Status of the harbour porpoise in Greenland

In Greenlandic waters the harbour porpoise (Phocoena phocoena) has been observed around the southern part of Greenland from Ammassalik on the east coast to Avanersuaq in northwest Greenland. The main distribution lies between Sisimiut and Paamiut in central west Greenland. Catch statistics from 1900 to 1993 indicate an annual average take of 668 harbour porpoises, ranging from 27 to 1531 animals. A decline in the reported catch has been recorded since 1980. Harbour porpoises are mainly caught between April and November, with a peak during June to October. Five fish species, crustaceans and squids have been found in stomach contents of harbour porpoises in Greenlandic waters. There are no indications that environmental issues such as organochlorines, heavy metals, oil or noise have constituted any threat to harbour porpoises in Greenland. No reports of ice entrapments of harbour porpoises have yet been made in Greenland, as is the case for white whales and narwhals on the west coast of Greenland. Disease patterns of harbour porpoise have not been studied in Greenland and incidents of mass mortality have never been recorded. Killer whales are sparse along the west Greenland coast and are not believed to constitute a threat to the harbour porpoise population. In Greenland no estimates on stock size are available, and a monitoring programme is needed if the impact of the catch is to be evaluated. Received: 10 February 1997 / Accepted: 26 September 1997     

Modelling geographical patterns in species richness using eigenvector-based spatial filters

Aim To test the mechanisms driving bird species richness at broad spatial scales using eigenvector‐based spatial filtering. Location South America. Methods An eigenvector‐based spatial filtering was applied to evaluate spatial patterns in South American bird species richness, taking into account spatial autocorrelation in the data. The method consists of using the geographical coordinates of a region, based on eigenanalyses of geographical distances, to establish a set of spatial filters (eigenvectors) expressing the spatial structure of the region at different spatial scales. These filters can then be used as predictors in multiple and partial regression analyses, taking into account spatial autocorrelation. Autocorrelation in filters and in the regression residuals can be used as stopping rules to define which filters will be used in the analyses. Results Environmental component alone explained 8% of variation in richness, whereas 77% of the variation could be attributed to an interaction between environment and geography expressed by the filters (which include mainly broad‐scale climatic factors). Regression coefficients of environmental component were highest for AET. These results were unbiased by short‐scale spatial autocorrelation. Also, there was a significant interaction between topographic heterogeneity and minimum temperature. Conclusion Eigenvector‐based spatial filtering is a simple and suitable statistical protocol that can be used to analyse patterns in species richness taking into account spatial autocorrelation at different spatial scales. The results for South American birds are consistent with the climatic hypothesis, in general, and energy hypothesis, in particular. Habitat heterogeneity also has a significant effect on variation in species richness in warm tropical regions.     

Modelling and predicting fungal distribution patterns using herbarium data

Aim The main aims of this study are: (1) to test if temperature and related parameters are the primary determinants of the regional distribution of macrofungi (as is commonly recognized for plants); (2) to test if the success of modelling fungal distribution patterns depends on species and distribution characteristics; and (3) to explore the potential of using herbarium data for modelling and predicting fungal species’ distributions. Location The study area, Norway, spans 58–71° N latitude and 4–32° E longitude, and embraces extensive ecological gradients in a small area. Methods The study is based on 1020 herbarium collections of nine selected species of macrofungi and a set of 75 environmental predictor variables, all recorded in a 5 × 5‐km grid covering Norway. Primarily, generalized linear model (GLM; logistic regression) analyses were used to identify the environmental variables that best accounted for the species’ recorded distributions in Norway. Second, Maxent analyses (using variables identified by GLM) were used to produce predictive potential distribution maps for these species. Results Variables relating to temperature and radiation were most frequently included in the GLMs, and between 24.8% and 59.8% of the variation in single‐species occurrence was accounted for. The fraction of variation explained by the GLMs ranged from 41.6% to 59.8% for species with restricted distributions, and from 24.8% to 39.3% for species with widespread/scattered and intermediate distributions. The two‐step procedure of GLM followed by Maxent gave predictions with very high values for the area under the curve (0.927–0.997), and maps of potential distribution were generally credible. Main conclusions We show that temperature is a key factor governing the distribution of macrofungi in Norway, indicating that fungi may respond strongly to global warming. We confirm that modelling success depends partly on species and distribution characteristics, notably on how the distribution relates to the extent of the study area. Our study demonstrates that the combination of GLM and Maxent may be a fruitful approach for biogeography. We conclude that herbarium data improve insight into factors that control the distributions of fungi, of particular value for research on fleshy fungi (mushrooms), which have largely cryptic life cycles.     

