Biological Conservation 143 (2010) 2006–2019 Contents lists available at ScienceDirect Biological Conservation journal homepage: www.elsevier.com/locate/biocon Hypotheses to explain patterns of population change among breeding bird species in England Chris B. Thaxter a,*, Andrew C. Joys a, Richard D. Gregory b, Stephen R. Baillie a, David G. Noble a a b British Trust for Ornithology, The Nunnery, Thetford, Norfolk IP24 2PU, UK Royal Society for the Protection of Birds, The Lodge, Sandy, Bedfordshire SG19 2DL, UK a r t i c l e i n f o Article history: Received 30 October 2009 Received in revised form 7 May 2010 Accepted 8 May 2010 Available online 11 June 2010 Keywords: Afro-Palaearctic Bioclimatic zone Breeding habitat Climatic niche Over-wintering Migration a b s t r a c t Population declines are now evident across many taxa, but within each assemblage there is often considerable variation in constituent population trends. We used bird population trends produced from the BTO/JNCC Common Birds Census (CBC) and the RSPB/BTO/JNCC Breeding Bird Survey (BBS), to test five main hypotheses to explain population changes of 59 breeding species in England (1967–2006): (1) breeding habitat, (2) predation risk to nest sites, (3) species climatic niche, (4) migration strategy, and (5) over-wintering bioclimatic zones of migrants, accounting for additional demographic and ecological traits. In absence of phylogenetic inter-relatedness, farmland species declined more than woodland species, most pronounced prior to 1986, probably reflecting agricultural intensification (1). We found limited support that ground nesters have declined more than above-ground or cavity nesters (2), and there was some indication that species with more northerly European distributions showed larger declines than more southerly-distributed species (3). Larger population declines were recorded for Afro-tropical migrants than species wintering in Europe or in the UK, most notable prior to 1986 (4). However, declines were not uniform across all migrants (5) – species over-wintering in the arid savannah bioclimatic zone of Africa decreased in population between 1967 and 1976, whereas species wintering in humid West African forest and savannah declined more after 1987. These results suggest both breeding and over-wintering factors influenced population trends. European countries signed to the Convention on the Conservation of Migratory Species of Wild Animals are required to protect and conserve populations of migrants. Understanding connectivity between breeding and over-wintering populations, and similar environmental pressures experienced within over-wintering areas may be a useful step towards mitigating against further declines in migrants. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Assemblages of species across a wide-range of taxa have shown substantial population declines in recent years (IUCN, 2010). However, patterns of population changes for constituent species are often mixed within these assemblages; therefore, the potential risk of extinction is not evenly distributed (Owens and Bennett, 2000; Thomas et al., 2004). Thus, understanding shared ecological and life history characteristics of species showing similar population changes, including those declining species more vulnerable to extinction, can help direct conservation and management priorities (Amano and Yamaura, 2007). A number of widespread and common breeding bird species have experienced declines in both population size and breeding range in the United Kingdom (UK) and across Western Europe in recent decades (Fuller et al., 1995; Gregory et al., 2007; Reif et al., 2008). The * Corresponding author. Tel.: +44 1842 750050; fax: +44 1842 750030. E-mail address: chris.thaxter@bto.org (C.B. Thaxter). 0006-3207/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2010.05.004 causes of these declines in the UK have been well documented for a number of farmland species (Fuller et al., 1995; Newton, 2004b), and have been attributed to intensification of agricultural practice within breeding habitats (O’Connor and Shrubb, 1986; Fuller et al., 1995; Robinson and Sutherland, 2002). Within the UK, larger declines have also been reported for farmland species than woodland species. However, patterns are generally mixed for woodland species across Europe (Hewson et al., 2007; Reif et al., 2008; Seoane and Carrascal, 2008), many of which have suffered declines in population (Fuller et al., 2005; Gregory et al., 2007; Hewson et al., 2007), and are placed as having unfavourable conservation status in the UK (Eaton et al., 2009) and at the European level (Birdlife International, 2004). Specialist species, reliant on specific habitat niches and diets have, showed larger declines than generalist species for both habitats (Siriwardena et al., 1998; Gregory et al., 2004, 2007; Hewson et al., 2007). Predation or lack of nesting sites may also limit populations of species if for instance habitat change exposes them to greater risk (Martin and Clobert, 1996; Chalfoun et al., 2002; Gregory et al., 2007). 