Linköping University | Department of Physics, Chemistry and Biology Bachelor thesis, 16 hp | Educational programme: Physics, Chemistry and Biology Spring term 2019 | LITH-IFM-G-EX--19/3704--SE
The effect of temperature on productivity
of birds in Sweden and Finland
Johanna Orsholm
Examinator, Jenny Hagenblad, IFM Biologi, Linköpings universitet Tutor, Karl-Olof Bergman, IFM Biologi, Linköpings universitet
2 Datum Date 2019-06-07 Avdelning, institution Division, Department
Department of Physics, Chemistry and Biology Linköping University
URL för elektronisk version
ISBN
ISRN: LITH-IFM-G-EX--19/3704--SE
_________________________________________________________________
Serietitel och serienummer ISSN
Title of series, numbering ______________________________
Språk Language Svenska/Swedish Engelska/English ________________ Rapporttyp1 Report category Licentiatavhandling Examensarbete C-uppsats D-uppsats Övrig rapport _____________ Titel/Title:
The effect of temperature on productivity of birds in Sweden and Finland
Författare/Author:
Johanna Orsholm
Nyckelord
Keyword
Birth rate, Global warming, Reproductive success, Species traits, Climatic niche, Multiple breeding, Breeding success
Sammanfattning
Abstract
Anthropogenic climate change is one of the most important factors influencing population growth and survival. Therefore, to be able to predict the effect of climate change on ecosystem composition and function, it is important to understand its effect on demographic variables, such as productivity. As a measure of productivity, I related the proportion of yearling birds captured during bird ringing in southern Sweden with mean temperature during the breeding season. I then compared the relationship between temperature and productivity for species with different traits regarding number of broods produced per season, thermal niches and migration behaviours. For most species (72%), productivity positively related to temperature during the breeding season. The relationship was strongest for species with the ability to vary the number of broods per year and species with a warmer thermal niche, whereas there was no difference between long-distance migratory and short-distance migratory species. The results suggest that, for some bird species in the study area, climate warming can increase population sizes. However, long-term effects of climate change may be different than the interannual fluctuations of temperature considered in this study, especially when interacting effects of habitat losses are taken into account.
3 Contents
1 Abstract ... 4
2 Introduction ... 4
3 Materials and methods ... 6
3.1 Bird ringing data from Ottenby Bird Observatory ... 6
3.2 Bird species ... 7
3.2.1 Breeding season ... 7
3.2.2 Number of broods per season ... 8
3.2.3 Migration behaviour ... 9 3.2.4 Thermal niche ... 9 3.3 Weather data ... 9 3.4 Data processing ... 10 3.5 Statistical analysis ... 10 4 Results ... 11
4.1 The effect of temperature on productivity ... 11
4.2 Differences in the response to temperature due to species-specific traits ... 11
5 Discussion ... 13
5.1 Relationship between productivity and temperature of the breeding season ... 13
5.2 Conclusion ... 16
5.3 Societal & ethical considerations ... 16
6 Acknowledgements ... 17
4
1 Abstract
Anthropogenic climate change is one of the most important factors influencing population growth and survival. Therefore, to be able to predict the effect of climate change on ecosystem composition and function, it is important to understand its effect on demographic variables, such as productivity. As a measure of productivity, I related the proportion of yearling birds captured during bird ringing in southern Sweden with mean temperature during the breeding season. I then compared the relationship between temperature and productivity for species with different traits regarding number of broods produced per season, thermal niches and migration behaviours. For most species (72%), productivity positively related to temperature during the breeding season. The relationship was strongest for species with the ability to vary the number of broods per year and species with a warmer thermal niche, whereas there was no difference between long-distance migratory and short-distance migratory species. The results suggest that, for some bird species in the study area, climate warming can increase population sizes. However, long-term effects of climate change may be different than the interannual fluctuations of temperature considered in this study, especially when interacting effects of habitat losses are taken into account.
2 Introduction
Anthropogenic climate change is causing increasing temperatures, changes in precipitation patterns and a higher frequency of extreme weather events (Wuebbles et al. 2017). Together with habitat loss it is one of the most important factors influencing population growth and survival (Travis 2003; Thomas et al. 2004; Mantyka-Pringle et al. 2012; Urban 2015). Species’ traits largely determine their susceptibility to climate change, where species with narrow requirements and low adaptability are generally the most vulnerable (Foden et al. 2008). Adaptions, as expected by climate change predictions, can already be seen in phenology and distribution of species (Parmesan & Yohe 2003), and can be caused by genetic change or a phenotypic response. Phenotypic plasticity, the ability of a single genotype to express multiple phenotypes (Houston & McNamara 1992), may enable a fast adaption and thus contribute to a species’ ability to tolerate climate change (Dunn & Winkler 2010).