Modelling spatial patterns in host-associated microbial communities

Microbial communities exhibit spatial structure at different scales, due to constant interactions with their environment and dispersal limitation. While this spatial structure is often considered in studies focusing on free-living environmental communities, it has received less attention in the context of host-associated microbial communities or microbiota. The wider adoption of methods accounting for spatial variation in these communities will help to address open questions in basic microbial ecology as well as realize the full potential of microbiome-aided medicine. Here, we first overview known factors affecting the composition of microbiota across diverse host types and at different scales, with a focus on the human gut as one of the most actively studied microbiota. We outline a number of topical open questions in the field related to spatial variation and patterns. We then review the existing methodology for the spatial modelling of microbiota. We suggest that methodology from related fields, such as systems biology and macro-organismal ecology, could be adapted to obtain more accurate models of spatial structure. We further posit that methodological developments in the spatial modelling and analysis of microbiota could in turn broadly benefit theoretical and applied ecology and contribute to the development of novel industrial and clinical applications.     

Migratory connectivity of American woodcock derived using satellite telemetry

American woodcock (Scolopax minor; woodcock) migratory connectivity (i.e., association between breeding and wintering areas) is largely unknown, even though current woodcock management is predicated on such associations. Woodcock are currently managed in the Eastern and Central management regions in the United States with the boundary between management regions analogous to the boundary between the Atlantic and Mississippi flyways, based largely on analysis of band returns from hunters. Factors during migration influence survival and fitness, and existing data derived from banding and very high frequency telemetry provide only coarse-scale information to assess factors influencing woodcock migratory movement patterns and behavior. To assess whether current management-region boundaries correspond with woodcock migratory connectivity in the Central Management Region and to describe migration patterns with higher resolution than has been previously possible, we deployed satellite transmitters on 73 woodcock (25 adult and 28 juvenile females, and 8 adult and 12 juvenile males) and recorded 87 autumn or spring migration paths from 2014 to 2016. Marked woodcock used 2 primary migrations routes: a Western Route and a Central Route. The Western Route ran north-south, connecting the breeding and wintering grounds within the Central Management Region. The hourglass-shaped Central Route connected an area on the wintering grounds reaching from Texas to Florida, to sites throughout northeastern North America in both the Eastern Management Region and Central Management Region and woodcock following this route migrated through the area between the Appalachian Mountains and the Mississippi Alluvial Valley in western Tennessee during autumn and spring. Two of 17 woodcock captured associated with breeding areas in Michigan, Wisconsin, or Minnesota migrated to wintering sites in the Eastern Management Region and 12 marked woodcock captured on wintering areas in Texas and Louisiana migrated to breeding sites in the Eastern Management Region. Woodcock that used the Western Route exhibited high concentrations of stopovers during spring in the Arkansas Ozark Mountains and northern Missouri, and along the Mississippi River on the border between Wisconsin and Minnesota, and autumn concentrations of stopovers in southwestern Iowa, central Missouri, the Arkansas portion of the Ozark Mountains, and around the junction of Texas, Louisiana, Oklahoma, and Arkansas. Woodcock that used the Central Route exhibited high concentrations of stopovers during spring in northern Mississippi through western Tennessee, western Kentucky, and the Missouri Bootheel, and autumn concentrations of stopovers in northern Illinois, southwestern Ohio, and the portions of Kentucky and Tennessee west of the Appalachian Mountains. We suggest that current management of woodcock based on 2 management regions may not be consistent with the apparent lack of strong migratory connectivity we observed. Our results also suggest where management of migration habitat might be most beneficial to woodcock. © 2019 The Wildlife Society.     

Variation in harbour porpoise activity in response to seismic survey noise

Animals exposed to anthropogenic disturbance make trade-offs between perceived risk and the cost of leaving disturbed areas. Impact assessments tend to focus on overt behavioural responses leading to displacement, but trade-offs may also impact individual energy budgets through reduced foraging performance. Previous studies found no evidence for broad-scale displacement of harbour porpoises exposed to impulse noise from a 10 day two-dimensional seismic survey. Here, we used an array of passive acoustic loggers coupled with calibrated noise measurements to test whether the seismic survey influenced the activity patterns of porpoises remaining in the area. We showed that the probability of recording a buzz declined by 15% in the ensonified area and was positively related to distance from the source vessel. We also estimated received levels at the hydrophones and characterized the noise response curve. Our results demonstrate how environmental impact assessments can be developed to assess more subtle effects of noise disturbance on activity patterns and foraging efficiency.     

