Intercalibration of different light-traps and bulbs used in moth monitoring in northern Europe

Four different combinations of light-traps and bulbs were tested during the summer 1996 in Kainuu, northern Finland: a Jalas model with a 160-W (J/160W) blended light lamp or a 125-W (J/125W) mercury vapour lamp, a Ryrholm trap with a 125-W (R/125W) mercury vapour lamp and a Rothamsted trap with a 200-W tungsten lamp (G/200W). The traps were rotated between four sites every night, but were kept in the same position for the fifth night in order to prevent the possible influence of moonlight. The longest distance between the traps was 150m, and there was no direct visibility between any of them. Three orders were inspected, i.e. Lepidoptera, Coleoptera and Hemiptera, the total numbers of individuals and species being as follows: 20857/425, 862/101 and 1868/58. G/200W collected significantly fewer moths than the other traps. In some cases, J/125W collected significantly more moths and less species than the J/160W design. The R/125W design collected significantly more species than the J/160W design. Similar differences in the effectiveness of the lamps and traps were found in the case of Coleoptera and Hemiptera. Alpha diversities showed the same trend

A new efficient bait-trap model for Lepidoptera surveys – the “Oulu” model

To get reliable estimates of biodiversity or relative population sizes, it is important to develop and properly test new survey tools in comparison with previous methods. Here, we introduce a new, effective bait-trap model, viz. the “Oulu” model, for Lepidoptera surveys and monitoring schemes. An extensive field experiment showed that the new bait-trap model captures more individuals and more species than the widely-used “Jalas”model, while the species richness and species composition of the total catches did not differ between the trap models. The differences between the trap models were consistent over time and habitats. We suggest that the “Oulu” model yields high catches because few individuals can escape from the trap. It is thus an effective tool to be used in Lepidoptera surveys and studies

Morphometric sex determination of Great Grey Owls Strix nebulosa

Suggestions have been made for sexing Great Grey Owls Strix nebulosa using body measurements as criterion. Here we present measurement data from a long-term collection of 83 dead owls from western and northern Finland indicating that lengths of forearm, and claws 1, 2 and 4, are superior over traditional measurements of wing, tarsus, bill and body mass in determining sex of Great Grey Owls. Forearm of males ranged 123–148 mm, and was on average 138 mm (n = 31). In comparison, the forearm of females ranged 131–162 mm, with an average of 147 mm (n = 49). Based on a logistic regression analysis, the combination of forearm, second claw and wing length was the best predictor in correct sex determination of 95% of the Great Grey Owl specimens