Phenotypic plasticity may allow species to adjust the number of breeding attempts per year in response to conditions during the breeding season (Møller et al. 2010). The ability to vary the number of breeding attempts have been shown in butterflies and moths, which increase the frequency of second generations, and sometimes the number of generations, with increasing
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temperature (Altermatt 2010). Increased number of breeding attempts may promote population growth and, if so, facilitate adaption due to the increased reproduction rate (Altermatt 2010). Bird species vary in the number of broods produced per year, where some species generally produce a fixed number of broods, while other are more flexible (i.e. facultative multi-brooded) (Cramp 1977-1994). Several factors influence the proportion of multi-brooding in birds, such as food availability (Nagy & Holmes 2005; Jiguet et al. 2007), latitude (Böhning-Gaese et al. 2000), and duration of the breeding season (Møller et al. 2010). Warming temperatures during the last couple of decades have advanced the appearance of many insects (Roy & Sparks 2000; Stefanescu et al. 2003; Gordo & Sanz 2005) and, likely to reduce a possible mismatch between food availability and breeding timing, some birds have advanced their breeding season accordingly (Crick & Sparks 1999; Visser et al. 2011; Dunn & Møller 2014). Advancement of the breeding season is most prominent in multi-brooding species, and the extended breeding season may allow more broods or a better temporal spacing between broods, thus increasing reproductive success (Møller et al. 2010).
Advancement of the laying date to match the altered phenology of spring may be possible due to phenotypic plasticity. However, ability to advance the breeding season may be limited by, for example, hormonal or genetic constraints (Dunn & Winkler 2010). Adaption to climate change in long-distance migratory (LDM) bird species are likely constrained by the timing of their migration (Both & Visser 2001). Rather than environmental cues at the breeding ground initiating migration, as is common for short-distance migrants (SDM), the timing of their migration is based on circannual rhythms not affected by climate change (Gwinner 1996). Therefore, LDMs may be unable to adjust their breeding season to match advanced spring conditions and thus can be more vulnerable to an ecological mismatch (Saino et al. 2011).
Further, susceptibility to climate change may vary with a species’ temperature niche (Stillman 2003; Thuiller et al. 2005; Wilson et al. 2005). Northward shifts of species’ ranges when temperatures increase have been observed in invertebrates (Sagarin et al. 1999), butterflies (Parmesan et al. 1999), and birds (Thomas & Lennon 1999; Hitch & Leberg 2007; Devictor et al. 2008). Species with a northern distribution may be driven further north, possibly by an increased interspecific competition of southern species shifting their range (Hersteinsson & MacDonald 1992; Beaugrand et al. 2002). For birds, species with a low thermal maximum have been observed to decline more during recent years than species with a high thermal
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maximum (Jiguet et al. 2010). That is, the response to climate warming may vary depending on a species’ distribution and temperature niche.
To be able to predict the effects of climate warming on species and populations, and also on ecosystems, it is important to understand how temperature affects demographic variables, such as productivity (annual number of offspring per year; Meller et al. 2018). Productivity may be positively or negatively affected by increasing temperatures (Eeva et al. 2002; Klady et al. 2011; Eglington et al. 2015). Further, avian abundance is partly determined by productivity (Sæther & Bakke 2000), which has been linked with population growth rates (Meller et al. 2018). Hence, understanding how productivity is affected by climate warming is crucial to be able to predict the effect of climate change on bird populations. In this study, I aimed examine if there is a correlation between temperature during the breeding season and productivity of birds and if productivity is affected by the ability to vary the number of broods per season, the migratory behaviour or the thermal niche of a species.
3 Materials and methods
3.1 Bird ringing data from Ottenby Bird Observatory
Ottenby Bird Observatory, hereafter called Ottenby, is located at the southern cape of Öland, Sweden (Figure 1). Since 1972, standardised bird ringing has been conducted at the observatory every autumn, from July 25th to November 15th. During this period, 13 mist-nets and two Heligoland traps are used, being opened 30 minutes before sunrise and closed at 11 am. If, at 11 am, there are still a great number of birds being captured, the nets are kept open until the numbers decline. The nets are emptied every 30 minutes and the birds are transported in special bags to the ringing laboratory where several parameters, including species and age, are recorded (Lindström et al. 2003).
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Figure 1. Ottenby Bird Observatory, located at the southern cape of Öland, Sweden (Google maps, 2019)
Birds captured at Ottenby are mainly recruited from Sweden and Finland, hereafter called the recruitment area. Some birds originate from western Russia, but since this proportion is very small (M. Hellström, personal communication) it was not taken into account in this study. From Ottenby, I received data of 51 bird species ringed during autumn catches. The data spanned over 47 years, from 1972 to 2018, hereafter called the study period. Data included the number of captured birds divided into different age classes, indicating whether they were bornthe current season or earlier.
