Habitat Discrimination Research Articles

Cast from the Past? Microbial Diversity of a Neolithic Stone Circle.

We studied the microbial diversity colonizing limestone rock pools at a Neolithic Monument (Arbor Low, Derbyshire, England). Five pools were analyzed: four located at the megaliths of the stone circle and one pool placed at the megalith at the Gib Hill burial mound 300 m distant. Samples were taken from rock pool walls and sediments, and investigated through molecular metabarcoding. The microbiome consisted of 23 phyla of bacteria (831 OTUs), 4 phyla of archaea (19 OTUs), and 27 phyla of microbial eukarya (596 OTUs). For bacteria, there were statistically significant differences in wall versus sediment populations, but not between pools. For archaea and eukarya, significant differences were found only between pools. The most abundant bacterial phylum in walls was Cyanobacteriota, and Pseudomonadota in sediments. For archaea and microbial eukarya, the dominant phyla were Euryarcheota and Chlorophyta, respectively, in both wall and sediments. The distant pool (P5) showed a markedly different community structure in phyla and species, habitat discrimination, and CHN content. Species sorting and dispersal limitation are discussed as mechanisms structuring the microbiome assemblages and their spatial connectivity. The Arbor Low microbiome is composed of terrestrial representatives common in extreme environments. The high presence of Cyanobacteriota and Chlorophyta in the Arbor Low stones is troubling, as these microorganisms can induce mechanical disruption by penetrating the limestone matrix through endolithic/chasmoendolithic growth. Future research should focus on the metabolic traits of strains to ascertain their implication in bioweathering and/or biomineralization.

Microhabitat preferences in the European green lizard (Lacerta viridis): implications for conservation management of isolated populations

The European green lizard (Lacerta viridis) populations in Bohemia, Czech Republic, are isolated by more than 150 km from the northern border of the continuous range of the species. These populations are fragmented and further isolated from each other. In this landscape mosaic, they are tied to specific habitats located in deeply incised river valleys (the so-called river phenomenon) and thus may be viewed as stenotopic. The research site is located on the northern edge of the city of Prague. Since 1998, this site has been the subject of long-term conservation management aimed at strengthening and maintaining the abundance of the local L. viridis population. To formulate recommendations for the management of other isolated L. viridis populations, we performed a spatial analysis of the localities with observed individuals to determine and evaluate the significance of the chosen biotic and abiotic factors for habitat discrimination. We applied principal components and discriminant function analyses and examined the effect of 24 variables on the species’ presence. The results revealed the principal role of the presence of rock debris and hiding places for lizard occurrence. The strongest negative predictors were the presence of tall grass and high vegetation coverage. We discuss the applicability of our findings in both the theory and practice of species conservation and population management.

Temperature is a cryptic factor shaping the geographical pattern of genetic variation in Ceratophyllum demersum across a subtropical freshwater lake

Macrophyte habitats exhibit remarkable heterogeneity, encompassing the spatial variation of abiotic and biotic components such as changes in water conditions and weather as well as anthropogenic stressors. Environmental factors are thought to be important drivers shaping the genetic and epigenetic variation of aquatic plants. However, the links among genetic diversity, epigenetic variation, and environmental variables remain largely unclear, especially for clonal aquatic plants. Here, we performed population genetic and epigenetic analyses in conjunction with habitat discrimination to elucidate the environmental factors driving intraspecies genetic and epigenetic variation in hornwort (Ceratophyllum demersum) in a subtropical lake. Environmental factors were highly correlated with the genetic and epigenetic variation of C. demersum, with temperature being a key driver of the genetic variation. Lower temperature was detected to be correlated with greater genetic and epigenetic variation. Genetic and epigenetic variation were positively driven by water temperature, but were negatively affected by ambient air temperature. These findings indicate that the genetic and epigenetic variation of this clonal aquatic herb is not related to the geographic feature but is instead driven by environmental conditions, and demonstrate the effects of temperature on local genetic and epigenetic variation in aquatic systems.

