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opencc-zeroJun 2019View details →

Data from: The influence of habitat and adults on the spatial distribution of juvenile corals

Population distributions are affected by a variety of spatial processes, including dispersal, intraspecific dynamics, and habitat selection. Within reef-building coral communities, these processes are especially important during the earliest life stages when reproduction provides mobility among sessile organisms and populations experience the greatest mortality bottlenecks both before and immediately after settlement. Here, we used large-area imaging to create photomosaics that allowed us to identify and map the location of 4,681 juvenile (1-5 cm diameter) and 25,902 adult (>5 cm diameter) coral colonies from eight 100m2 plots across the forereef of Palmyra Atoll. Using metrics of density, percent cover, and the relative location of each colony within each plot, we examined abundance and spatial relationships between juvenile and adult coral taxa. Within coral taxa, juvenile density was generally positively related to the numerical density and percent cover of adults. Nearest neighbor analyses showed aggregation of juveniles near adults of the same taxon for two of the focal taxa (Pocillopora and Fungiids), while all other taxa showed random spatial patterning relative to adults. Three taxa had clustered distributions of juveniles overall. Additionally, we found that on a colony level, juveniles for five of nine focal taxa (accounting for >98% of all identified juveniles) associated with a specific habitat type, with four of those five taxa favoring unconsolidated (e.g., rubble) over consolidated substrata. The general lack of clustering in juvenile corals contrasts with consistent clustering patterns seen in adult corals, suggesting that adult spatial patterns are largely driven by processes occurring after maturity such as partial colony mortality, including fission and fragmentation. The association of many taxa with unconsolidated habitat also suggests that corals may play an important role in colonizing natural rubble patches that could contribute to reef stabilization over time.

opencc-zeroAug 2020View details →

Supplementary material 2 from: Krajewski Ł, Adamec L, Saługa M, Bednarek-Ochyra H, Plášek V (2020) Welcome to the Czech Republic again! Rare northern mosses Calliergon megalophyllum and Drepanocladus sordidus (Amblystegiaceae) in South Bohemia in light of their European distribution and habitat preferences. PhytoKeys 154: 111-136. https://doi.org/10.3897/phytokeys.154.51454

A comparison of phytosociological releves from world sites of Calliergon megalophyllum (and Drepanocladus sordidus) from the present and literature data

opennotspecifiedMay 2020View details →

FIGURE 1 in Chironomidae (Diptera) of Croatia with notes on the diversity and distribution in various habitat types

