Dealing with Uncertainty in Spatially Explicit Population Models

It has been argued that spatially explicit population models (SEPMs) cannot provide reliable guidance for conservation biology because of the difficulty of obtaining direct estimates for their demographic and dispersal parameters and because of error propagation. We argue that appropriate model calibration procedures can access additional sources of information, compensating the lack of direct parameter estimates. Our objective is to show how model calibration using population-level data can facilitate the construction of SEPMs that produce reliable predictions for conservation even when direct parameter estimates are inadequate. We constructed a spatially explicit and individual-based population model for the dynamics of brown bears (Ursus arctos) after a reintroduction program in Austria. To calibrate the model we developed a procedure that compared the simulated population dynamics with distinct features of the known population dynamics (=patterns). This procedure detected model parameterizations that did not reproduce the known dynamics. Global sensitivity analysis of the uncalibrated model revealed high uncertainty in most model predictions due to large parameter uncertainties (coefficients of variation CV 0.8). However, the calibrated model yielded predictions with considerably reduced uncertainty (CV 0.2). A pattern or a combination of various patterns that embed information on the entire model dynamics can reduce the uncertainty in model predictions, and the application of different patterns with high information content yields the same model predictions. In contrast, a pattern that does not embed information on the entire population dynamics (e.g., bear observations taken from sub-areas of the study area) does not reduce uncertainty in model predictions. Because population-level data for defining (multiple) patterns are often available, our approach could be applied widely.     

Patterns of distribution and abundance of bonefish larvae <Emphasis Type="Italic">Albula</Emphasis> spp. (Albulidae) in the western Caribbean and adjacent areas

Overall patterns of distribution and abundance of Albula spp. leptocephali larvae offshore in the western Caribbean Sea (CAS) and Gulf of Mexico (GOM), and in coastal waters of the Mexican Caribbean (MXC) were analyzed from: (a) cruise data available from the Academy of Natural Sciences of Philadelphia (CAS, GOM) and (b) coastal plankton surveys (1998–2002 and January 2004) (MXC). We found striking inshore-offshore differences in the larval catch and size structure. Offshore cruises yielded 57 leptocephali, mostly determined as early stage I (18.0 ± 8.2 mm SL, mean ± SD). In contrast, coastal samples yielded 2,466 larvae 51.4 ± 3.6 mm SL, mostly late stage I; of these, 2,345 (95%) were caught over 4 nights in January 2004. The relationship between the larval length (mm, SL) and the distance to the coastline (km) was best represented by the regression model with a distinct variance for each locality. To ascertain whether the coastal inflow of leptocephali follows a regular seasonal pattern or depends on episodic events will require further monitoring; available evidence suggests that the southern coast of the MXC offers favorable conditions for the recruitment of Albula spp. larvae.     

The search for stability on narrow supports: an experimental study in cats and dogs

Kinematic and coordination variables were studied in two carnivorans, one with known locomotor capabilities in arboreal substrates (cat), and the other a completely terrestrial species (dog). Two horizontal substrates were used: a flat trackway on the ground (overground locomotion) and an elevated and narrow runway (narrow-support locomotion). Despite their different degree of familiarity with the ‘arboreal’ situation, both species developed a strategy to adapt to narrow supports. The strategy of cats was based on using slower speeds, coupled with modifications to swing phase duration, to keep balance on narrow supports. The strategy of dogs relied on high speeds to gain in dynamic stability, and they increased cycle frequency by reducing swing phase duration. Furthermore, dogs showed a high variability in limb coordination, although a tendency to canter-like coordination was observed, and also avoided whole-body aerial phases. In different ways, both strategies suggested a reduction of peak vertical forces, and hence a reduction of the vertical oscillations of the centre of mass. Finally, lateral oscillation was reduced by the use of a crouched posture.     

