State space and movement specification in open population spatial capture-recapture models.

With continued global changes, such as climate change, biodiversity loss, and habitat fragmentation, the need for assessment of long-term population dynamics and population monitoring of threatened species is growing. One powerful way to estimate population size and dynamics is through capture-recapture methods. Spatial capture (SCR) models for open populations make efficient use of capture-recapture data, while being robust to design changes. Relatively few studies have implemented open SCR models, and to date, very few have explored potential issues in defining these models. We develop a series of simulation studies to examine the effects of the state-space definition and between-primary-period movement models on demographic parameter estimation. We demonstrate the implications on a 10-year camera-trap study of tigers in India. The results of our simulation study show that movement biases survival estimates in open SCR models when little is known about between-primary-period movements of animals. The size of the state-space delineation can also bias the estimates of survival in certain cases.We found that both the state-space definition and the between-primary-period movement specification affected survival estimates in the analysis of the tiger dataset (posterior mean estimates of survival ranged from 0.71 to 0.89). In general, we suggest that open SCR models can provide an efficient and flexible framework for long-term monitoring of populations; however, in many cases, realistic modeling of between-primary-period movements is crucial for unbiased estimates of survival and density

Densidade Da Jaguatirica Em Um Ambiente Semiárido No Nordeste Do Brasil

Ocelots play a key role in ecological communities as mesopredators affecting the lower trophic level and other mesopredators. They show great variability in ecological traits across their distribution, but knowledge of this species is missing in several regions where it occurs. Here, we present the first study of ocelot in the Brazilian semiarid of Caatinga. Arid habitats might keep carnivore population density low and therefore vulnerable to environmental shocks and to human-induced changes, at risk of local extinction. To assess their population status, we used camera traps between September 2009 and January 2010. We estimated the density of ocelots using a spatially explicit capture-recapture method (SECR) to be 3.16 ± 0.46 individuals per 100 km2. This is a low-density estimate for ocelots, which might reflect the harsh conditions of the arid habitat. A longer population study of the ocelot can answer if this low population density is enough for a long-term persistence of this species in this and other arid environments. © 2016, Universidade Estadual de Campinas UNICAMP. All rights reserved.16

A review of camera trapping for conservation behaviour research

An understanding of animal behaviour is important if conservation initiatives are to be effective. However, quantifying the behaviour of wild animals presents significant challenges. Remote-sensing camera traps are becoming increasingly popular survey instruments that have been used to non-invasively study a variety of animal behaviours, yielding key insights into behavioural repertoires. They are well suited to ethological studies and provide considerable opportunities for generating conservation-relevant behavioural data if novel and robust methodological and analytical solutions can be developed. This paper reviews the current state of camera-trap-based ethological studies, describes new and emerging directions in camera-based conservation behaviour, and highlights a number of limitations and considerations of particular relevance for camera-based studies. Three promising areas of study are discussed: (1) documenting anthropogenic impacts on behaviour; (2) incorporating behavioural responses into management planning and (3) using behavioural indicators such as giving up densities and daily activity patterns. We emphasize the importance of reporting methodological details, utilizing emerging camera trap metadata standards and central data repositories for facilitating reproducibility, comparison and synthesis across studies. Behavioural studies using camera traps are in their infancy; the full potential of the technology is as yet unrealized. Researchers are encouraged to embrace conservation-driven hypotheses in order to meet future challenges and improve the efficacy of conservation and management processes

Sex differences and age-related changes in vertebral body volume and volumetric bone mineral density at the thoracolumbar spine using opportunistic QCT

ObjectivesTo quantitatively investigate the age- and sex-related longitudinal changes in trabecular volumetric bone mineral density (vBMD) and vertebral body volume at the thoracolumbar spine in adults.MethodsWe retrospectively included 168 adults (mean age 58.7 ± 9.8 years, 51 women) who received ≥7 MDCT scans over a period of ≥6.5 years (mean follow-up 9.0 ± 2.1 years) for clinical reasons. Level-wise vBMD and vertebral body volume were extracted from 22720 thoracolumbar vertebrae using a convolutional neural network (CNN)-based framework with asynchronous calibration and correction of the contrast media phase. Human readers conducted semiquantitative assessment of fracture status and bony degenerations.ResultsIn the 40-60 years age group, women had a significantly higher trabecular vBMD than men at all thoracolumbar levels (p<0.05 to p<0.001). Conversely, men, on average, had larger vertebrae with lower vBMD. This sex difference in vBMD did not persist in the 60-80 years age group. While the lumbar (T12-L5) vBMD slopes in women only showed a non-significant trend of accelerated decline with age, vertebrae T1-11 displayed a distinct pattern, with women demonstrating a significantly accelerated decline compared to men (p<0.01 to p<0.0001). Between baseline and last follow-up examinations, the vertebral body volume slightly increased in women (T1-12: 1.1 ± 1.0 cm3; L1-5: 1.0 ± 1.4 cm3) and men (T1-12: 1.2 ± 1.3 cm3; L1-5: 1.5 ± 1.6 cm3). After excluding vertebrae with bony degenerations, the residual increase was only small in women (T1-12: 0.6 ± 0.6 cm3; L1-5: 0.7 ± 0.7 cm3) and men (T1-12: 0.7 ± 0.6 cm3; L1-5: 1.2 ± 0.8 cm3). In non-degenerated vertebrae, the mean change in volume was <5% of the respective vertebral body volumes.ConclusionSex differences in thoracolumbar vBMD were apparent before menopause, and disappeared after menopause, likely attributable to an accelerated and more profound vBMD decline in women at the thoracic spine. In patients without advanced spine degeneration, the overall volumetric changes in the vertebral body appeared subtle