Importance of estuaries for the horse-eye jack Caranx latus in northeastern Brazil: a case study of underestimated connectivity at the land-sea interface

This study aimed to evaluate the importance of inshore estuarine habitats for the maintenance of offshore exploited stocks of the horse-eye jack Caranx latus, a marine tropical species of high economic value. Otoliths of 143 yearlings were used to develop a data set of multi-elemental fingerprints for different juvenile habitats of C. latus in northeastern Brazil, including 7 estuaries and the coastal zone. This data set was then compared to the signatures in the juvenile part of the otolith of 40 sub-adult and adult fish caught at sea to identify their origin. Although otolith multi-elemental concentrations overlapped for some of the estuaries investigated, the maximum overall discrimination accuracy between them was only 58%. However, grouping several estuaries according to their similarity in elemental signatures increased accuracy to 80%. In both cases, correct re-assignment rates for the coastal zone were above 94%, and strontium (Sr) was the most significant element in juvenile habitat discrimination. The remaining elements (B, Ba, Co, P, Rb, and Zn) allowed us to distinguish between 3 distinct groups of estuaries, for which correct re-assignment rates were 70-88%. Juvenile fingerprints in sub-adult and adult otoliths revealed that most of the fish in the local, exploited stock (75%) originate from an inshore estuarine habitat, particularly from larger estuaries under constant marine influence (32.5%). This biological connectivity between continental and coastal waters should be considered for the conservation of tropical marine coastal stocks in general, as it is likely to apply to other exploited marine species, in Brazil and elsewhere.

Auditory discrimination of natural soundscapes.

A previous modelling study reported that spectro-temporal cues perceptually relevant to humans provide enough information to accurately classify "natural soundscapes" recorded in four distinct temperate habitats of a biosphere reserve [Thoret, Varnet, Boubenec, Ferriere, Le Tourneau, Krause, and Lorenzi (2020). J. Acoust. Soc. Am. 147, 3260]. The goal of the present study was to assess this prediction for humans using 2 s samples taken from the same soundscape recordings. Thirty-one listeners were asked to discriminate these recordings based on differences in habitat, season, or period of the day using an oddity task. Listeners' performance was well above chance, demonstrating effective processing of these differences and suggesting a general high sensitivity for natural soundscape discrimination. This performance did not improve with training up to 10 h. Additional results obtained for habitat discrimination indicate that temporal cues play only a minor role; instead, listeners appear to base their decisions primarily on gross spectral cues related to biological sound sources and habitat acoustics. Convolutional neural networks were trained to perform a similar task using spectro-temporal cues extracted by an auditory model as input. The results are consistent with the idea that humans exclude the available temporal information when discriminating short samples of habitats, implying a form of a sub-optimality.

Ionomic Parameters of Populations of Common Juniper (Juniperus communis L.) Depending on the Habitat Type.

For the study of the ionomic parameters of Juniperus communis needles, fourteen sites covering most of the territory of Lithuania and belonging to distinct habitats (coastal brown dunes covered with natural Scots pine forests (G), Juniperus communis scrubs (F), transition mires and quaking bogs (D), subcontinental moss Scots pine forests (G), and xero-thermophile fringes) were selected. Concentrations of macro-, micro-, and non-essential elements were analyzed in current-year needles, sampled in September. According to the concentrations of elements in J. communis needles, the differences between the most contrasting populations were as follows: up to 2-fold for Mg, N, K, Ca, and Zn; 2- to 7-fold for P, Na, Fe, Cu, Al, Cr, Ni, and Pb; and 26- to 31-fold for Mn and Cd. The concentrations of Cd, Cr, and Ni in needles of J. communis did not reach levels harmful for conifers. When compared to all other habitats (B, F, G, and E), the populations from transition mires and quaking bogs (D) had significantly lower concentrations of main nutritional elements N (12176 µg/g d. m.), P (1054 µg/g d. m.), and K (2916 µg/g d. m.). In Juniperus communis scrubs (F), a habitat protected by EUNIS, the concentration of K in the needles was highest, while Zn and Cu concentrations were the lowest. Principal component (PC) analyses using concentrations of 15 elements as variables for the discrimination of populations or habitats allowed authors to distinguish F and B habitats from the E habitat (PC1) and F and D habitats from the G habitat (PC2). Discriminating between populations, the most important variables were concentrations of P, N, Mg, Ca, Cu, and K. Discriminating between habitats, the important variables were concentrations of N and P.

