home range formation. These adaptations had broader consequences for the community leading to changes in community structure and composition. The strength of community responses to perceived predation risk was driven by refuge availability in the landscape and the foraging strategy of prey animals. Low refuge availability in the landscape strongly decreased diversity and total biomass of prey communities. Additionally, body mass distributions in prey communities facing high predation risk were shifted towards small prey animals. With increasing refuge availability the consequences of non-consumptive predator effects were reduced, diversity and total biomass of the prey community increased. Prey foraging strategies affected community composition. Under medium refuge availability, risk-averse prey communities consisted of many small animals while risk-taking prey communities showed a more even body mass distribution. Our findings reveal that non-consumptive predator effects can have important implications for prey community diversity and should therefore be considered in the context of conservation and nature management.