FIGURE 1. Distribution of sampling sites throughout Croatia. Site codes: 1. Kopačko lake, Kopački Rit; 2. Sakadaš lake, Kopački Rit; 3. Biljsko lake, Bilje; 4. Đola, Darda; 5. Fountain I, Osijek; 6. Fountan II, Osijek; 7. Fountain III, Osijek; 8. Jug II urban pond, Osijek; 9. Kupska urban pond, Osijek; 10. Getro urban pond, Osijek; 11. Drava, Osijek; 12. Karašica, Črnkovci; 13. Lapovac; 14. Jošava; 15. Sava, Slavonski Šamac; 16. Sava, Slavonski Brod; 17. Jovanovica, Papuk; 18. Brzaja, Papuk; 19. Sjeverna Pakra; 20. Ljuta Pakra; 21. Rogljica, Psunj; 22. Šumetlica, Psunj; 23. Orljava, Slavonski Kobaš; 24. Sava, Davor; 25. Mura, Goričan; 26. Šoderica, Koprivnica; 27. Drava, Botovo; 28. Česma, Narta; 29. Popovac; 30. Pakra reservoir; 31. Sava, Jasenovac; 32. Fountain, Varaždin; 33. Aqucity, Varaždin; 34. Drava, Varaždin; 35. Danube, upstream Drava; 36. Sutla, Lu- pinjak; 37. Sutla, Zelenjak; 38. Sava, Drenje Brdovečko; 39. Sava, near Bregana; 40. Sava, Podsused; 41. Rakitje; 42. Jarun, Zagreb; 43. Sava, Ščitarjevo; 44. Novo Čiće; 45. Sava, Oborovo; 46. Sava, Dubrovčak; 47. Sava, Tišina; 48. Sava, Galdovo; 49. Kupa, Petrinja; 50. Stupnica, Gornja Stupnica; 51. Kupa, Ozalj-Mahićno; 52. Dobra, Novigrad na Dobri; 53. Mrežnica, Karlovac; 54. Mrežnica, Belavići; 55. Korana, Ladvenjak; 56. Mrežnica, Zvečaj; 57. Dobra, Skukani; 58. Dobra, Gorinci; 59. Dobra, Podumol; 60. Dobra, Lešće; 61. Globornica, Dobrenići; 62. Dobra, Trošmarija; 63. Turpinjska rijeka, Grabovac Krnjački; 64. Korana, Veljun; 65. Sabljaci; 66. Slunjčica, Rastoke; 67. Dobra, Vrbovsko; 68. Dobra, Gornja Dobra; 69. Dobra, izvorište Hlevci; 70. Kupa, Brod na Kupi; 71. Čabranka, Zamost; 72. Križ potok; 73. Lokve reservoir; 74. Rječina spring;75. Tribalj; 76. Jezero Njivice; 77. Ponikve, Krk; 78. Vransko jezero, Cres; 79. Boljunčica izvor; 80. Mirna izvor; 81. Butoniga jezero; 82. Butoniga izvor; 83. Mirna, Istarske toplice; 84. Mirna, Ponte Porton; 85. Rovinj; 86. Kozjak; 87. Crna rijeka spring; 88. Bijela Rijeka spring; 89. Vrba, Ramljani; 90. Gacka, Čovići; 91. Lukina jama; 92. Brušanka; 93. Počiteljica, Ornice; 94. Opsenice Sv. Rok; 95. Štikada; 96. Otuča, Gračac; 97. Butišnica spring; 98. Krupa spring; 99. Zrmanja, Ervenik- ušće u Krupu; 100. Butišnica, Golubić; 101. Radljevac; 102. Zrmanja, Palanka; 103. Zrmanja, Palanka– Ervenik; 104. Razovac reservoir; 105. Vlačine reservoir; 106. Peruća reservoir; 107. Krka, Roški slap; 108. Visovac; 109. Guduća, Bribišnica; 110. Vransko jezero, Biograd na moru; 111. Zeleno jezero; 112. Prološko Blato; 113. Rijeka Jadro spring; 114. Prančevići reservoir; 115. Rijeka Ma- tica, Vrgorac; 116. Neretva delta; 117. Sobra, Blatina; 118. Ljuta, Konavle; 119. Danube, Erdut.

opencc-zeroDec 2015View details →

Data from: Distribution of the invasive Caprella mutica Schurin, 1935 and native Caprella linearis (Linnaeus, 1767) on artificial hard substrates in the North Sea: separation by habitat

Studying offshore natural and artificial hard substrates in the southern North Sea (51ºN–57ºN/1ºW–9ºE), the invasive introduced Japanese skeleton shrimp Caprella mutica Schurin, 1935 was found to co-exist with the native Caprella linearis (Linnaeus, 1767) only on near-shore locations that had an intertidal zone (e.g., wind farm foundations). In contrast, on far offshore and strictly subtidal locations, such as shipwrecks and rocky reefs, only C. linearis was found. Based on these exploratory observations, we hypothesised that artificial structures that are only subtidal are inhabited exclusively by C. linearis, and never by C. mutica. To test this hypothesis and understand factors driving each species' habitat preferences, habitat suitability models were constructed using generalised additive models, based on samples collected in 2013–2015 from offshore gas platforms, buoys, shipwrecks, and rocky reefs and combined with data from other published and unpublished surveys (2001–2014). The models showed that the presence of C. mutica is explained by the availability of intertidal and floating hard substrates, suspended particulate matter density (SPM), mean annual sea surface temperature, salinity, and current velocity. The C. linearis model included subtidal hard substrates, SPM, salinity, temperature, and current velocity. The modelled distributions showed a significant difference, demonstrating that C. linearis' habitat preference does not fully overlap with that of C. mutica. Thus, the native and alien Caprella species are likely to be able to co-exist in the North Sea.

opencc-zeroJul 2019View details →

Data from: Revisiting the functional response in habitat selection for large herbivores: a matter of spatial variation in resource distribution?