The emergence of imperfect philopatry and fidelity in spatially and temporally heterogeneous environments

Repeatability in habitat use - often termed site fidelity - is widespread and ubiquitous. Often, used habitat areas may be inherited by offspring in a phenomenon called natal philopatry, leading to intergenerational repeatability in habitat preferences. Both fidelity and philopatry may represent strategies that could optimize fitness in spatially and temporally heterogeneous environments; however, the suite of ecological factors that encourage or discourage fidelity and philopatry remain poorly understood in most taxa. While turtles (Order Testudines) exhibit both fidelity and natal philopatry when selecting nesting areas, emerging evidence suggests that nest choice may be more plastic than previously thought. However, few studies to date have attempted to explore the behavioral choices that may produce deviations from nest site fidelity and philopatry. We used a spatially-explicit, individual-based model to explore how behavioral responses to a heterogeneous landscape can generate population-level patterns of fidelity and philopatry. We demonstrate that this model can dispersal patterns inferred from behavioral and genetic data from a Blanding's Turtle (Emydoidea blandingii) population in central Wisconsin. Reduced philopatry was associated with increasing error rates in habitat discrimination, and reduced site fidelity was associated with decreasing risk tolerance. Unpredictable spatial distributions of risk increased natal philopatry but decreased site fidelity overall, suggesting that strong natal imprinting may sometimes be associated with rapid shifts in habitat preferences in unpredictable environments. Associating risk exposure with increased adult or nest mortality led to increased nest site fidelity in both cases, but with relatively weak effects on natal philopatry. We also demonstrate the utility of this model for other landscapes and species by exploring a simplified seabird system. Our model holds promise for more detailed exploration of the ecological and evolutionary factors that may give rise to fidelity and philopatry.

Multiple imputation of multibeam angular response data for high resolution full coverage seabed mapping

Acoustic data collected by multibeam echosounders (MBES) are increasingly used for high resolution seabed mapping. The relationships between substrate properties and the acoustic response of the seafloor depends on the acoustic angle of incidence and the operating frequency of the sonar, and these dependencies can be analysed for discrimination of benthic substrates or habitats. An outstanding challenge for angular MBES mapping at a high spatial resolution is discontinuity; acoustic data are seldom represented at a full range of incidence angles across an entire survey area, hindering continuous spatial mapping. Given quantifiable relationships between MBES data at various incidence angles and frequencies, we propose to use multiple imputation to achieve complete estimates of angular MBES data over full survey extents at a high spatial resolution for seabed mapping. The primary goals of this study are (i) to evaluate the effectiveness of multiple imputation for producing accurate estimates of angular backscatter intensity and substrate penetration information, and (ii) to evaluate the usefulness of imputed angular data for benthic habitat and substrate mapping at a high spatial resolution. Using a multi-frequency case study, acoustic soundings were first aggregated to homogenous seabed units at a high spatial resolution via image segmentation. The effectiveness and limitations of imputation were explored in this context by simulating various amounts of missing angular data, and results suggested that a substantial proportion of missing measurements (> 40%) could be imputed with little error using Multiple Imputation by Chained Equations (MICE). The usefulness of imputed angular data for seabed mapping was then evaluated empirically by using MICE to generate multiple stochastic versions of a dataset with missing angular measurements. The complete, imputed datasets were used to model the distribution of substrate properties observed from ground-truth samples using Random Forest and neural networks. Model results were pooled for continuous spatial prediction and estimates of confidence were derived to reflect uncertainty resulting from multiple imputations. In addition to enabling continuous spatial prediction, the high-resolution imputed angular models performed favourably compared to broader segmentations or non-angular data.