Population dynamics of an expanding passerine at the distribution margin

This is the peer reviewed version of the following article: Karvonen, J.; Orell, M.; Rytkönen, S.; Broggi, J.; Belda Perez, EJ. (2012). Population dynamics of an expanding passerine at the distribution margin. Journal of Avian Biology. 43(2):102-108. doi:10.1111/j.1600-048X.2011.05376.x., which has been published in final form at http://dx.doi.org/10.1111/j.1600-048X.2011.05376.x. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving [http://olabout.wiley.com/WileyCDA/Section/id-817011.html ]Individuals may be maladapted to novel environments at the species' distribution margin. We investigated population dynamics in a marginal habitat where reproduction has been proven poor. Survival, population growth rate (¿) and its components, breeding and natal dispersal were studied in great tits Parus major breeding at the northern margin of its distribution in northern Finland. We used long term capture-mark-recapture data sets. Study area size and population density were used to explain adult survival rates. The average annual estimates of adult survival rose from 0.371 to 0.388 between the periods of 1971-1984 and 1999-2009. The estimates are slightly lower than estimates of small passerines in Europe. Low local survival rate of fledglings (0.050-0.055) probably reflects intensified emigration from this low quality area. Temporal variation in ¿ was large (0.498-1.856). Despite of low adult survival and recruitment rates, the mean estimates of ¿ (1.008 and 1.033) indicate an overall stability in the population size. Indeed, our results suggest that the immigration has an important role in the population dynamics of northern great tits. Thus the population is demographically and genetically dependent on core habitats which may cause adaptive problems due to intensive gene flow. Given those limitations, options for evolution of local adaptations in northern distribution margins are discussed.Satu Lampila, Mikko Ojanen, Suvi Ponnikas, Kari Koivula and numerous other field workers helped with data collection over the years. Veli-Matti Pakanen and Emma Vatka helped with the manuscript. Financial support for this study was provided by the Research Council for Biosciences and Environment of the Academy of Finland.Karvonen, J.; Orell, M.; Rytkönen, S.; Broggi, J.; Belda Pérez, EJ. (2012). Population dynamics of an expanding passerine at the distribution margin. Journal of Avian Biology. 43(2):102-108. https://doi.org/10.1111/j.1600-048X.2011.05376.xS102108432Bauchau, V., & Van Noordwijk, A. J. (1995). Comparison of survival estimates obtained from three different methods of recapture in the same population of the great tit. Journal of Applied Statistics, 22(5-6), 1031-1038. doi:10.1080/02664769524775Broggi, J., Hohtola, E., Orell, M., & Nilsson, J.-Å. (2005). LOCAL ADAPTATION TO WINTER CONDITIONS IN A PASSERINE SPREADING NORTH: A COMMON-GARDEN APPROACH. Evolution, 59(7), 1600-1603. doi:10.1111/j.0014-3820.2005.tb01810.xClobert, J., Perrins, C. M., McCleery, R. H., & Gosler, A. G. (1988). Survival Rate in the Great Tit Parus major in Relation to Sex, Age, and Immigration Status. The Journal of Animal Ecology, 57(1), 287. doi:10.2307/4779Dhondt, A. A., Adriaensen, F., Matthysen, E., & Kempenaers, B. (1990). Nonadaptive clutch sizes in tits. Nature, 348(6303), 723-725. doi:10.1038/348723a0Dingemanse, N. J., Both, C., van Noordwijk, A. J., Rutten, A. L., & Drent, P. J. (2003). Natal dispersal and personalities in great tits ( Parus major ). Proceedings of the Royal Society of London. Series B: Biological Sciences, 270(1516), 741-747. doi:10.1098/rspb.2002.2300Doncaster, C. P., Clobert, J., Doligez, B., Gustafsson, L., & Danchin, E. (1997). Balanced Dispersal Between Spatially Varying Local Populations: An Alternative To The Source‐Sink Model. The American Naturalist, 150(4), 425-445. doi:10.1086/286074Gould, W. R., & Nichols, J. D. (1998). ESTIMATION OF TEMPORAL VARIABILITY OF SURVIVAL IN ANIMAL POPULATIONS. Ecology, 79(7), 2531-2538. doi:10.1890/0012-9658(1998)079[2531:eotvos]2.0.co;2GREENWOOD, P. J., HARVEY, P. H., & PERRINS, C. M. (1978). Inbreeding and dispersal in the great tit. Nature, 271(5640), 52-54. doi:10.1038/271052a0Greño, J. L., Belda, E. J., & Barba, E. (2008). Influence of temperatures during the nestling period on post-fledging survival of great tit Parus major in a Mediterranean habitat. Journal of Avian Biology, 39(1), 41-49. doi:10.1111/j.0908-8857.2008.04120.xHORAK, P., & LEBRETON, J.