3.2 Bird species
Bird species that are regularly captured during autumn catches were chosen from the annual report of 2017 from Ottenby (Hellström et al. 2018). All waders were excluded due to large variations in number of catches between years. Of the remaining species, the ortolan bunting (Emberiza hortulana) were excluded, since less than 100 catches were registered during the study period. Thereafter 50 species remained (Appendix 1).
3.2.1 Breeding season
Volume 1-9 of the book collection Handbook of the Birds of Europe, the Middle East and North Africa: Birds of the Western Palearctic (Cramp 1977-1994) were used to determine the breeding season for each species (Appendix 1). The breeding season was defined as the first month when eggs were laid until the last month when chicks were still in the nest. The blue tit (Cyanistes caeruleus), the thrush nightingale (Luscinia luscinia) and the bluethroat (Luscinia svecica) did not have the end of the breeding season specified by the book collection. For C. caeruleus, the breeding season of the great tit (Parus major) was used, and for L. luscinia, the
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breeding season of the whinchat (Saxicola rubetra) was used (Åke Lindström, personal communication). For L.svecica, the breeding season was determined as June-August (Arheimer 1982). Since cues affecting the breeding of birds may occur earlier than the first month of laying, mean temperature of the breeding season was calculated by including one month before laying of the first brood. For example, if the breeding season was May to July, mean temperature was calculated for April to July. For brevity, the prolonged season will hereafter be referred to as the breeding season.
The breeding seasons of birds vary across their range and data may therefore vary depending on where it was collected. Additionally, the phenology of breeding has been affected by climate change, which may cause older data to be invalid. For a majority (84%) of the study species, data of the breeding season was collected from studies conducted in Scandinavia. For the rest, data was collected from studies conducted in Western or Central Europe. No adjustment of the breeding seasons was made to correct for changes caused by climate change, but since one month previous to egg-laying was included in all analyses, the temperature experienced by the birds during the breeding season was most likely included.
3.2.2 Number of broods per season
The book collection (Cramp 1977-1994) was used to assign all species one of two traits regarding the number of broods produced per season:
- A variable number of broods produced per season (Var) - A fixed number of broods produced per season (Fix)
When the book collection stated a range of number of broods produced, for example “1-2 broods”, it was interpreted as a variable number of broods per season, while if it stated a fixed number, for exampe “1 brood”, it was interpreted as a fixed number of broods per season. Since variations in breeding strategies are common throughout a species’ range, and since the book collection did not specifically describe populations of northern Europe, the allocation of traits was adjusted for eleven species (Møller et al. 2008; Å. Lindström, personal communication; S. Bensch, personal communication). In total, 30 species were classified as having a variable number of broods per season and 20 species were classified as having a fixed number of broods per season (Appendix 1).
9 3.2.3 Migration behaviour
The book collection (Cramp 1977-1994) was used to assign all species one of two traits regarding migration behaviour:
- Long-distance migrant (LDM) - Short-distance migrant (SDM)
Long-distance migrant was defined as a species with its wintering grounds south of Sahara, while short-distance migrant was defined as a species with its wintering grounds north of Sahara. The red-breasted flycatcher (Ficedula parva) and the scarlet rosefinch (Carpodacus erythrinus) were exceptions, since they migrate to Southern Asia. They were both classified as long-distance migrants. In total, 23 species were classified as LDMs and 27 species were classified as SDMs (Appendix 1).
3.2.4 Thermal niche
As a measure of thermal niche, a species temperature index (STI) was obtained for each species (Lindström et al. 2013). STI is estimated as mean temperature of the species’ distribution and may vary depending on what part of the distribution is used. However, if the same boundaries are used when calculating STI for all species, the values are comparable. The species were divided into two groups: the 25 species with the highest STI (“warmer thermal niche”) and the 25 species with the lowest STI (“colder thermal niche”).
3.3 Weather data
To measure mean temperature of the entire recruitment area, cities evenly distributed across the area, with weather stations operating from 1972 to 2018, were chosen. Monthly mean temperatures were obtained for eight cities in Sweden and six cities in Finland (Figure 2), from the Swedish Meteorological and Hydrological Institute (SMHI) and the Finnish Meteorological Institute (FMI) respectively. In some cases, multiple weather stations were used to complete the data sets (Appendix 2).
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Figure 2. The cities for which mean temperatures were used during the study.
3.4 Data processing
As a measure of productivity, the proportion of yearlings of all birds (yearlings + adults) was calculated for each species. Mean temperature of the recruitment area, estimated as mean temperature of the fourteen cities for which temperature data was obtained, was calculated for each species’ breeding season.
3.5 Statistical analysis
To test for a correlation between productivity and temperature, a multiple regression analysis was performed for each species using the proportion of yearlings as the dependent variable. Mean temperature of the breeding season and year (continuous, to account for any temporal trend in productivity over the study period) was included as factors in the analysis.