Sentinel-2 Remote Sensed Image Classification with Patchwise Trained ConvNets for Grassland Habitat Discrimination

The present study focuses on the use of Convolutional Neural Networks (CNN or ConvNet) to classify a multi-seasonal dataset of Sentinel-2 images to discriminate four grassland habitats in the “Murgia Alta” protected site. To this end, we compared two approaches differing only by the first layer machinery, which, in one case, is instantiated as a fully-connected layer and, in the other case, results in a ConvNet equipped with kernels covering the whole input (wide-kernel ConvNet). A patchwise approach, tessellating training reference data in square patches, was adopted. Besides assessing the effectiveness of ConvNets with patched multispectral data, we analyzed how the information needed for classification spreads to patterns over convex sets of pixels. Our results show that: (a) with an F1-score of around 97% (5 × 5 patch size), ConvNets provides an excellent tool for patch-based pattern recognition with multispectral input data without requiring special feature extraction; (b) the information spreads over the limit of a single pixel: the performance of the network increases until 5 × 5 patch sizes are used and then ConvNet performance starts decreasing.

Can UAVs fill the gap between in situ surveys and satellites for habitat mapping?

Habitat mapping is an essential descriptor to monitor and manage natural or semi-natural ecosystems. Habitats integrate both the environmental conditions and the related biodiversity. However, it remains challenging to map certain habitats such as inland wetlands due to spectral, spatial and temporal variability in the vegetation cover. Currently, no satellite constellations optimize the spectral, spatial and temporal resolutions required to map wetlands according to the habitats discriminated from in situ surveys. Our approach aims to combine satellite and unmanned aerial vehicle (UAV) data to exceed their respective limitations. Both data sources were combined through a spectral unmixing algorithm with the hypothesis that endmembers from UAV data are pure enough to enhance plant community abundances estimated from satellite data. The experiment was conducted on the regional preserve of the Sougéal marsh, a wet grassland of 174 ha located upstream of the Mont-Saint-Michel Bay. Two satellite data sources - Sentinel-2 and Pleiades - and three acquisition periods - November 2017, April 2018 and May 2018 - were considered. A reference map of plant community distribution was produced from UAV multitemporal data and floristic surveys to validate the unmixing of satellite data. This study shows innovative results and perspectives: while UAV can improve habitat discrimination, results vary among acquisition periods and habitats. Results illustrate well the great potential of combined UAV and satellite data but also demonstrate the influence of endmembers on the unmixing process and technical limitations (e.g. spectral mismatches between sensors), which can be overcome using domain adaptation.

Forest habitat invasions – Who with whom, where and why

Abstract Even though temperate forests have lower non-native plant species richness and cover in comparison to some other habitats, such as anthropogenically influenced habitats or some grassland habitats, several recent studies from Central Europe suggest that there has been an increase in the numbers and proportions of non-native species in forests. Previous studies on the level of invasion in forest habitats were usually conducted on a relatively coarse scale, often excluding plantations of non-native trees or analyzing them together as a group regardless of the different biological properties of different species. Therefore, a more detailed analysis would be helpful to obtain better insight into the processes taking place in forests, focusing not only on the analysis of the invasion level of different forest types at a finer scale (e.g., in various types of floodplain, beech or coniferous) but also on the character of the non-native plants found there (invasive status, frequencies and habitat preferences). In this study, we aimed to (i) compare the invasion level of various forest habitats (including forests dominated by non-native trees) in Slovakia with regard to different residence times and invasive status of non-native species, (ii) analyze whether forest habitats possess specific non-native species combinations, and (iii) determine the preferences of non-native plants with respect to specific forest habitats and the co-occurrence of other plant species with the most frequent non-native species. Our study confirmed that almost all forest habitats contained at least one non-native species. Native forests at lower elevations and closer to rivers were more invaded, while broadleaved, mixed and especially coniferous forests at higher elevations and ecologically strictly limited forests were less (or un-) invaded. Significant differences between various types of riparian and coniferous forests, emphasized the importance of the more detailed discrimination of the forest habitats in comparison with previous studies. Non-native tree plantations, which are among the most invaded forests, also deserve special attention. Some non-native trees form stable communities with typical native and non-native species, where non-native dominants can act as drivers of further changes in the vegetation composition, facilitating spread of other co-occurring non-native shrubs and herbs. Taking into consideration the potential negative impacts of some non-native plants on species composition, forest microclimate and soil chemistry, it would be advisable for foresters to factor this into forest management because their choice of planted species may both positively and negatively influence the level of invasion in managed forests.