2007 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 Population change, however, is not restricted to processes operating in breeding habitats. Species that breed in Europe but winter in Africa have shown larger population declines than those that are more sedentary (Kanyamibwa et al., 1990; Baillie and Peach, 1992; Berthold et al., 1998; Berthold, 2001; Sanderson et al., 2006; Moller et al., 2008). Such declines may be driven by environmental conditions (Peach et al., 1991; Kanyamibwa et al., 1993), food availability (Newton, 2004a), and linked to climate change; migrants may be at a competitive disadvantage compared to shorter distance migrants or sedentary residents that can return earlier to breeding grounds (Sanderson et al., 2006). Among migrants, those species showing plasticity in timing of migration and arrival times with breeding food resources are more likely to avoid trophic mis-matches (Both et al., 2006; Moller et al., 2008). Population changes of long-distance migrants may also depend on where species over-winter in Africa (Newton, 2004a). For instance, wintering zones of African migrants can broadly be delineated into arid Savannah zones of the Sahel and humid tropic regions (‘‘bioclimatic zones”, Hewson and Noble, 2009). Differences have been recorded between these groupings for woodland species in the UK, therefore, common climatic or habitat-related challenges, such as intensity of land use, may be faced by species wintering in similar bioclimatic zones (Hewson and Noble, 2009). Species may also show population changes in relation to their climate envelope (Jiguet et al., 2007). Within Europe, species with more northerly breeding ranges and lower tolerance of maximum temperatures at the southern edge of their range have shown largest declines within Europe, representing responses to climate change (Julliard et al., 2004; Jiguet et al., 2007; Lemoine et al., 2007). Population changes have also been found to vary in relation to body mass of species (Bennett and Owens, 2002; Amano and Yamaura, 2007), breeding population size (Henle et al., 2004), brain size (Shultz et al., 2005; Moller, 2008), and the distance species are willing to fly to escape predation (Moller, 2008). Therefore, identifying ecological drivers of populations related to species traits in a comparative manner (e.g. Amano and Yamaura, 2007; Seoane and Carrascal, 2008; Moller, 2008; Hewson and Noble, 2009) may help identify vulnerable species that are not routinely monitored. This approach is potentially more cost-effective than investing large amounts of time and resources on individual species-intensive studies (Siriwardena et al., 1998). Within England, bird population trends are routinely produced from the BTO/JNCC Common Birds Census (CBC) and the RSPB/BTO/JNCC Breeding Bird Survey (BBS). However, to date there has been no complete ecological comparison between key hypotheses of population change for the whole census time period available. A recent study (Hewson and Noble, 2009) analysed population changes using CBC data to its final year (2000), however the study focused on woodland sites, and did not include assessment of some other variables such as climatic niche that species adopt, which could also influence population changes. Here, we test five hypotheses to explain changes in breeding bird populations for 59 species in England for the full time period available (1966–2007); predictions under each are presented in Table 1. We hypothesise that populations will vary in relation to (1) main breeding habitat (farmland and woodland), (2) predation risk of nests (Ground, above-ground, and cavity nesters), (3) climatic niche (latitudinal midpoint of European breeding range), (4) migration strategy used (Afro-tropical, European, or over-wintering in the UK); finally, we considered a hypothesis for African migrants, testing whether trends are related to (5) specific bioclimatic zones in Africa. Table 1 Table of hypotheses proposed to explain changes in population of breeding birds in England, together with associated predictions expected under each; one variable was tested under each hypothesis. Hypothesis Prediction References 1. Breeding habitat Farmland species will show steeper declines than woodland species due to larger scale agricultural habitat changes that have taken place Fuller et al. (1995), Gregory et al. (2007) 2. Predation risk of nest Species that nest on the ground will be more at risk to predation than species nesting above-ground or in cavities, hence will show bigger population declines Gregory et al. (2007) 3. Climatic niche Species with more northerly European distributions, or reduced tolerance to maximum southerly temperatures will show declines compared to southerly distributed or more temperature tolerant species Jiguet et al. (2007), Moller et al. (2008) 4. Migration Strategy Species that over-winter in Africa (Afro-tropical migrants) will show greater declines than species wintering in Europe, or species wintering within the UK Sanderson et al. (2006) 5. Wintering