Productivity may be density-dependent and generally decrease with increasing population size (Arcese et al. 1992; Dhondt 2010). However, population size was not expected to be correlated with temperature such as that it would affect the result of the regression analysis and, therefore, population size was not included as a factor in the regression analysis. Further, productivity may be autocorrelated (i.e. related to the productivity of the previous year), which could shroud a potential correlation between temperature and productivity. However, it
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was not expected to affect the correlations and was therefore not adjusted for in the regression analysis.
To test for differences in temperature’s effect on productivity between species with different traits, mean regression coefficients were compared using t-tests.
4 Results
4.1 The effect of temperature on productivity
A majority of species in the study (36 species; 72%) showed a positive relationship between mean temperature of the breeding season and productivity. Of these, the correlation was significant for seven species (P < 0.05; Figure 3). One species showed no correlation between temperature and productivity, while 13 species (26%) showed a negative relationship between mean temperature of the breeding season and productivity. Of these, the correlation was significant for one species (P < 0.05; Figure 3).
4.2 Differences in the response to temperature due to species-specific traits
Species with a varied number of broods per season showed a tendency to increase productivity more with increasing temperature than species with a fixed number of broods per season (t(48) = -1.943, P = 0.058; Figure 4). There was no difference between long-distance
migratory species and short-distance migratory species regarding the effect of temperature on productivity (t(48) = 0.222; P = 0.826). Lastly, species with a warmer thermal niche showed a
tendency to increase productivity more with increasing temperature than species with a colder thermal niche (t(48) = 1.904, P = 0.063; Figure 5).
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Figure 3. Regression coefficients and 95% confidence intervals of regressions of mean temperature during the breeding season and productivity for 50 bird species. *Regression significant for significance level P < 0.05. 1Regression significant for significance level P < 0.1
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Figure 4. Mean regression coefficient for 50 species of a regression of productivity and mean temperature of the breeding season. The species were divided into two groups: species with a varied number of broods per season and species with a fixed number of broods per season. N = 50, B ± SE
Figure 5. Mean regression coefficient for 50 species of a regression of productivity and mean temperature of the breeding season. The species were divided into two groups: species with a warmer thermal niche and species with a colder thermal niche. N = 50, B ± SE
5 Discussion
5.1 Relationship between productivity and temperature of the breeding season
This study indicated that, for a majority of species in the study area, there was a positive relationship between temperature of the breeding season and productivity of birds. Productivity has been shown to positively correlate with population growth rate for several
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species (Meller et al. 2018). The positive relationship between temperature of the breeding season and productivity in this study may thus suggest that climate warming can increase bird population sizes, at least in northern populations. However, long-term effects of increasing temperatures may be different than the effects of interannual fluctuations of temperature considered in this study.
The larger productivity during warm years could be explained by an increased food availability (Eeva 2000 in Meller et al. 2018), reduced thermoregulatory demands (Tinbergen & Dietz 1994), or the opportunity to breed earlier. Early breeders generally lay larger clutches, which could be an effect of quality (e.g. if individuals with a high phenotypic quality breeds earlier) or of breeding date per se (e.g. if there is a trade-off between reproductive investment and initiation of moult) (Verhulst & Nilsson 2008).
The results of this study indicated that ability to vary the number of breeding attempts per year and temperature niche, but not migration behaviour, affected the relationship between productivity and temperature during the breeding season. Species with a varied number of broods showed a tendency to increase productivity more with increasing temperatures than species with a fixed number of broods. This is in line with an earlier study, where the number of broods per year positively related to recent population trends, suggesting that single-brooded species are more vulnerable to climate change (Jiguet et al. 2007). Multi-single-brooded species have been shown to advance the breeding season more than single-brooded species, thus prolonging the breeding season and possibly allowing more broods or a better temporal distribution of broods (Møller et al. 2010). Additionally, increased food availability due to warmer springs may facilitate multi-brooding (Nagy & Holmes 2005; Jiguet et al. 2007) and thus further benefit multi-brooded species in particular. Therefore, by enabling an increased proportion of multi-brooding, or by allowing better temporal spacing between broods and thus an increased parental investment in both first and subsequent broods, climate warming may increase productivity of multi-brooded bird species.
Surprisingly, in this study, there was no difference between long-distance migratory (LDM) and short-distance migratory (SDM) species regarding the response of productivity to increasing temperatures. Migration timing likely prevents LDMs from fully adapting to an advanced spring phenology, and LDMs have been observed to arrive later in relation to spring conditions than SDMs (Saino et al. 2011). Further, population declines have been observed in
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migratory bird species that have not advanced their spring migration (Møller et al. 2008), and the inability to adapt to spring conditions may thus make LDMs more vulnerable to an ecological mismatch, caused by climate change, than SDMs. The possibly detrimental effect of climate change is supported by population declines of LDM species observed in north-eastern Europe (Laaksonen & Lehikoinen 2013). In contrast with the observed population declines, the results of this study did not indicate a negative effect of temperature on productivity of LDM species. The results are consistent with observations in Finland, where spring temperature had a positive effect on productivity of both SDM and LDM species (Meller et al. 2018). The observed population declines of LDM species can however be explained by several other mechanisms, such as impaired conditions along the migration route or at the wintering ground, possibly causing an increased adult mortality (reviewed by Faaborg et al. 2010).