Divergent habitat use of two urban lizard species.

Faunal responses to anthropogenic habitat modification represent an important aspect of global change. In Puerto Rico, two species of arboreal lizard, Anolis cristatellus and A. stratulus, are commonly encountered in urban areas, yet seem to use the urban habitat in different ways. In this study, we quantified differences in habitat use between these two species in an urban setting. For each species, we measured habitat use and preference, and the niche space of each taxon, with respect to manmade features of the urban environment. To measure niche space of these species in an urban environment, we collected data from a total of six urban sites across four different municipalities on the island of Puerto Rico. We quantified relative abundance of both species, their habitat use, and the available habitat in the environment to measure both microhabitat preference in an urban setting, as well as niche partitioning between the two different lizards. Overall, we found that the two species utilize different portions of the urban habitat. Anolis stratulus tends to use more “natural” portions of the urban environment (i.e., trees and other cultivated vegetation), whereas A. cristatellus more frequently uses anthropogenic structures. We also found that aspects of habitat discrimination in urban areas mirror a pattern measured in prior studies for forested sites in which A. stratulus was found to perch higher than A. cristatellus and preferred lower temperatures and greater canopy cover. In our study, we found that the multivariate niche space occupied by A. stratulus did not differ from the available niche space in natural portions of the urban environment and in turn represented a subset of the niche space occupied by A. cristatellus. The unique niche space occupied by A. cristatellus corresponds to manmade aspects of the urban environment generally not utilized by A. stratulus. Our results demonstrate that some species are merely tolerant of urbanization while others utilize urban habitats in novel ways. This finding has implications for long‐term persistence in urban habitats and suggests that loss of natural habitat elements may lead to nonrandom species extirpations as urbanization intensifies.

Habitat mapping of coastal wetlands using expert knowledge and Earth observation data

Summary Long‐term habitat mapping and change detection are essential for the management of coastal wetlands as well as for evaluating the impact of conservation policies. Earth observation (EO) data and techniques are a valuable resource for long‐term habitat mapping. Although the use of EO data is well developed for the automatic production of land cover (LC) maps, this is not the same for habitat maps, which are highly related to biodiversity. In a previous paper, we used the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) environmental attributes (e.g. water quality, lithology, soil surface aspect) for LC‐to‐habitat class translation. However, these environmental attributes are often not openly available, not updated or are missing. This paper offers an alternative, knowledge‐based solution to automatic habitat mapping. When only expert rules and EO data are used, the final overall map accuracy, which is obtained by comparing reference ground truth patches to the ones depicted in the output map, is lower (75·1%) than the accuracy obtained using environmental attributes alone (97·0%). Some ambiguities that still remain in habitat discrimination are resolved by integrating the use of LCCS environmental attributes (if available) and expert rules. In this paper, we use very high‐resolution (VHR) satellite data and LIDAR data. LC classes are labelled according to the LCCS taxonomy, which offers a framework to integrate EO data with in situ and ancillary data. Output habitat classes are labelled according to the European Habitats Directive (92/43 EEC Directive) Annex I habitat types and Eunis habitat classification. Two Natura 2000 coastal wetland sites in southern Italy are considered. Synthesis and applications. In this paper, we study the exploitation of ecological rules on vegetation pattern, plant phenology and habitat geometric properties for automatic translation of land cover (LC) maps to habitat maps in coastal wetlands. The methodology is useful for relatively inaccessible sites (e.g. wetlands) as it does not require in‐field campaigns (generally costly) but only the elicitation of ecological expert rules. This can support site (e.g. Natura 2000) managers in long‐term automatic habitat mapping. Habitat changes can be automatically detected by comparing map pairs, and trends can be quantified. This is particularly useful to satisfy the commitments of the European Habitats Directive (92/43/EEC), which requires Member States to take measures to maintain as, or restore to, favourable conservation status those natural habitat types and species of community interest that are listed in the Annexes to the Directive.