Individually Adapted Imagery Improves Brain-Computer Interface Performance in End-Users with Disability

Brain-computer interfaces (BCIs) translate oscillatory electroencephalogram (EEG) patterns into action. Different mental activities modulate spontaneous EEG rhythms in various ways. Non-stationarity and inherent variability of EEG signals, however, make reliable recognition of modulated EEG patterns challenging. Able-bodied individuals who use a BCI for the first time achieve - on average - binary classification performance of about 75%. Performance in users with central nervous system (CNS) tissue damage is typically lower. User training generally enhances reliability of EEG pattern generation and thus also robustness of pattern recognition. In this study, we investigated the impact of mental tasks on binary classification performance in BCI users with central nervous system (CNS) tissue damage such as persons with stroke or spinal cord injury (SCI). Motor imagery (MI), that is the kinesthetic imagination of movement (e.g. squeezing a rubber ball with the right hand), is the "gold standard" and mainly used to modulate EEG patterns. Based on our recent results in able-bodied users, we hypothesized that pair-wise combination of "brain-teaser" (e.g. mental subtraction and mental word association) and "dynamic imagery" (e.g. hand and feet MI) tasks significantly increases classification performance of induced EEG patterns in the selected end-user group. Within-day (How stable is the classification within a day?) and between-day (How well does a model trained on day one perform on unseen data of day two?) analysis of variability of mental task pair classification in nine individuals confirmed the hypothesis. We found that the use of the classical MI task pair hand vs. feed leads to significantly lower classification accuracy - in average up to 15% less - in most users with stroke or SCI. User-specific selection of task pairs was again essential to enhance performance. We expect that the gained evidence will significantly contribute to make imagery-based BCI technology become accessible to a larger population of users including individuals with special needs due to CNS damage.     

Breeding like rabbits: global patterns of variability and determinants of European wild rabbit reproduction

The importance of European wild rabbits Oryctolagus cuniculus both as a pest in some areas and as a key prey species in others emphasizes the need to understand what controls its population dynamics worldwide. In this study we aim to describe the variability in rabbit breeding parameters and identify the main factors that govern it at a global scale. Despite the species' wide distribution, some reproductive traits such as short sexual maturity age, duration of gestation period, and existence of post-partum oestrus are similar in all populations conferring the species a high breeding potential. Nevertheless, other aspects vary substantially among regions resulting in highly different population productivities and also across years. These latter parameters are the length of breeding season, proportion of pregnant females, age of first reproduction, and number and size of litters. Our results show that variability in these attributes is mainly affected by a combination of environmental controls (i.e. temperature, resource availability, and photoperiod) and individual properties (age and body weight). On the other hand, the effect of other factors such as population density could not be demonstrated. Knowledge about the factors driving global reproduction patterns of European wild rabbits will improve our understanding about their population dynamics, and thus will help to optimize the management and conservation of their populations.     

One or two cameras per station? Monitoring jaguars and other mammals in the Amazon

Camera trapping has become a popular technique to monitor carnivore populations due to its usefulness in estimating abundance. Nevertheless, there are a number of problems associated with study design which are motivating researchers to search for a compromise that ensures improvement of precision while being cost-effective. We have used data from a capture?Crecapture study in a forested area in central Brazil to evaluate the effectiveness of using one versus two cameras per trapping station for determining jaguar (Panthera onca) density and capture rates of several other mammals. The capture rate for the jaguar and other species recorded with only one camera was lower than that with two cameras. The number of jaguars identified using photos from one camera ranged between six and seven animals, but reached ten individuals when two-camera sets were used where pictures of both flanks could be positively individualized. These differences, combined with different estimates of effective sampled area size, resulted in jaguar densities estimates ranging from 2.18 to 5.40 and 3.99?individuals/100?km² when one and two cameras were used per station, respectively (using the half-MMDM and Heterogeneity model). Based on our results, we recommend the use of two cameras per station for jaguar density monitoring to ensure reasonable levels of reliability and accuracy of estimates despite a small sample size.