This study indicated that species with warmer thermal niches increased productivity more with increasing temperature than species with colder thermal niches, suggesting that southern species benefit more from climate warming than northern species. A similar pattern has been shown in France, The Netherlands, and Sweden, where populations breeding close to the species thermal minimum (i.e. northern end of distribution) had higher population growth rates than populations breeding close to the species thermal maximum (i.e. southern end of distribution) (Jiguet et al. 2010). Further, low thermal maximums correlate with observed population declines, suggesting that northern populations decline more than southern populations (Jiguet et al. 2007). Differences in productivity and population growth rates between populations in the northern and the southern end of a species’ range may be one of the factors causing a northward shift of species distributions (Thomas & Lennon 1999).
Shifts of distributions and changes of relative abundance of species may affect ecosystem compositions. Changes in ecosystems can be illustrated using a community temperature index (CTI), a measure of relative abundances of species with warm (high STI) versus cold (low STI) temperature niches in a species assemblage. In Sweden, CTI of bird communities have been shown to change in accordance with temperature, mainly due to changes in relative abundances of species (Lindström et al. 2013). Differences in productivity between species with warm and cold thermal niches when temperatures increase may affect population growth rates and abundance of species, and can thus be a contributing factor to the observed changes of CTI.
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The results from this study indicated that productivity of species with colder thermal niches were positively related to temperature, though this relation was stronger for species with warmer thermal niches. However, several other mechanisms not investigated in this study (e.g. adult survival) may be making northern species vulnerable to climate change. Changes in ecosystem composition due to altered relative abundances of species may, by altering interspecific competition, negatively affect northern species (Hersteinsson & MacDonald 1992; Beaugrand et al. 2002). Further, habitat loss is a major factor affecting survival and population growth (e.g. Fahrig 1997; Brooks et al. 2002), and alpine habitats have been recognised as one of the most vulnerable to climate change (Gonzalez et al. 2010). Increased interspecific competition and habitat loss may, at least partially, explain the population declines of alpine and arctic species observed in Fennoscandia (Lehikoinen et al. 2014).
5.2 Conclusion
The positive relationship between temperature and productivity in this study suggests that climate warming can increase population sizes. Additionally, species-specific traits seemed to determine how strong the relationship between productivity and temperature is, suggesting that multi-brooded species and southern species may benefit the most from climate warming. However, climate change has other effects than increasing temperatures, and its long-term effects may be different than the interannual fluctuations of temperature considered in this study. Climate change and habitat loss are recognised as among the largest threats to biodiversity (Mantyka-Pringle et al. 2012), and habitat loss may add to the effect of climate warming. Therefore, accurate predictions of the effects of climate change on bird populations and communities must also consider the effects of habitat loss and degradation.
5.3 Societal & ethical considerations
Climate change is one of our time’s greatest threats, and it is important to understand the mechanisms by which it affects populations and ecosystems. With increasing habitat loss and degradation, species extinction and reduction of population sizes become urgent issues. If there is a difference in survival between species depending on their traits it may affect ecosystem composition and function, and therefore knowledge about such a mechanism is relevant for conservation issues.
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The project largely depends on data from bird ringing at Ottenby Bird Observatory. Bird ringing does not require an ethical permit, but Ottenby have a ringing permit from the Bird Ringing Centre at Naturhistoriska riksmuseet.
6 Acknowledgements
I am grateful to Magnus Hellström, manager at Ottenby Bird Observatory, who provided the bird ringing data as well as guidance before and during the study. Additionally, I thank my supervisor, Karl-Olof Bergman, for guidance and support, and Lars Westerberg, who helped with the statistical analyses. Finally, I am grateful to Åke Lindström, Professor at the Department of Biology at Lund University, for providing data of STI for all species and plenty of advice during the study, and Staffan Bensch, Professor at the Department of Biology at Lund University, for advice regarding breeding strategies.
7 References
Altermatt F (2010) Climatic warming increases voltinism in european butterflies and moths. Proc. R. Soc. B 277, 1281–1287.
Arcese P, Smith J N M, Hochachka W M, Rogers C M, Ludwig D (1992) Stability, regulation, and the determination of abundance in an insular song sparrow population. Ecology 73, 805–822.
Arheimer O (1982) Blåhakens Luscinia svecica häckningsbiologi i fjällbjörkskog vid Ammarnäs. Vår Fågelvärd 41, 249–260.
Beaugrand G, Reid P C, Ibanez F, Lindley J A, Edwards M (2002) Reorganization of North Atlantic marine copepod biodiversity and climate. Science 296, 1692–1694.