How does the selection of landscape classification schemes affect the spatial pattern of natural landscapes? An assessment on a coastal wetland site in southern Italy.

It is widely known that thematic resolution affects spatial pattern and landscape metrics performances. In literature, data dealing with this issue usually refer to a specific class scheme with its thematic levels. In this paper, the effects of different land cover (LC) and habitat classification schemes on the spatial pattern of a coastal landscape were compared. One of the largest components of the Mediterranean wetland system was considered as the study site, and different schemes widely used in the EU were selected and harmonized with a common thematic resolution, suitable for habitat discrimination and monitoring. For each scheme, a thematic map was produced and, for each map, 28 landscape metrics were calculated. The landscape composition, already in terms of number of classes, class area, and number of patches, changes significantly among different classification schemes. Landscape complexity varies according to the class scheme considered and its underlying semantics, depending on how the different types aggregate or split when changing class scheme. Results confirm that the selection of a specific class scheme affects the spatial pattern of the derived landscapes and consequently the landscape metrics, especially at class level. Moreover, among the classification schemes considered, EUNIS seems to be the best choice for a comprehensive representation of both natural and anthropogenic classes.

Vegetation phenology and habitat discrimination: Impacts for E. multilocularis transmission host modelling

Echinococcus multilocularis (Em), a parasitic tapeworm, is responsible for a significant burden of human disease across continental Asia. Here, we use a time-series of MODIS 16-day 250 m Enhanced Vegetation Index (EVI) satellite data to quantify the seasonal vegetation dynamics across a study area in Serxu County, Sichuan Province, China, in relation to the presence of the Em intermediate host Ochotona curzoniae (plateau pika) and Ochotona cansus (Gansu pika) (here merged to Ochotona spp.). A series of derived phenological metrics are analysed using the random forests statistical method to determine the relative importance of seasonal vegetation characteristics. Results indicate negative relationships between Ochotona spp. presence and EVI showing a preference for low-biomass habitats. However, EVI values during green-up and senescence periods are also shown to be important, potentially resulting from improved detectability of low-biomass grassland habitats at these times. Improved detection of Ochotona spp. preferred habitats via time-series EVI imagery offers better understanding of the distributions of this Em host, and the potential for monitoring the changes in Ochotona spp. optimal habitat distributions resulting from landscape change. This could aid the identification of villages at increased risk of infection, enabling preventive strategies to be adopted.

Detecting the Phenology and Discriminating Mediterranean Natural Habitats With Multispectral Sensors—An Analysis Based on Multiseasonal Field Spectra

