An evaluation of field and non-invasive genetic methods to estimate brown bear (Ursus arctos) population size

Estimates of population size and density are essential for successful management and conservation of any species. Although there are a variety of methods available for estimating abundance and density of populations, most studies rely on only one estimator and very few studies have compared and critically evaluated the adequacy and the cost of these methods. We used the brown bear (Ursus arctos) in south-central Sweden to compare the performance of three different methods of estimating population size, including methods based on conventional field data as well as on non-invasive genetic data. The method based on observations of females with cubs underestimated the true population size, as the estimates were below the number of unique genotypes determined from faecal data inside the study area. The best traditional method was based on observations of bears from a helicopter. The genetic method using the closed population MARK estimator, as recommended in a previous study, seemed to perform the best. We conclude that approximately 223 (188-282) bears were present in our 7328 km² study area during 2001 and 2002 and suggest that this hunted brown bear population has been relatively stable for about ten years. The non-invasive genetic method was less expensive than the most reliable traditional field method (a CMR method based on observations of bears from a helicopter), and preferable from an ethical point of view. We recommend that future studies using non-invasive genetic methods based on collected faecal samples should aim at collecting 2.5-3 times the number of faecal samples as the “assumed” number of animals.     

Empirical predictions of plant material C and N mineralization patterns from near infrared spectroscopy, stepwise chemical digestion and C/N ratios

Prediction of carbon (C) and nitrogen (N) mineralization patterns of plant litter is desirable for both agronomic and environmental reasons. Near infrared reflectance (NIR) spectroscopy has recently been introduced in decomposition studies to characterize biochemical composition. The purpose of the current study was to use empirical techniques to predict C and N mineralization patterns of a wide range of plant materials incubated under controlled temperature and moisture conditions. We hypothesized that the richness of information in the NIR spectra would considerably improve predictions compared to traditional stepwise chemical digestion (SCD) or C/N ratios. Initially, we fitted a number of empirical functions to the observed C and N mineralization patterns. The best functions fitted with R²=0.990 and 0.949 to C and N, respectively. The fractions of C and N mineralized at different points in time were then either predicted directly with regression functions or indirectly by prediction of the parameters of the empirical functions fitted to incubation data. In both cases, partial least squares (PLS) regressions were used and predictions were validated by cross-validations. We found that the NIR spectra (best R²=0.925) were able to predict C mineralization patterns marginally better than the SCD fractions (best R²=0.911), but considerably better than the C/N ratios (best R²=0.851). In contrast, N mineralization was better predicted by SCD fractions (best R²=0.533) than the C/N ratio (best R²=0.497), which was better than NIR predictions (best R²=0.446). Although the predictions with the NIR spectra were only slightly better for C and worse for N mineralization compared to SCD fractions, NIR spectroscopy still holds advantages, as it is a much less laborious and cheaper analytical method. Furthermore, exploration of the applications of NIR spectroscopy in decomposition studies has only just begun, and offers new ways to gain insights into the decomposition process.     

Genetic tracking of the brown bear in northern Pakistan and implications for conservation

Asian bears face major threats due to the impact of human activities as well as a critical lack of knowledge about their status, distribution and needs for survival. Once abundant in northern Pakistan, the Himalayan brown bear (Ursus arctos isabellinus) has been exterminated in most of its former distribution range. It presently occurs sparsely, in small populations, the Deosai National Park supporting the largest isolate. This decline might imply a reduction in genetic diversity, compromising the survival of the population. Using a combination of fecal DNA analysis and field data, our study aimed at assessing the size and genetic status of the Deosai population and give guidelines for its conservation and management. Using fecal genetic analysis, we estimated the population to be 40-50 bears, which compares well with the field census of 38 bears. The northern Pakistani brown bear population may have undergone an approximate 200-300-fold decrease during the last thousand years, probably due to glaciations and the influence of growing human population. However, in spite of the presence of a bottleneck genetic signature, the Deosai population has a moderate level of genetic diversity and is not at immediate risk of inbreeding depression. Gene flow might exist with adjacent populations. We recommend careful monitoring of this population in the future both with field observations and genetic analyses, including sampling of adjacent populations to assess incoming gene flow. The connectivity with adjacent populations in Pakistan and India will be of prime importance for the long-term survival of Deosai bears.     