Most habitats are distributed heterogeneously in space, forcing animals to move according to both habitat characteristics and their needs for energy and safety. Animal space use should therefore vary according to habitat characteristics, a process known as the "functional response" in habitat selection. This response has often been tested vis-à-vis the proportion of a habitat category within areas available to individuals. Measuring sought-after resources in landscape where they are continuously distributed is a challenge and we posit here that both the mean availability of a resource and its spatial variation should be measured. Accordingly, we tested for a functional response in habitat selection according to these two descriptors of the resource available for a mountain herbivore. We hypothesized that selection should decrease with mean value of resources available and increase with its spatial variation. Based on GPS data from 50 chamois females and data on the actual foodscape (i.e. distribution of edible-only biomass in the landscape), we estimated individual selection ratio (during summer months) for biomass at the home range level, comparing edible biomass in individual home ranges and the mean and standard deviation of edible biomass in their available range. Chamois being a group-living species, available accessible ranges were shared by several individuals that formed socio-spatial groups (clusters) in the population. As expected, selection ratios increased with the standard deviation of edible resources in each cluster, but unlike our prediction, was unrelated to its mean. Selection of areas richer in resources hence did not fade away when more resources were available on average, a result that may be explained by the need for this capital breeder species to accumulate fat-reserve at a high rate during summer months. Low spatial variation could limit the selection of chamois, which highlights the importance of resource distribution in the process of habitat selection.

opencc-zeroDec 2014View details →

Data from: The influence of data resolution on predicted distribution and estimates of extent of current protection of three 'listed' deep-sea habitats

Modelling approaches have the potential to significantly contribute to the spatial management of the deep-sea ecosystem in a cost effective manner. However, we currently have little understanding of the accuracy of such models, developed using limited data, of varying resolution. The aim of this study was to investigate the performance of predictive models constructed using non-simulated (real world) data of different resolution. Predicted distribution maps for three deep-sea habitats were constructed using MaxEnt modelling methods using high resolution multibeam bathymetric data and associated terrain derived variables as predictors. Model performance was evaluated using repeated 75/25 training/test data partitions using AUC and threshold-dependent assessment methods. The overall extent and distribution of each habitat, and the percentage contained within an existing MPA network were quantified and compared to results from low resolution GEBCO models. Predicted spatial extent for scleractinian coral reef and Syringammina fragilissima aggregations decreased with an increase in model resolution, whereas Pheronema carpenteri total suitable area increased. Distinct differences in predicted habitat distribution were observed for all three habitats. Estimates of habitat extent contained within the MPA network all increased when modelled at fine scale. High resolution models performed better than low resolution models according to threshold-dependent evaluation. We recommend the use of high resolution multibeam bathymetry data over low resolution bathymetry data for use in modelling approaches. We do not recommend the use of predictive models to produce absolute values of habitat extent, but likely areas of suitable habitat. Assessments of MPA network effectiveness based on calculations of percentage area protection (policy driven conservation targets) from low resolution models are likely to be fit for purpose.

opencc-zeroDec 2014View details →

Data from: Predictive modelling of habitat selection by marine predators with respect to the abundance and depth distribution of pelagic prey

1. Understanding the ecological processes that underpin species distribution patterns is a fundamental goal in spatial ecology. However, developing predictive models of habitat use is challenging for species that forage in marine environments, as both predators and prey are often highly mobile and difficult to monitor. Consequently, few studies have developed resource selection functions for marine predators based directly on the abundance and distribution of their prey. 2. We analysed contemporaneous data on the diving locations of two seabird species, the shallow-diving Peruvian Booby (Sula variegata) and deeper diving Guanay Cormorant (Phalacrocorax bougainvilliorum), and the abundance and depth distribution of their main prey, Peruvian anchoveta (Engraulis ringens). Based on this unique data set, we developed resource selection functions to test the hypothesis that the probability of seabird diving behaviour at a given location is a function of the relative abundance of prey in the upper water column. 3. For both species, we show that the probability of diving behaviour is mostly explained by the distribution of prey at shallow depths. While the probability of diving behaviour increases sharply with prey abundance at relatively low levels of abundance, support for including abundance in addition to the depth distribution of prey is weak, suggesting that prey abundance was not a major factor determining the location of diving behaviour during the study period. 4. The study thus highlights the importance of the depth distribution of prey for two species of seabird with different diving capabilities. The results complement previous research that points towards the importance of oceanographic processes that enhance the accessibility of prey to seabirds. The implications are that locations where prey is predictably found at accessible depths may be more important for surface foragers, such as seabirds, than locations where prey is predictably abundant. 5. Analysis of the relative importance of abundance and accessibility is essential for the design and evaluation of effective management responses to reduced prey availability for seabirds and other top predators in marine systems.