Due to their high degree of vegetation heterogeneity, fragmentation, and biodiversity, Mediterranean natural habitats are difficult to assess and monitor with in situ observations solely. Together with standardized ground plots and regular in situ measurements, remote sensing contributes to better understand the diversity of these habitats and their phenology. We used field spectroradiometry to simulate the radiometric signal corresponding to six multispectral satellites: 1) IKONOS, 2) Landsat 5 TM, 3) Landsat 8, 4) Pléiades, 5) Sentinel-2, and 6) WorldView-2. We compared the suitability of each sensor for the estimation of the cover fraction of photosynthetic vegetation (PV) observed for five types of habitats during a vegetation cycle from February to October 2013. We also analyzed the contribution of multiseasonal satellite acquisitions for habitat discrimination. We showed that multivariate regression applied to Worldview-2 reflectance produces the most accurate PV. This was explained by the higher number of spectral bands in the visible domain. Habitat discrimination based on monotemporal acquisitions showed better performances when PV was higher. Sentinel-2 and WorldView-2 outperformed other sensors for each individual date. Multitemporal acquisitions outperformed monotemporal acquisition for habitat discrimination. However, selecting all reflectance data acquired during the season resulted in suboptimal performances compared to more parsimonious combinations. Finally, all of them ranged between 86.6% and 89.2% classification accuracy with multiseasonal acquisitions. New strategies need to be designed to identify individual habitats of particular interest. Defining optimal multiseasonal remote-sensing acquisitions specific to each habitat and appropriate spectral and spatial resolution will contribute to improved discrimination of Mediterranean natural habitats.

Habitat differentiation and degradation characterization of Cinnamomi Cortex by 1H NMR spectroscopy coupled with multivariate statistical analysis

In this study, habitat differentiation and degradation characterization of Cinnamomi Cortex (CC) were carried out using 1H NMR spectroscopy coupled with multivariate statistical analysis. Twenty-one components were plausibly identified in 1H NMR spectrum of CC, among which fatty acid, β-glucose, cinnamaldehyde and other seven compounds were screened out as reasonable chemical markers in orthogonal partial least squares-discriminant analysis (OPLS-DA), being responsible for the habitat discrimination of CC from Guangdong and Guangxi provinces of China. The results of 1H NMR spectroscopy combined with principal component analysis (PCA) revealed that the contents of coumarin and carbohydrates changed mildly during twoweek-storage, while the degradation of cinnamaldehyde along with some fatty acids was crucial. The degradated products of cinnamaldehyde were supposed as cinnamic acid and styrene, the latter of which is a potential neurotoxic and hepatotoxic compound. The results of radical scavenging assays suggested that degradation could down-regulate anti-oxidation performance of CC. Thus, the efficacy and safety of CC extract after long time storage deserve attention. Above all, 1H NMR spectroscopy can be used as a reliable tool to assess the quality of medicinal herbs as well as herbal dietary supplements.

Volatiles from spruce trap-trees detected by Ips typographus bark beetles: chemical and electrophysiological analyses

In the search for compounds that contribute to the host or habitat discrimination, antennae of Ips typographus were screened for sensitivity to volatiles released by spruce trap-trees using gas chromatography linked to electroantennography. The antennally active compounds were determined using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometric detection. Data show that I. typographus antennae respond to compounds emitted by the host. In total, 18 of antennally active compounds were detected: α-pinene, camphene, sabinene, β-pinene, myrcene, Δ-3-carene, p-cymene, limonene, β-phellandrene, 1,8-cineole, γ-terpinene, terpinolene, nonanal, camphor, trans-pinocamphone, cis-pinocamphone, terpinen-4-ol, and verbenone. Unequivocal identification of all active minor compounds is provided and confirmed using synthetic standards. Compounds in minor quantities like 1,8-cineole, β-phellandrene, camphor, cis-pinocamphone, and trans-pinocamphone were more active than major spruce monoterpenes. We hypothesize that the minor spruce compounds may play so far unrecognized role in conveying information about host suitability for I. typographus.