bioclimatic zone African migrants will differ in their population trends linked to whether they winter in arid or humid bioclimatic zones Hewson and Noble (2009) 2. Materials and methods 2.1. Monitoring programmes We used long-running monitoring schemes that routinely produce annual population trends for a wide-range of species, mainly the CBC and BBS. The CBC began in 1962 using a territory mapping method for farmland and woodland plots, however this scheme ended in 2000 and has now been replaced by the BBS, which began in 1994 (see Risely et al., 2009 for sampling distribution). The BBS uses line-transect methodology consisting of two roughly parallel 1 km length transects that are surveyed twice per breeding season (April–June), within a randomly allocated 1  1 km square of the National Grid. Squares are selected through stratified random sampling by observer density. Both CBC and BBS surveys were run in parallel for seven years to allow calibration (Freeman et al., 2003) and for most species, population trends were not significantly different between the two surveys, providing a complete time series between 1966 and 2007. Where a difference was observed, species were excluded from analysis. We focus here on trends for England rather than the UK, due to superior correspondence between CBC and BBS, given that most CBC survey plots were located in England. We investigated 59 species, from the suite of 69 species for which trends are routinely produced (Baillie et al., 2010). We excluded three introduced species (Little Owl Athene noctua, Red-legged Partridge Alectoris rufa, Pheasant Phasianus colchicus), four waterbirds (Coot Fulica atra, Mallard Anas platyrhynchos, Moorhen Gallinula chloropus and Mute Swan Cygnus olor), and three species where there was disparity between BBS and 2008 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 CBC trends (house sparrow Passer domesticus, sparrowhawk Accipiter nisus, and collared dove Streptopelia decaocto), assessed through statistical comparisons of the fluctuations and turning points of trends between the two schemes. A potential caveat to these datasets is that changing detectability of species may influence the likelihood of observing species over time; however, we believe such effects would be minimal, albeit not yet quantified. 2.2. Generation of population indices Data collected under CBC and the BBS consist of annual counts over a period of years at a series of sites. Population trends can therefore be represented as a generalised linear model (GLM), modelling count as a function of site and year, using a Poisson error distribution and log-link function (ter Braak et al., 1994; Pannekoek and van Strien, 1996). Individual parameter estimates were generated for each year providing a relative index of population size. To prevent short-term fluctuations, arising from natural population variability and statistical error, having an undue influence on the overall long-term trend, real GLM trends were smoothed to extract the long-term pattern of population change. We used a non-parametric thin-plate smoothing spline with 11 degrees of freedom specified from 0.3 times the number of years 1966– 2007 (Fewster et al., 2000). To avoid problems associated with serial correlation within the count data, we used 199 bootstraps, sampling with replacement from the original dataset, which were also smoothed, thus generating standard errors around the trend estimates. Generation of all population indices was undertaken in SAS 9.1 (SAS Institute, Inc). 2.3. Data manipulation of population indices We used population change measures for each species across the time series of population indices, calculated from the smoothed population indices as a ratio (last/first year) for the period of interest. These changes were calculated for the complete time period 1967–2006, and sub-divided into four equal time periods: 1967– 1976, 1977–1986, 1987–1996, and 1997–2006 (Hewson and Noble, 2009). The total time series was not split for any a priori decision linked to specific ecological drivers. Rather, sub-periods were used to obtain greater temporal resolution allowing detection of population change at different temporal scales, important when investigating different ecological factors that may operate at different temporal scales (Hewson and Noble, 2009). For smoothed time series we did not include first and last years of the series (in this case 1966 and 2007), as these years have a large influence on the direction of trend in the series and may thus bias population changes (see Baillie et al., 2010 for more details). The 95% confidence intervals across smoothed bootstraps provided a measure of precision of the change for each species for each time period. Examples of smoothed trends are displayed in Appendix (Fig. A1). 