Inferring climatic controls of rice stem borers’ spatial distributions using maximum entropy modelling

Accurate assessment of pest potential distributions is needed to identify their establishment risks that play a key role in pest management in agricultural ecosystems. We used a correlative niche modelling method (Maxent) to predict and map the spatial distributions of two important rice stem borers, Chilo suppressalis and Sesamia cretica, in paddy fields of Iran. In total, 195 presence occurrence records (101 records for C. suppressalis and 94 records for S. cretica) were compiled. A set of environmental and topographic variables, with the highest effects on the species distributions and the lowest correlations among themselves, were used. The results showed that mainly the northern parts of Iran were the most suitable areas for C. suppressalis, and north, north‐east and south‐west of Iran as the most suitable areas for S. cretica. Both models performed well, with an area under the receiver operating characteristic curve (AUC) of 0.983 and 0.786 for C. suppressalis and S. cretica, respectively. The Maxent models showed higher accuracy for predicting the distribution of the specialist pest with the small range sizes compared to the generalist species. Assessing the importance of environmental variables, which were derived from the jackknife test, showed the precipitation as the variable with the highest contribution (66%) in explaining the spatial distribution of C. suppressalis compared to the other variables. The distribution of S. cretica was influenced by a set of variables derived from both the precipitation and temperature. The Maxent predictions were useful to map the geographical distributions of the risk for both rice stem borers that is needed to develop effective management strategies.     

A maximum entropy analysis of protein orientations using fluorescence polarization data from multiple probes

Techniques have recently become available to label protein subunits with fluorescent probes at predetermined orientation relative to the protein coordinates. The known local orientation enables quantitative interpretation of fluorescence polarization experiments in terms of orientation and motions of the protein within a larger macromolecular assembly. Combining data obtained from probes placed at several distinct orientations relative to the protein structure reveals functionally relevant information about the axial and azimuthal orientation of the labeled protein segment relative to its surroundings. Here we present an analytical method to determine the protein orientational distribution from such data. The method produces the broadest distribution compatible with the data by maximizing its informational entropy. The key advantages of this approach are that no a priori assumptions are required about the shape of the distribution and that a unique, exact fit to the data is obtained. The relative orientations of the probes used for the experiments have great influence on information content of the maximum entropy distribution. Therefore, the choice of probe orientations is crucial. In particular, the probes must access independent aspects of the protein orientation, and two-fold rotational symmetries must be avoided. For a set of probes, a "figure of merit" is proposed, based on the independence among the probe orientations. With simulated fluorescence polarization data, we tested the capacity of maximum entropy analysis to recover specific protein orientational distributions and found that it is capable of recovering orientational distributions with one and two peaks. The similarity between the maximum entropy distribution and the test distribution improves gradually as the number of independent probe orientations increases. As a practical example, ME distributions were determined with experimental data from muscle fibers labeled with bifunctional rhodamine at known orientations with respect to the myosin regulatory light chain (RLC). These distributions show a complex relationship between the axial orientation of the RLC relative to the fiber axis and the azimuthal orientation of the RLC about its own axis. Maximum entropy analysis reveals limitations in available experimental data and supports the design of further probe angles to resolve details of the orientational distribution.     

Classification of heterogeneous microarray data by maximum entropy kernel

Background  

There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are commonly used in microarray analyses with support vector machines (SVMs) to approach a wide range of classification problems. However, the standard vectorial data kernel family (linear, RBF, etc.) that takes vectorial data as input, often fails in prediction if the data come from different platforms or laboratories, due to the low gene overlaps or consistencies between the different datasets.     

Modelling the spatial distribution of wildlife animals using presence and absence data

This study was conducted to analyze the habitat preference of six major mammals for various environmental factors based on 100 random points within a mountain area in South Korea. In-situ presence and absence data for the mammals were surveyed and collected, and twelve explanatory variables related to topography, water, greenness, and anthropogenic influence were applied to create a habitat distribution model. The best combination of variables was determined using Moran’s I coefficients and Akaike criteria information, and applied to estimate the habitat preference for each species using GRASP v.3.0. The predictive map showed that wildlife animals in this study were mainly categorized into two groups: Group I (Korean squirrel, Sciurus vulgaris, mole, Talpa micrura and water deer, Hydropotes inermis), showed equal preference for all mountainous areas; Group II (weasel, Mustela sibirica, leopard cat, Felis bengalensis and raccoon dog, Nyctereutes procyonoides) showed different preferences in a mountain.     