-D. (2008). Survival of adult Great Tits Parus major in relation to sex and habitat; a comparison of urban and rural populations. Ibis, 140(2), 205-209. doi:10.1111/j.1474-919x.1998.tb04380.xKawecki, T. J. (2008). Adaptation to Marginal Habitats. Annual Review of Ecology, Evolution, and Systematics, 39(1), 321-342. doi:10.1146/annurev.ecolsys.38.091206.095622Kokko, H. (2006). From Individual Dispersal to Species Ranges: Perspectives for a Changing World. Science, 313(5788), 789-791. doi:10.1126/science.1128566KVIST, L., ARBABI, T., PÄCKERT, M., ORELL, M., & MARTENS, J. (2007). Population differentiation in the marginal populations of the great tit (Paridae: Parus major). Biological Journal of the Linnean Society, 90(2), 201-210. doi:10.1111/j.1095-8312.2007.00726.xLampila, S., Orell, M., Belda, E., & Koivula, K. (2006). Importance of adult survival, local recruitment and immigration in a declining boreal forest passerine, the willow tit Parus montanus. Oecologia, 148(3), 405-413. doi:10.1007/s00442-006-0386-3Lebreton, J.-D., Burnham, K. P., Clobert, J., & Anderson, D. R. (1992). Modeling Survival and Testing Biological Hypotheses Using Marked Animals: A Unified Approach with Case Studies. Ecological Monographs, 62(1), 67-118. doi:10.2307/2937171Lenormand, T. (2002). Gene flow and the limits to natural selection. Trends in Ecology & Evolution, 17(4), 183-189. doi:10.1016/s0169-5347(02)02497-7Matthysen, E., Adriaensen, F., & Dhondt, A. A. (2001). Local recruitment of great and blue tits (Parus major, P. caeruleus) in relation to study plot size and degree of isolation. Ecography, 24(1), 33-42. doi:10.1034/j.1600-0587.2001.240105.xORELL, M. (2008). Population fluctuations and survival of Great Tits Par us major dependent on food supplied by man in winter. Ibis, 131(1), 112-127. doi:10.1111/j.1474-919x.1989.tb02750.xORELL, M., LAHTI, K., & MATERO, J. (2008). High survival rate and site fidelity in the Siberian Tit Parus cinctus, a focal species of the taiga. Ibis, 141(3), 460-468. doi:10.1111/j.1474-919x.1999.tb04415.xPayevsky, V. A. (2006). Mortality rate and population density regulation in the great tit, Parus major L.: A review. Russian Journal of Ecology, 37(3), 180-187. doi:10.1134/s1067413606030064Postma, E., & van Noordwijk, A. J. (2005). Gene flow maintains a large genetic difference in clutch size at a small spatial scale. Nature, 433(7021), 65-68. doi:10.1038/nature03083Pradel, R. (1996). Utilization of Capture-Mark-Recapture for the Study of Recruitment and Population Growth Rate. Biometrics, 52(2), 703. doi:10.2307/2532908Pulliam, H. R. (1988). Sources, Sinks, and Population Regulation. The American Naturalist, 132(5), 652-661. doi:10.1086/284880Rytkonen, S., & Orell, M. (2001). Great tits, Parus major, lay too many eggs: experimental evidence in mid-boreal habitats. Oikos, 93(3), 439-450. doi:10.1034/j.1600-0706.2001.930309.xRytkonen, S., & Krams, I. (2003). Does foraging behaviour explain the poor breeding success of great tits Parus major in northern Europe? Journal of Avian Biology, 34(3), 288-297. doi:10.1034/j.1600-048x.2003.03041.xSasvari, L., & Orell, M. (1992). Breeding Success in a North and a Central European Population of the Great Tit Parus major. Ornis Scandinavica, 23(1), 96. doi:10.2307/3676432Tinbergen, J. M. (2004). Strong evidence for selection for larger brood size in a great tit population. Behavioral Ecology, 15(4), 525-533. doi:10.1093/beheco/arh045Väisänen R. A. Lammi E. Koskimies P 1998 Muuttuva pesimälinnusto Otava, KeuruuVerhulst, S., Perrins, C. M., & Riddington, R. (1997). NATAL DISPERSAL OF GREAT TITS IN A PATCHY ENVIRONMENT. Ecology, 78(3), 864-872. doi:10.1890/0012-9658(1997)078[0864:ndogti]2.0.co;2Visser, M. E., & Verboven, N. (1999). Long-Term Fitness Effects of Fledging Date in Great Tits. Oikos, 85(3), 445. doi:10.2307/3546694White, G. C., & Burnham, K. P. (1999). Program MARK: survival estimation from populations of marked animals. Bird Study, 46(sup1), S120-S139. doi:10.1080/0006365990947723