Böhning-Gaese K, Halbe B, Lemoine N, Oberrath R (2000) Factors influencing the clutch size, number of broods and annual fecundity of North American and European land birds. Evolutionary Ecology Research 2, 823–839.
Both C, Visser M E (2001) Adjustment to climate change is constrained by arrival date in a long-distance migrant bird. Nature 411, 296–298.
Brooks T M, Mittermeier R A, Mittermeier C G, Da Fonseca G A B, Rylands A B, Konstant W R, … Hilton-Taylor C (2002) Habitat loss and extinction in the hotspots of
biodiversity. Conservation Biology 16, 909–923.
18
Africa: the birds of the western Palearctic, Vol 1-9. Oxford: Oxford University Press. Crick H Q P, Sparks T H (1999) Climate change related to egg-laying trends. Nature 399, 423.
Devictor V, Julliard R, Couvet D, Jiguet F (2008) Birds are tracking climate warming, but not fast enough. Proc. R. Soc. B 275, 2743–2748.
Dhondt A A (2010) Effects of competition on great and blue tit reproduction: Intensity and importance in relation to habitat quality. Journal of Animal Ecology 79, 257–265.
Dunn P O, Møller A P (2014) Changes in breeding phenology and population size of birds. Journal of Animal Ecology 83, 729–739.
Dunn P O, Winkler D W (2010) Effects of climate change on timing of breeding and reproductive success in birds. In A P Møller, F Wolfgang, P Berthold (Eds.), Effects of Climate Change on Birds (pp. 113–128). Oxford: Oxford University Press.
Eeva T, Lehikoinen E, Rönkä M, Lummaa V, Currie D (2002) Different responses to cold weather in two pied flycatcher populations. Ecography 25, 705–713.
Eglington S M, Julliard R, Gargallo G, van der Jeugd H P, Pearce-Higgins J W, Baillie S R, Robinson R A (2015) Latitudinal gradients in the productivity of European migrant warblers have not shifted northwards during a period of climate change. Global Ecology and Biogeography 24, 427–436.
Faaborg J, Holmes R T, Anders A D, Bildstein K L, Dugger K M, Gauthreaux S A, … Warnock N (2010) Recent advances in understanding migration systems of New World land birds. Ecological Monographs 80, 3–48.
Fahrig L (1997) Relative effects of habitat loss and fragmentation on population extinction. The Journal of Wildlife Management 61, 603–610.
Foden W, Mace G, Vié J-C, Angulo A, Butchart S, DeVantier L, … Turak E (2008) Species susceptibility to climate change imapcts. In J-C Vié, C Hilton-Taylor, S N Stuart (Eds.), The 2008 Review of The IUCN Red List of Threatened Species. IUCN Gland,
Switzerland.
Gonzalez P, Neilson R P, Lenihan J M, Drapek R J (2010) Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change. Global Ecology and
19
Google maps (2019) Google maps.
https://www.google.se/maps/place/Ottenby+f%C3%A5gelstation/@56.3065677,14.1244 768,7z/data=!4m5!3m4!1s0x46f89f515e451a89:0x1d75ff160dde06d!8m2!3d56.1975749 !4d16.3993958 (Accessed 6 May 2019)
Gordo O, Sanz J J (2005) Phenology and climate change: a long-term study in a Mediterranean locality. Oecologia 146, 484–495.
Gwinner E (1996) Circannual clocks in avian reproduction and migration. Ibis 138, 47–63.
Hellström M, Andersson A, Lilja Nordin T, Waldenström J, Lindström Å (2018) Fågelräkning och ringmärkning vid Ottenby fågelstation 2017. Rapport, Ottenby fågelstation. 48 pp.
Hersteinsson P, MacDonald D W (1992) Interspecific competition and the geographical
distribution of red and arctic foxes vulpes vulpes and alopex lagopus. Oikos 64, 505–515.
Hitch A T, Leberg P L (2007) Breeding distributions of North American bird species moving north as a result of climate change. Conservation Biology 21, 534–539.
Houston A I, McNamara J M (1992) Phenotypic plasticity as a state-dependent life-history decision. Evolutionary Ecology 6, 243–253.
Jiguet F, Devictor V, Ottvall R, Van Turnhout C, van der Jeugd H, Lindström Å (2010) Bird population trends are linearly affected by climate change along species thermal ranges. Proc. R. Soc. B 277, 3601–3608.
Jiguet F, Gadot A S, Julliard R, Newson S E, Couvet D (2007) Climate envelope, life history traits and the resilience of birds facing global change. Global Change Biology 13, 1672– 1684.
Klady R A, Henry G H R, Lemay V (2011) Changes in high arctic tundra plant reproduction in response to long-term experimental warming. Global Change Biology 17, 1611–1624.