Characterization of nucleotidic sequences using maximum entropy techniques

A statistical method for characterizing nucleotidic sequences based on maximum entropy techniques is presented. The method uses only codon usage tables and takes into account the length of sequences, and preserves the information contained in each codon by a punctual index. We present the methodological aspects of the analysis, showing an application relative to nucleotidic sequences of eukaryotes.     

Gas exchange and heart rate in the harbour porpoise, Phocoena phocoena

The respiratory physiology, heart rates and metabolic rates of two captive juvenile male harbour porpoises (both 28 kg) were measured using a rapid-response respiratory gas analysis system in the laboratory. Breath-hold durations in the laboratory (12 ± 0.3 s, mean ± SEM) were shorter than field observations, although a few breath-holds of over 40 s were recorded. The mean percentage time spent submerged was 89 ± 0.4%. Relative to similarly-sized terrestrial mammals, the respiratory frequency was low (4.9 ± 0.19 breaths · min⁻¹) but with high tidal volumes (1.1 ± 0.01 l), enabling a comparatively high minute rate of gas exchange. Oxygen consumption under these experimental conditions (247 ± 13.8 ml O₂ · min⁻¹) was 1.9-fold higher than predicted by standard scaling relations. These data together with an estimate of the total oxygen stores predicted an aerobic dive limit of 5.4 min. The peak end-tidal O₂ values were related to the length of the previous breath-hold, demonstrating the increased oxygen uptake from the lung for the longer dives. Blood oxygen capacity was 23.5 ± 1.0 ml · 100 ml⁻¹, and the oxygen affinity was high, enabling rapid oxygen loading during ventilation. Accepted: 11 August 1999     

Population structure of bycaught harbour porpoise (Phocoena phocoena) in Norway

ABSTRACT

The preference for coastal habitats makes the harbour porpoise, Phocoena phocoena, vulnerable to fisheries conflicts and hence prone to die due to entangling in fishing nets. An opportunistic sampling of such casualties (134 individuals) in Norwegian waters was used to assess the genetic population structure of the species by SNP-genotyping at 78 loci. The results of genetic clustering obtained for these individuals failed to identify more than one genetic group. Likewise, the individually-based F did not meet an Isolation-by-Distance pattern, thus supporting the conclusion that harbour porpoise in Norway probably belongs to a single genetic group or population.     

Modelling relationships between species spatial abundance patterns and climate

Aim To move towards modelling spatial abundance patterns and to evaluate the relative impacts of climatic change upon species abundances as opposed to range extents. Location Southern Africa, including Lesotho, Namibia, South Africa, Swaziland and Zimbabwe. Methods Quantitative response surface models were fitted for 78 bird species, mostly endemic (68) or near‐endemic to the region, to model relationships between species reporting rates (i.e. the proportion of checklists reporting a species for a particular grid cell), as recorded by the Southern African Bird Atlas Project, and four bioclimatic variables derived from climatic data for the period 1961–90. With caution, reporting rates can be used as a proxy for abundance. Models were used to project potential impacts of a series of projected climatic change scenarios upon species abundance patterns and range extents. Results Most models obtained were robust with good predictive power. Projections of potential future abundance patterns indicate that the magnitude of impacts upon a proxy for abundance are greater than those upon range extent for the majority of species (82% by 2071–2100). For most species (74%) both abundance and range extent are projected to decrease by 2100. Impacts are especially severe if species are unable to realize projected range changes; when only the area of a species' simulated present range is considered, overall abundance decreases of more than 80% are projected for 19 (24%) of species examined. Main conclusions Our results indicate that projected climatic changes are likely to elicit greater relative changes in species abundances than range extents. For most species examined changes were decreases, suggesting the impacts upon biodiversity are likely generally to be negative. These results also suggest that previous estimates of the proportion of species at increased risk of extinction as a result of climatic change may, in some cases, be under‐estimates.     