Integrating Multiple Genetic Detection Methods to Estimate Population Density of Social and Territorial Carnivores

Spatial capture–recapture models can produce unbiased estimates of population density, but sparse detection data often plague studies of social and territorial carnivores. Integrating multiple types of detection data can improve estimation of the spatial scale parameter (σ), activity center locations, and density. Noninvasive genetic sampling is effective for detecting carnivores, but social structure and territoriality could cause differential detectability among population cohorts for different detection methods. Using three observation models, we evaluated the integration of genetic detection data from noninvasive hair and scat sampling of the social and territorial coyote (Canis latrans). Although precision of estimated density was improved, particularly if sharing σ between detection methods was appropriate, posterior probabilities of σ and posterior predictive checks supported different σ for hair and scat observation models. The resulting spatial capture–recapture model described a scenario in which scat‐detected individuals lived on and around scat transects, whereas hair‐detected individuals had larger σ and mostly lived off of the detector array, leaving hair but not scat samples. A more supported interpretation is that individual heterogeneity in baseline detection rates (λ0) was inconsistent between detection methods, such that each method disproportionately detected different population cohorts. These findings can be attributed to the sociality and territoriality of canids: Residents may be more likely to strategically mark territories via defecation (scat deposition), and transients may be more likely to exhibit rubbing (hair deposition) to increase mate attraction. Although this suggests that reliance on only one detection method may underestimate population density, integrating multiple sources of genetic detection data may be problematic for social and territorial carnivores. These data are typically sparse, modeling individual heterogeneity in λ0 and/or σ with sparse data is difficult, and positive bias can be introduced in density estimates if individual heterogeneity in detection parameters that is inconsistent between detection methods is not appropriately modeled. Previous suggestions for assessing parameter consistency of σ between detection methods using Bayesian model selection algorithms could be confounded by individual heterogeneity in λ0 in noninvasive detection data. We demonstrate the usefulness of augmenting those approaches with calibrated posterior predictive checks and plots of the posterior density of activity centers for key individuals

Coopetition as a development stimulator of enterprises in the networked steel sector

The article deals with the problems of coopetition, i.e. simultaneous cooperation and competition between enterprises. This phenomenon is becoming more and more common in the steel industry, initially in the dimension of individual alliances, and currently it takes a form of network connections. The different groups of enterprises are involved in these networks: global players, regional champions, as well as niche specialists. Through the coopetition companies achieve benefits (both internal and external) which are becoming the stimulator of survival and growth in a highly competitive steel industry

Association of Thigh Muscle Strength with Texture Features Based on Proton Density Fat Fraction Maps Derived from Chemical Shift Encoding-Based Water-Fat MRI

Purpose: Based on conventional and quantitative magnetic resonance imaging (MRI), texture analysis (TA) has shown encouraging results as a biomarker for tissue structure. Chemical shift encoding-based water–fat MRI (CSE-MRI)-derived proton density fat fraction (PDFF) of thigh muscles has been associated with musculoskeletal, metabolic, and neuromuscular disorders and was demonstrated to predict muscle strength. The purpose of this study was to investigate PDFF-based TA of thigh muscles as a predictor of thigh muscle strength in comparison to mean PDFF. Methods: 30 healthy subjects (age = 30 ± 6 years; 15 females) underwent CSE-MRI of the lumbar spine at 3T, using a six-echo 3D spoiled gradient echo sequence. Quadriceps (EXT) and ischiocrural (FLEX) muscles were segmented to extract mean PDFF and texture features. Muscle flexion and extension strength were measured with an isokinetic dynamometer. Results: Of the eleven extracted texture features, Variance(global) showed the highest significant correlation with extension strength (p 2adj = 0.712), and Correlation showed the highest significant correlation with flexion strength (p = 0.016, R2adj = 0.658). Multivariate linear regression models identified Variance(global) and sex, but not PDFF, as significant predictors of extension strength (R2adj = 0.709; p 2adj = 0.674; p < 0.001). Conclusions: Prediction of quadriceps muscle strength can be improved beyond mean PDFF by means of TA, indicating the capability to quantify muscular fat infiltration patterns