Laaksonen T, Lehikoinen A (2013) Population trends in boreal birds: continuing declines in agricultural, northern, and long-distance migrant species. Biological Conservation 168, 99–107.
Lehikoinen A, Green M, Husby M, Kålås J A, Lindström Å (2014) Common montane birds are declining in northern Europe. Journal of Avian Biology 45, 3–14.
20
Lindström Å, Green M, Paulson G, Smith H G, Devictor V (2013) Rapid changes in bird community composition at multiple temporal and spatial scales in response to recent climate change. Ecography 36, 313–322.
Lindström Å, Hedenström A, Hjort C (2003) Rutiner för fångst och ringmärkning vid Ottenby fågelstation.
Mantyka-Pringle C S, Martin T G, Rhodes J R (2012) Interactions between climate and habitat loss effects on biodiversity: a systematic review and meta-analysis. Global Change Biology 18, 1239–1252.
Meller K, Piha M, Vähätalo A V, Lehikoinen A (2018) A positive relationship between spring temperature and productivity in 20 songbird species in the boreal zone. Oecologia 186, 883–893.
Møller A P, Flensted-Jensen E, Klarborg K, Mardal W, Nielsen J T (2010) Climate change affects the duration of the reproductive season in birds. Journal of Animal Ecology 79, 777–784.
Møller A P, Rubolini D, Lehikoinen E (2008) Populations of migratory bird species that did not show a phenological response to climate change are declining. Proceedings of the National Academy of Sciences 105, 16195–16200.
Nagy L R, Holmes R T (2005) Food limits annual fecundity of a migratory songbird: an experimental study. Ecology 86, 675–681.
Parmesan C, Ryrholm N, Stefanescu C, Hill J K, Thomas C D, Descimon H, … Warren M (1999) Poleward shifts in geographical ranges of butterfly species associated with regional warming. Nature 399, 579–583.
Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42.
Roy D B, Sparks T H (2000) Phenology of British butterflies and climate change. Global Change Biology 6, 407–416.
Sæther B-E, Bakke O (2000) Avian life history variation and contribution of demographic traits to the population growth rate. Ecology 81, 642–653.
21
intertidal community over short and long time scales. Ecological Monographs 69, 465– 490.
Saino N, Ambrosini R, Rubolini D, von Hardenberg J, Provenzale A, Hüppop K, … Sokolov L (2011) Climate warming, ecological mismatch at arrival and population decline in migratory birds. Proc. R. Soc. B 278, 835–842.
Stefanescu C, Peñuelas J, Filella I (2003) Effects of climatic change on the phenology of butterflies in the northwest Mediterranean Basin. Global Change Biology 9, 1494–1506.
Stillman J H (2003) Acclimation capacity underlies susceptibility to climate change. Science 301, 65.
Thomas C D, Cameron A, Green R E, Bakkenes M, Beaumont L J, Collingham Y C, … Williams S E (2004) Extinction risk from climate change. Nature 427, 145–148.
Thomas C D, Lennon J J (1999) Birds extend their ranges northwards. Nature 399, 213–213.
Thuiller W, Lavorel S, Araújo M B (2005) Niche properties and geographical extent as
predictors of species sensitivity to climate change. Global Ecology and Biogeography 14, 347–357.
Tinbergen J M, Dietz M W (1994) Parental energy expenditure during brood rearing in the great tit (Parus major) in relation to body mass, temperature, food availability and clutch size. Functional Ecology 8, 563–572.
Travis J M J (2003) Climate change and habitat destruction: a deadly anthropogenic cocktail. Proc. R. Soc. Lond. B 270, 467–473.
Urban M C (2015) Accelerating extinction risk from climate change. Science 348, 571–573.
Verhulst S, Nilsson J Å (2008) The timing of birds’ breeding seasons: a review of
experiments that manipulated timing of breeding. Phil. Trans. R. Soc. B. 363, 399–410.
Visser M E, te Marvelde L, Lof M E (2011) Adaptive phenological mismatches of birds and their food in a warming world. Journal of Ornithology 153, 75–84.
Wilson R J, Gutiérrez D, Gutiérrez J, Martínez D, Agudo R, Monserrat V J (2005) Changes to the elevational limits and extent of species ranges associated with climate change.
Ecology Letters 8, 1138–1146.
22
(2017) Our globally changing climate. In D J Wuebbles, D W Fahey, K A Hibbard, D J Dokken, B C Stewart, T K Maycock (Eds.), Climate Science Special Report: Fourth National Climate Assessment, Volume I.