Geographical variation in temporal and spatial vocalization patterns of male harbour seals in the mating season

In the aquatically mating harbour seal, Phoca vitulina, oestrous females show marked differences in spatial and temporal distribution between geographical areas. This suggests that the males' display behaviour may also vary between areas. We recorded male vocalizations in two areas, the Moray Firth and Orkney, U.K. In the Moray Firth, females haul out on a few intertidal sandbars and travel along predictable routes to forage at sea. In Orkney, female haul out sites are much less influenced by tidal availability and females are much more dispersed. In the Moray Firth, males vocalized only during a short mating season, from 1 July to 12 August. Vocalizations varied significantly with the tide, the peak at high tide clearly coinciding with the period when most females were in the water. In contrast, vocalizations in Orkney were significantly related to both tidal and diel patterns. We suggest that the timing of male vocalizations reflects differences in female availability between sites. In the inner Moray Firth, vocalizations were heard throughout the females' range, whereas vocalizations in Orkney were heard only in two discrete areas. However, at both sites the density of vocalizing males was highest in narrow channels and/or along predictable female travel routes. Therefore, males clearly adapt their temporal and spatial behaviour patterns to variations in female distribution and density. These results suggest that male mating strategies in aquatically mating pinnipeds are more variable than was previously envisaged. Copyright 1999 The Association for the Study of Animal Behaviour.     

Modelling spatial patterns of biodiversity for conservation prioritization in North-eastern Mexico

Relationships between spatial patterns of bird and mammal species richness in north‐eastern Mexico were analysed in relation to the location of three biosphere reserves (El Abra‐Tanchipa, El Cielo, and Sierra Gorda) and 13 priority areas recently identified for conservation. Ecological niches were modelled and potential distributions delimited for 285 bird and 114 mammal species using a genetic algorithm based on locality information from museum specimens and 15 selected environmental attributes. Potential distributions were transformed into hypothesized current distributions based on species–habitat associations as reflected in a recent land‐use map. Although species richness was lower when distributions were reduced from potential to current, spatial patterns of potential and current richness were similar. Heuristic, complementarity‐based prioritization procedures were used to identify combinations of areas and sites with maximal species representation: the biosphere reserves included 79% of birds and 74% of mammal species; eight priority areas provided an additional 11% of birds and 13% of mammals; the remaining 10% of birds and 13% of mammals were concentrated in new sites across the study area.     

Granulosa cell tumour in a harbour porpoise (Phocoena phocoena) from German waters

Neoplastic diseases in harbour porpoises Phocoena phocoena have rarely been described, and there are no reported gonadal stromal tumours. A 12 yr old female harbour porpoise was stranded on the North Sea coast of Schleswig-Holstein, Germany. Necropsy findings included a severe granulomatous pneumonia, pregnancy and a left ovarian tumour. Respiratory insufficiency was the likely cause of death. There was a multinodular mass composed of cords with peripherally palisading cells within the left ovary. The histological and cytological appearance of the neoplasm was suggestive of a granulosa cell tumour; supportive immunohistochemical stains, including those for vimentin, cytokeration, carcinoembryonic antigen, c-kit, chromogranin and α-smooth muscle action, were negative.     

Trends of harbour porpoise (Phocoena phocoena) density in the southern North Sea

In the southern North Sea, harbour porpoise occurrence increased in recent years after a phase of low abundances during earlier decades. Only very few studies on porpoise presence in the southern German North Sea exist so far. As anthropogenic activities will strongly increase in this part of the North Sea during the next years it is most important to assess population level effects. This study focuses on the analysis of temporal and spatial trends in porpoise density in this area of recent change. Dedicated aerial line-transect distance sampling surveys were conducted in the southern German North Sea between May 2002 and June 2013 to assess porpoise density and distribution. Statistical inferences on porpoise population trends were made using a Markov Chain Monte Carlo (MCMC) technique. Two approaches were chosen to test for a trend in porpoise density and an additional model focused on the change in density of calves. During 55,820 km of survey effort 4377 porpoises including 140 calves were recorded. A significant effect of increasing spatial aggregation from the lower density areas in the south-eastern German Bight to hot spot areas in the western parts was detected. For the western part of the study area a significant increase in porpoise density between 2002 and 2013 was detected. Seasons were significantly different with highest porpoise density in spring and successively decreasing densities in summer and autumn. From 2008 onwards high densities were also observed in summer. Calf density increased during the study period and was significantly higher in the west. On the basis of this extensive and unique data set on porpoise occurrence in the southern German North Sea the findings clearly show that especially the south-western German North Sea serves as habitat of increasing importance for porpoises throughout the last decade. Definite reasons still remain unresolved. Changes in prey abundance or less favourable conditions in other areas could be important factors, which may also have caused a southward shift from high density areas in northern waters. On this baseline, further integrative approaches might lead to a sound understanding of the effect of anthropogenic activities on the future development of porpoise populations.