2.4. Ecological variables Ecological variables included in this study are presented in Appendix (Table A1 and species population changes are shown in Appendix (Table A2). Population trends were assessed in relation to breeding habitat by splitting species into farmland (n = 18) and woodland (n = 29) (Wernham et al., 2002; Baillie et al., 2010). Species belonging to three other categories of urban, upland, and wetland were also analysed in this study. However, we did not have adequate power to reliably test these habitat categories, hence we grouped these species as ‘‘other” (n = 12). We assessed whether species that nest on the ground were more vulnerable to predation than those species that do not, by dividing species into ground nesters (n = 10), above-ground nesters (n = 31), and cavity or hole nesters (n = 18), based on information in Wernham et al. (2002). To test whether species varied in population in relation to the climatic niche adopted, we extracted the latitudinal midpoint of the European breeding distribution (Lemoine et al., 2007), calculated as the mean of the northernmost and southernmost extents of species’ distributions from EBCC Atlas data (Hagemeijer and Blair, 1997). We also tested a separate variable of ‘‘thermal maximum” (Jiguet et al., 2007), relating to the thermal tolerance of species at the leading southern edge of the species range, available for 47 species. We tested whether long-distance migrants have shown bigger population declines than other species, by separating Afrotropical migrants (n = 15) from those species that over-winter in Europe (n = 13) or remain within the UK over-winter (n = 31) (after Wernham et al., 2002). In a separate analysis, we examined whether Afro-tropical migrants showed differences to both European and UK species combined. We investigated whether Afrotropical migrants showed similarities in breeding population by bioclimatic wintering zones (Hewson and Noble, 2009); species were separated into wintering in humid tropics and forest south of the Sahel (typified by Guinean forest and savannah of West Africa) (n = 7), and those wintering just south of the Sahara in an arid savannah habitat (n = 8) (Cramp, 1977–1994; Curry-Lindahl, 1981; Wernham et al., 2002). Following Hewson and Noble (2009), we included chiffchaff Phylloscopus collybita in the ‘‘arid” grouping, but excluded blackcap Sylvia atricapilla from migrant groupings, due to a lack of evidence that the species crosses the Sahara (Wernham et al., 2002). The Barn Swallow Hirundo rustica winters in southern Africa, however of those species assessed here, it is the only species to do so, thus preventing a formal assessment of the southern bioclimatic zone. We therefore included barn swallow in the ‘‘humid” grouping, because it is known from ringing recoveries to pass through the humid tropics of West Africa on migration (Wernham et al., 2002). Previous studies have suggested that populations may vary in relation to population size (Sæther and Engen, 2002; Henle et al., 2004), relative brain mass (Shultz et al., 2005), body mass (Bennett and Owens, 2002; Amano and Yamaura, 2007), flight distance (Moller, 2008), and annual fecundity (Sæther and Bakke, 2000), the latter representing a good proxy for other demographic rates (Sæther, 1988). Therefore, these variables were controlled for in this study. Population size and body mass of birds was extracted from Wernham et al. (2002). Breeding range was inevitably correlated to population size (e.g. Holt et al., 2002), and hence was not included in this study. We included a measure of productivity as a surrogate for annual fecundity, here calculated as the clutch size multiplied by the number of broods. Information on brain mass was taken from Garamszegi et al. (2002) and Moller et al. (2008), and following Moller et al. (2008), we used phylogenetically independent contrasts to regress brain mass (g) with body mass (g), accounting for phylogeny, and used the residuals of the relationship for inclusion as relative brain size in analyses [PIC regression equation: log(brain mass) = 0.617 [±0.033]  log(body mass). To allow for the possibility of non-linear relationships we also tested quadratic terms for continuous variables (e.g. Fig. 1 in Amano and Yamaura, 2007), but initial analysis suggested no significant improvement in prediction of population change for these terms. Hence to avoid excessive reduction in residual degrees of freedom, we excluded quadratic terms from further analysis. Diet and degree of specialisation has been found to influence population trends in some studies (Gregory et al., 2007). We did not include diet in this study because it was confounded by breeding habitat where a higher proportion of seed-consumers were present for farmland species. Population change, breeding population size, and body mass were log transformed, and latitudinal midpoint of breeding range was centralised, prior to analyses. 