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Appendix 1: Species included in the study and their traits regarding breeding season, number of broods per season, migration behaviour and thermal niche
Fix = fixed number of broods per season Var = varied number of broods per season LDM = long-distance migrant SDM = short-distance migrant
Species Scientific name Breeding
season Number of broods Migration behaviour Thermal niche
Barred warbler Sylvia nisoria May-July Fix LDM Warmer Black redstart Phoenicurus
ochruros
May-July Var SDM Warmer
Blackbird Turdus merula March-August Var SDM Warmer
Blackcap Sylvia atricapilla May-July Var SDM Warmer
Blue tit Cyanistes caeruleus May-July Var SDM Warmer Bluethroat Luscinia svecica June-August Fix LDM Colder Brambling Fringilla
montifringilla
May-July Fix SDM Colder
Bullfinch Pyrrhula pyrrhula May-July Var SDM Colder
Chaffinch Fringilla coelebs May-June Var SDM Warmer
Chiffchaff Phylloscopus collybita
May-July Var SDM Warmer
Coal tit Periparus ater April-July Var SDM Warmer
Common redpoll
Acanthis flammea May-July Var SDM Colder
Dunnock Prunella modularis April-August Var SDM Colder
Fieldfare Turdus pilaris May-August Var SDM Colder
Garden warbler Sylvia borin May-August Var LDM Colder
Goldcrest Regulus regulus May-July Var SDM Colder
Goldfinch Carduelis carduelis May-August Var SDM Warmer Grasshopper
warbler
Locustella naevia April-August Fix LDM Colder
Great grey shrike
Lanius excubitor April-June Fix SDM Colder
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Greater whitethroat
Sylvia communis May-August Fix LDM Warmer
Greenfinch Chloris chloris May-July Var SDM Warmer
House martin Delichon urbicum May- September
Var LDM Warmer
Icterine warbler Hippolais icterina May-August Fix LDM Colder Lesser
whitethroat
Sylvia curruca May-August Fix LDM Colder
Linnet Linaria cannabina April-August Var SDM Warmer
Long-eared owl Asio otus March-July Fix SDM Warmer
Marsh warbler Acrocephalus palustris
June-August Fix LDM Warmer
Pied flycatcher Ficedula hypoleuca May-June Fix LDM Colder Red-backed
shrike
Lanius collurio May-July Fix LDM Warmer
Red-breasted flycatcher
Ficedula parva May-June Fix LDM Warmer
Redstart Phoenicurus phoenicurus
May-July Var LDM Colder
Redwing Turdus iliacus May-July Var SDM Colder
Reed bunting Emberiza schoeniclus
May-July Var SDM Colder
Reed warbler Acrocephalus scirpaceus
May-August Var LDM Warmer
Robin Erithacus rubecula April-July Var SDM Warmer
Scarlet rosefinch
Carpodacus erythrinus
May-July Fix LDM Colder
Sedge warbler Acrocephalus schoenobaenus
May-August Fix LDM Colder
Siskin Spinus spinus April-August Var SDM Colder
Song thrush Turdus philomelos March-August Var SDM Colder Sparrowhawk Accipiter nisus May-August Fix SDM Warmer
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flycatcher
Swallow Hirundo rustica May-September
Var LDM Warmer
Thrush nightingale
Luscinia luscinia May-July Fix LDM Warmer
Tree pipit Anthus trivialis April- August Var LDM Colder
Whinchat Saxicola rubetra May-July Fix LDM Colder
Willow warbler Phylloscopus trochilus
May-July Var LDM Colder
Wood warbler Phylloscopus sibilatrix
May-July Fix LDM Colder
Wren Troglodytes
troglodytes
April-July Var SDM Warmer
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Appendix 2: Weather stations used to calculate mean temperature of the recruitment area
City Weather station Time period
Falun Falun-Lugnet February 1972-September 2018
Vintjärn July 1982, February 1983
Borlänge flygplats February-May 2006 Jokkmokk Jokkmokk February 1972-June 2018
Jokkmokk
flygplats Mo
May-August 2000, August-September 2009, April 2011, August 2011, June 2012, August 2012, April 2013, August 2013, April 2018, July-September 2018
Nattavaara by July 1975, June-July 1999, August 2002, August 2003 Linköping Malmslätt February 1972-September 2018
Umeå Umeå flygplats February 1972-September 2018
Holmögadd A March 1998, June 1998
Uppsala Uppsala February 1972-September 1985 Uppsala Aut February 1986-September 2018
Växjö Växjö February 1972-September 2006
Växjö A June 1999, February-September 2002, July 2004, August 2006, February 2007-September 2018
Växjö-Kronoberg July 1986
Vänersborg Vänersborg February 1972-September 2018
Såtenäs March 1984
Östersund Frösön February 1972-September 2018
Frösön D September 2005
Joensuu Liperi Joensuu lentoasema
January 1972-September 2018
Kajana Kajaani lentoasema January 1972-September 2018 Lampis Hämeenlinna
Lammi Pappila
January 1972-September 2018
Sodankylä Sodankylä Tähtelä January 1972-September 2018 Uleåborg Hailuoto Keskikylä January 1972-September 2018 Ylistaro Seinäjoki Pelmaa January 1972-September 2018