opencc-zeroDec 2014View details →

Data from: Assessing cumulative impacts of forest development on the distribution of furbearers using expert-based habitat modeling

Cumulative impacts of anthropogenic landscape change must be considered when managing and conserving wildlife habitat. Across the central-interior of British Columbia, Canada, industrial activities are altering the habitat of furbearer species. This region has witnessed unprecedented levels of anthropogenic landscape change following rapid development in a number of resource sectors, particularly forestry. Our objective was to create expert-based habitat models for three furbearer species: fisher (Pekania pennanti), Canada lynx (Lynx canadensis), and American marten (Martes americana) and quantify habitat change for those species. We recruited 10 biologist and 10 trapper experts and then used the analytical hierarchy process to elicit expert knowledge of habitat variables important to each species. We applied the models to reference landscapes (i.e., registered traplines) in two distinct study areas and then quantified the change in habitat availability from 1990 to 2013. There was strong agreement between expert groups in the choice of habitat variables and associated scores. Where anthropogenic impacts had increased considerably over the study period, the habitat models showed substantial declines in habitat availability for each focal species (78% decline in optimal fisher habitat, 83% decline in optimal lynx habitat, and 79% decline in optimal marten habitat). For those traplines with relatively little forest harvesting, the habitat models showed no substantial change in the availability of habitat over time. The results suggest that habitat for these three furbearer species declined significantly as a result of the cumulative impacts of forest harvesting. Results of this study illustrate the utility of expert knowledge for understanding large-scale patterns of habitat change over long time periods.

opencc-zeroDec 2011View details →

Data from: Distribution models and a dated phylogeny for Chilean Oxalis species reveal occupation of new habitats by different lineages, not rapid adaptive radiation

Among the World's most challenging environments for plant life is the Atacama Desert, an arid zone extending over 1300 km and from sea level to 2000/3000 m along the southwestern Andean foothills. Plants there and in the adjacent Mediterranean zone exhibit striking adaptations, and we here use a species-rich such group to address the question whether adaptations arose in parallel, at different times, or simultaneously. Answering this type of question has been a major concern of evolutionary biology over the past few years, with a growing consensus that lineages tend to be conservative in their vegetative traits and niche requirements. Combined nuclear and chloroplast DNA sequences for 112 species of Oxalidales (4900 aligned nucleotides) yielded a fossil-calibrated phylogeny that includes 43 of the 54 species of Oxalis occurring in Chile. Distribution models (SDMs) for these species that included precipitation, temperature, fog and/or vegetation types and the phylogeny were used to reconstruct ancestral habitat preferences, relying on likelihood and Bayesian techniques. Since uneven collecting can reduce the power of SDMs, we used a background sample from 1224 Chilean Oxalis collections to correct models for collecting effort. Models with just 10 of 19 bioclim parameters did as well as more parameter-rich models. Results reveal that the Oxalis flora of Chile consists of seven distant lineages that originated at different times prior to the last Andean uplift pulse and some of which had features pre-adapting them to seasonally arid or xeric conditions. The Mediterranean core zone, south of the Atacama, offered an ecological refuge for insufficiently arid-adapted species and harbors a mix of ancient and young groups. There is no evidence of rapid adaptive radiation.

opencc-zeroDec 2018View details →

Data from: Human traffic and habitat complexity are strong predictors for the distribution of a declining amphibian

Invasive species and habitat modification threaten California's native pond-breeding amphibians, including the federally threatened California Red-legged Frog (Rana draytonii). The relative contributions of invasive species, including the American Bullfrog (Lithobates catesbeianus), and of habitat changes to these declines are disputed. I conducted a field study over several years in central California to examine the presence/absence of these two species at 79 breeding ponds to determine the predictive role for occupancy of factors including vegetation, pond characteristics, and measures of human activity. I used a boosted regression tree approach to determine the relative value of each predictor variable. Increased measures of human activity, especially proximity to trails and roads, were the best predictors for the absence of California Red-legged Frogs and California Newts. Historical factors and habitat conditions were associated with the extent and spread of the American Bullfrog. The extent and complexity of aquatic macrophytes and pond surface area were good predictors for the presence of these and other amphibian species. Surprisingly, invasive species played a relatively small role in predicting pond occupancy by the native species. These findings can inform conservation and restoration efforts for California Red-legged Frogs, which apparently persist best in small vegetated ponds in areas of low human disturbance.