From feces to data : A metabarcoding method for analyzing consumed and available prey in a bird-insect food web

Diets play a key role in understanding trophic interactions. Knowing the actual structure of food webs contributes greatly to our understanding of biodiversity and ecosystem functioning. The research of prey preferences of different predators requires knowledge not only of the prey consumed, but also of what is available. In this study, we applied DNA metabarcoding to analyze the diet of 4 bird species (willow tits Poecile montanus, Siberian tits Poecile cinctus, great tits Parus major and blue tits Cyanistes caeruleus) by using the feces of nestlings. The availability of their assumed prey (Lepidoptera) was determined from feces of larvae (frass) collected from the main foraging habitat, birch (Betula spp.) canopy. We identified 53 prey species from the nestling feces, of which 11 (21%) were also detected from the frass samples (eight lepidopterans). Approximately 80% of identified prey species in the nestling feces represented lepidopterans, which is in line with the earlier studies on the parids' diet. A subsequent laboratory experiment showed a threshold for fecal sample size and the barcoding success, suggesting that the smallest frass samples do not contain enough larval DNA to be detected by high-throughput sequencing. To summarize, we apply metabarcoding for the first time in a combined approach to identify available prey (through frass) and consumed prey (via nestling feces), expanding the scope and precision for future dietary studies on insectivorous birds.Peer reviewe

Temperature synchronizes temporal variation in laying dates across European hole-nesting passerines

Publisher Copyright: © 2022 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.Identifying the environmental drivers of variation in fitness-related traits is a central objective in ecology and evolutionary biology. Temporal fluctuations of these environmental drivers are often synchronized at large spatial scales. Yet, whether synchronous environmental conditions can generate spatial synchrony in fitness-related trait values (i.e., correlated temporal trait fluctuations across populations) is poorly understood. Using data from long-term monitored populations of blue tits (Cyanistes caeruleus, n = 31), great tits (Parus major, n = 35), and pied flycatchers (Ficedula hypoleuca, n = 20) across Europe, we assessed the influence of two local climatic variables (mean temperature and mean precipitation in February–May) on spatial synchrony in three fitness-related traits: laying date, clutch size, and fledgling number. We found a high degree of spatial synchrony in laying date but a lower degree in clutch size and fledgling number for each species. Temperature strongly influenced spatial synchrony in laying date for resident blue tits and great tits but not for migratory pied flycatchers. This is a relevant finding in the context of environmental impacts on populations because spatial synchrony in fitness-related trait values among populations may influence fluctuations in vital rates or population abundances. If environmentally induced spatial synchrony in fitness-related traits increases the spatial synchrony in vital rates or population abundances, this will ultimately increase the risk of extinction for populations and species. Assessing how environmental conditions influence spatiotemporal variation in trait values improves our mechanistic understanding of environmental impacts on populations.Peer reviewe

The EU Horizon 2020 project GRACE : integrated oil spill response actions and environmental effects

This article introduces the EU Horizon 2020 research project GRACE (Integrated oil spill response actions and environmental effects), which focuses on a holistic approach towards investigating and understanding the hazardous impact of oil spills and the environmental impacts and benefits of a suite of marine oil spill response technologies in the cold climate and ice-infested areas of the North Atlantic and the Baltic Sea. The response methods considered include mechanical collection in water and below ice, in situ burning, use of chemical dispersants, natural biodegradation, and combinations of these. The impacts of naturally and chemically dispersed oil, residues resulting from in situ burning, and non-collected oil on fish, invertebrates (e.g. mussels, crustaceans) and macro-algae are assessed by using highly sensitive biomarker methods, and specific methods for the rapid detection of the effects of oil pollution on biota are developed. By observing, monitoring and predicting oil movements in the sea through the use of novel online sensors on vessels, fixed platforms including gliders and the so-called SmartBuoys together with real-time data transfer into operational systems that help to improve the information on the location of the oil spill, situational awareness of oil spill response can be improved. Methods and findings of the project are integrated into a strategic net environmental benefit analysis tool (environment and oil spill response, EOS) for oil spill response strategy decision making in cold climates and ice-infested areas

Variation in clutch size in relation to nest size in birds

Peer reviewe