Allergenicity assessment of the papaya ringspot virus coat protein expressed in transgenic rainbow papaya

The virus-resistant, transgenic commercial papaya Rainbow and SunUp (Carica papaya L.) have been consumed locally in Hawaii and elsewhere in the mainland United States and Canada since their release to planters in Hawaii in 1998. These papaya are derived from transgenic papaya line 55-1 and carry the coat protein (CP) gene of papaya ringspot virus (PRSV). The PRSV CP was evaluated for potential allergenicity, an important component in assessing the safety of food derived from transgenic plants. The transgene PRSV CP sequence of Rainbow papaya did not exhibit greater than 35% amino acid sequence homology to known allergens, nor did it have a stretch of eight amino acids found in known allergens which are known common bioinformatic methods used for assessing similarity to allergen proteins. PRSV CP was also tested for stability in simulated gastric fluid and simulated intestinal fluid and under various heat treatments. The results showed that PRSV CP was degraded under conditions for which allergenic proteins relative to nonallergens are purported to be stable. The potential human intake of transgene-derived PRSV CP was assessed by measuring CP levels in Rainbow and SunUp along with estimating the fruit consumption rates and was compared to potential intake estimates of PRSV CP from naturally infected nontransgenic papaya. Following accepted allergenicity assessment criteria, our results show that the transgene-derived PRSV CP does not pose a risk of food allergy.     

Frequent long-distance plant colonization in the changing Arctic

The ability of species to track their ecological niche after climate change is a major source of uncertainty in predicting their future distribution. By analyzing DNA fingerprinting (amplified fragment-length polymorphism) of nine plant species, we show that long-distance colonization of a remote arctic archipelago, Svalbard, has occurred repeatedly and from several source regions. Propagules are likely carried by wind and drifting sea ice. The genetic effect of restricted colonization was strongly correlated with the temperature requirements of the species, indicating that establishment limits distribution more than dispersal. Thus, it may be appropriate to assume unlimited dispersal when predicting long-term range shifts in the Arctic.     

Collaborative validation of the QuEChERS procedure for the determination of pesticides in food by LC-MS/MS

Seven FDA pesticide laboratories collaborated to develop and validate an LC-MS/MS method to determine 173 pesticides in <20 min. The average determination coefficient (r2) was >0.99 for all but two compounds tested. The limits of detection were <20 ng/mL for all compounds and <10 ng/mL for 363 of the 368 transitions reported. The method was used to determine pesticides in two AOAC sponsored proficiency samples. The LC-MS/MS determination was used for the analysis of oranges, carrots and spinach using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, Safe) method. Each matrix was fortified at 20, 100, 400, and 1000 ng/g. No false positive responses were detected in controls of the three matrices. 165 pesticides had recoveries between 70 and 130%, and 161 had minimum detection levels less than 10 ng/g. Recoveries of 169 compounds for the 1000 ng/g spikes were within 50-150%. A matrix effect study indicated all three matrices caused a small net suppressing effect, the most pronounced attributable to the citrus matrix. The procedure proved to be accurate, precise, linear, sensitive and rugged, and adds 100 pesticides to the scope of the FDA pesticide program.     

A comparative molecular field analysis study of obtusifoliol 14α-methyl demethylase inhibitors

This report describes the development of a Comparative Molecular Field Analysis (CoMFA) model from a set of obtusifoliol 14α-methyl demethylase (DM) inhibitors to aid in the design of herbicides targeting sterol biosynthesis. CoMFA is a three-dimensional (3-D) quantitative structure–activity relationship (QSAR) method that is useful in the probing of receptor binding sites when experimental structure data are unavailable. Conformational analysis and SAR of some rigid and active analogs were used to build the initial model using the active analog hypothesis. The model was subsequently used to design compounds that retain the active site shape requirements, but incorporate physical properties that favor soil-applied herbicidal action. In addition, a second-generation CoMFA model incorporating the newly designed inhibitors was developed and represents the current understanding of the DM binding site. This model was derived from a pharmacophore developed from two methods, the active analog approach as well as from the Catalyst program. The fact that two independent methods produced a similar pharmacophore strengthens the validity of the model. © 1999 Society of Chemical Industry     

Snapshots of DsbA in action: detection of proteins in the process of oxidative folding

DsbA, a thioredoxin superfamily member, introduces disulfide bonds into newly translocated proteins. This process is thought to occur via formation of mixed disulfide complexes between DsbA and its substrates. However, these complexes are difficult to detect, probably because of their short-lived nature. Here we show that it is possible to detect such covalent intermediates in vivo by a mutation in DsbA that alters cis proline-151. Further, this mutant allowed us to identify substrates of DsbA. Alteration of the cis proline, highly conserved among thioredoxin superfamily members, may be useful for the detection of substrates and intermediate complexes in other systems.