Methods for estimating a critical value for determining the freshwater/estuarine habitat residence of American eels from otolith Sr:Ca data

Linear discriminant analysis (LDA) and habitat discrimination critical value (HDCV) methods are alternatives for evaluating the migratory history, such as the proportion of residence in freshwater (%fwr) and estuarine/marine habitats, of individual American eels (Anguilla rostrata) via the analysis of otolith Sr:Ca data. The LDA process requires Sr:Ca data from both freshwater and estuarine/marine groups while the mean + cSD method requires only a freshwater standard. For the two group (freshwater, estuarine/marine), single predictor variable (Sr:Ca) case, the LDA process defaults to Fisher's linear discriminant where the HDCV equals the average of the group mean Sr:Ca values. The difference between freshwater and estuarine resident eel mean otolith Sr:Ca values, based on 13 published studies and the current study (n = 14), decreased with increasing freshwater group otolith mean (r = 0.80, p < 0.001), reflecting a relatively constant estuarine group mean (r = 0.38, p = 0.17). A process is proposed for estimating a HDCV from freshwater group otolith Sr:Ca mean and SD values based on empirical linear relations between the LDA, HDCV and freshwater mean (n = 14, r = 0.90, p < 0.0001) and c and SD (n = 14, r = −0.89, p < 0.0001) from the equation HDCV = mean + cSD. Variation in the sample sizes of otolith Sr:Ca values used in the discriminant process of estimating a HDCV, while statistically significant, had trivial effect sizes that were likely of little biological consequence. However, larger sample sizes are preferred over smaller sample sizes. Estimates of %fwr increased with increases in the HDCV. Differences in %fwr estimates over a range of HDCVs were highly statistically significant and effect sizes increased with increased HDCV difference. As HDCV levels increased, growth rate estimates increased for a given %fwr value. A HDCV difference of ≤0.5 × 10−3 produced a small effect size. Accurate estimation of a HDCV is fundamental to the assessment of the habitat residence and inter-habitat movement of American eels and perhaps of other diadromous fishes and helps minimize bias in dependent estimates of other useful statistics such as the percentage of freshwater residence (%fwr) and growth rate.

P.1.g.038 Evaluation of the effects of gamma-carboline derivatives on the brain mitochondria

Linear discriminant analysis (LDA) and habitat discrimination critical value (HDCV) methods are alternatives for evaluating the migratory history, such as the proportion of residence in freshwater (%fwr) and estuarine/marine habitats, of individual American eels (Anguilla rostrata) via the analysis of otolith Sr:Ca data. The LDA process requires Sr:Ca data from both freshwater and estuarine/marine groups while the mean + cSD method requires only a freshwater standard. For the two group (freshwater, estuarine/marine), single predictor variable (Sr:Ca) case, the LDA process defaults to Fisher's linear discriminant where the HDCV equals the average of the group mean Sr:Ca values. The difference between freshwater and estuarine resident eel mean otolith Sr:Ca values, based on 13 published studies and the current study (n = 14), decreased with increasing freshwater group otolith mean (r = 0.80, p < 0.001), reflecting a relatively constant estuarine group mean (r = 0.38, p = 0.17). A process is proposed for estimating a HDCV from freshwater group otolith Sr:Ca mean and SD values based on empirical linear relations between the LDA, HDCV and freshwater mean (n = 14, r = 0.90, p < 0.0001) and c and SD (n = 14, r = −0.89, p < 0.0001) from the equation HDCV = mean + cSD. Variation in the sample sizes of otolith Sr:Ca values used in the discriminant process of estimating a HDCV, while statistically significant, had trivial effect sizes that were likely of little biological consequence. However, larger sample sizes are preferred over smaller sample sizes. Estimates of %fwr increased with increases in the HDCV. Differences in %fwr estimates over a range of HDCVs were highly statistically significant and effect sizes increased with increased HDCV difference. As HDCV levels increased, growth rate estimates increased for a given %fwr value. A HDCV difference of ≤0.5 × 10−3 produced a small effect size. Accurate estimation of a HDCV is fundamental to the assessment of the habitat residence and inter-habitat movement of American eels and perhaps of other diadromous fishes and helps minimize bias in dependent estimates of other useful statistics such as the percentage of freshwater residence (%fwr) and growth rate.