opencc-zeroDec 2012View details →

Data from: Stepping-stone expansion and habitat loss explain a peculiar genetic structure and distribution of a forest insect

It is challenging to unravel the history of organisms with highly scattered populations. Such species may have fragmented distributions because extant populations are remnants of a previously more continuous range, or because the species has narrow habitat requirements in combination with good dispersal capacity (naturally or vector borne). The northern pine processionary moth Thaumetopoea pinivora has a scattered distribution with fragmented populations in two separate regions, northern and south-western Europe. The aims of this study were to explore the glacial and postglacial history of T. pinivora, and add to the understanding of its current distribution and level of contemporary gene flow. We surveyed published records of its occurrence and analysed individuals from a representative subset of populations across the range. A 633 bp long fragment of the mtDNA COI gene was sequenced and nine polymorphic microsatellite loci were genotyped. Only nine nucleotide sites were polymorphic in the COI gene and 90% of the individuals from across its whole range shared the same haplotype. The microsatellite diversity gradually declined towards the north, and unique alleles were found in only three of the northern and three of southern sites. Genetic structuring did not indicate complete isolation among regions, but an increase of genetic isolation by geographic distance. Approximate Bayesian model choice suggested recent divergence during the postglacial period, but glacial refugia remain unidentified. The progressive reduction of suitable habitats is suggested to explain the genetic structure of the populations and we suggest that T. pinivora is a cold-tolerant relict species, with situation-dependent dispersal.

Figure 6 in Mollusk distribution in four habitats along a salinity gradient in a coastal lagoon from the Gulf of Mexico

Figure 6. PCA plot showing relationships between environmental variables and molluscan assemblages from Mecoacan lagoon. Numbers represent sites, black dots = cold fronts season, open triangles = drought season, and black squares = rainy season. Sal: salinity; OD: dissolved oxygen; TDS: turbidity; Temp: temperature.

Figure 4 in Mollusk distribution in four habitats along a salinity gradient in a coastal lagoon from the Gulf of Mexico

Figure 4. MDS plot of bootstrap averages showing variations of molluscan assemblages by habitat. Ellipses denote approximate 95% confidence intervals and black symbols represent averages (av).

Figure 5 in Mollusk distribution in four habitats along a salinity gradient in a coastal lagoon from the Gulf of Mexico

Figure 5. MDS plot of bootstrap averages showing variations of molluscan assemblages by sites nested within a) ARE, b) MAN, c) VAS, and d) RAI. Ellipses denote approximate 95% confidence intervals and black symbols represent averages (av).

Figure 3 in Mollusk distribution in four habitats along a salinity gradient in a coastal lagoon from the Gulf of Mexico

Figure 3. MDS plot of bootstrap averages showing variation in molluscan assemblages by climatic season: cold fronts (triangles), drought (circles) and rainy (diamonds). Ellipses denote approximate 95% confidence intervals and black symbols represent averages (av).

Figure 2 in Mollusk distribution in four habitats along a salinity gradient in a coastal lagoon from the Gulf of Mexico

Figure 2. PCO showing the ordination of water environmental variables from Mecoacan lagoon. Numbers represent sites, black dots = cold fronts season, black squares = drought season, and black triangles = rainy season.

opennotspecifiedJun 2013View details →

FIGURE 3. a in A long-lost relic from the Eastern Ghats: Morphology, distribution and habitat of Sepsophis punctatus Beddome, 1870 (Squamata: Scincidae)

FIGURE 3. a: Dorsal view of CES09/985 in life; b: Close up photograph showing the vestigial forelimbs.

opennotspecifiedJun 2013View details →

FIGURE 2a & 2b in A long-lost relic from the Eastern Ghats: Morphology, distribution and habitat of Sepsophis punctatus Beddome, 1870 (Squamata: Scincidae)

FIGURE 2a & 2b. Photographs of the habitat close to the type locality where CES09/985 was found.

opennotspecifiedJun 2013View details →

FIGURE 1 in A long-lost relic from the Eastern Ghats: Morphology, distribution and habitat of Sepsophis punctatus Beddome, 1870 (Squamata: Scincidae)

FIGURE 1. Distribution of Sepsophis punctatus in the Eastern Ghats. The blue dot represents the type locality and the black dots represent the additional localities where S. punctatus was found.