2009 Population change % (0 = no change) Population change % (0 = no change) C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 (a) 80 Farmland (n = 18) Woodland (n = 29) Other (n = 12) * * * 80 60 60 40 40 20 20 0 0 −20 −20 −40 −40 −60 −60 −80 (c) 67−06 67−76 77−86 87−96 97−06 African (n = 15) European (n = 13) UK (n = 31) −80 67−06 67−76 77−86 87−96 97−06 Arid (n = 7) Humid (n = 8) 80 * * * 60 40 40 20 20 0 0 −20 −20 −40 −40 −60 −60 −80 * (d) 80 60 Above ground (n = 31) Ground (n = 10) Hole/cavity (n = 18) (b) 67−06 67−76 77−86 87−96 97−06 −80 * 67−06 Observation periods (years) * * 67−76 77−86 87−96 97−06 Observation periods (years) Fig. 1. Changes in breeding population of species (±1 SE) in England in relation to: (a) Breeding habitat: farmland, woodland, and ‘‘other” (see text for details); (b) Predation risk to nest sites: ground nesters, above-ground nesters, and cavity nesters; (c) Migration strategy: species wintering in the UK, compared to species wintering in Europe, and species wintering in Africa; and (d) Afro-tropical migrants: bioclimatic zones of humid and arid zones; ‘‘” denotes significant multivariate result; see Table 3 for significance of coefficient levels. 2.5. Statistical analyses Univariate analyses were initially used to explore relationships and understand patterns between ecological variables and dependent variables; these are presented in Appendix (Table A3). We then performed complete multivariate analyses testing hypotheses relating to breeding habitat, predation risk, climatic niche, and migration strategy using the full suite of 59 species; separate analyses were then conducted for Afro-tropical migrants (n = 15) only, to test the variable of bioclimatic wintering zones. We used phylogenetic generalised least squares (PGLS) regression to control for phylogenetic dependence in our data (Grafen, 1989; Martins and Hansen, 1997). We used the avian phylogeny of Thomas (2008) and obtained genetic distances of branch lengths between species using the available electronic version of the maximum credibility tree. The tree was processed and incorporated into PGLS models using the Analysis of Phylogenetics and Evolution (APE) package (Paradis, 2004) in R V. 2.10.1. (The R Development Core Team, 2010) (Appendix (Fig. A2). Within PGLS models, the covariance matrix was modified to accommodate the magnitude of deviation from a standard Brownian motion structure through specifying a measure of phylogenetic correlation k Freckleton et al., 2002. The k values for each model were tested against a model assuming Brownian Motion (k = 1), and a model with no phylogentic dependence (k = 0, Freckleton et al., 2002). The k values were significantly different from an ordinary least squares model of zero in the majority of cases (likelihood ratio tests, P < 0.05), therefore we retained a phylogenetic correlation structure in all models. To account for the hierarchical nature of these analyses (i.e. initial GLM population trends, used in further PGLS analyses), we specified model weights in all PGLS models of as log(1/SE) of change from bootstrapped smoothed population trends, thus giving greater weighting to more precise estimates. All models were specified using residual maximum likelihood (REML). Best models were selected through a step-down term dropping procedure using all variables, and then sequentially removing non-significant terms until a minimum adequate model containing final significant predictors was obtained (Zuur et al., 2009). All population changes are presented as b-estimates (±SE) from multivariate regression models. 3. Results 3.1. General population trends During the period 1967–2006, 56% species (33/59) declined, nine of which experienced significant declines greater than 75%, with a further ten species experiencing significant declines greater than 50%. The greatest number of species experiencing significant declines was between 1977 and 1986 (31 species). Between the periods 1987–1996 and 1997–2006, similar num- 2010 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 Table 2 Minimum adequate models from multivariate phylogenetic generalised least squares analyses, for periods of 1967–2006, 1967–1976, 1977–1986, 1987–1996, and 1997–2006; hypotheses proposed to explain population changes for ‘‘all species” included: (1) climatic niche (latitudinal midpoint of European breeding range), (2) migration strategy (UK migrants, European migrants, African migrants), (3) breeding habitat (wood, farm, other), (4) predation risk to nest sites (‘‘Nesting habitat”: Above-ground, ground, cavity); a subanalysis was conducted for African migrants only testing (5) bioclimatic wintering zones (Humid, Arid). Other ecological traits were also controlled for (see text for details); nDF = numerator degrees of freedom; Level = factor level; b = model beta coefficients; factor level coefficients are expressed relative to a common intercept containing the first factor level. All species nDF F P Level b SE t P 1967–2006 Migration 2 3.291 0.045 Europe UK 0.066 0.014 1 2 3.887 4.271 0.054 0.019 2.902 2.02 0.005 0.048 Breeding population size Residual df 1 52 7.293 0.009 0.137 0.142 0.024 0.137 0.121 0.070 1.882 2.549 Latitudinal midpoint Breeding habitat 0.257 0.363 0.055 0.397 0.231 0.273 African migrants Bioclimatic zone Breeding habitat 1 2 6.064 5.426 0.034 0.025 Humid Other Wood 0.326 0.587 0.400 0.132 0.178 0.185 2.463 3.290 2.168 0.034 0.008 0.055 Residual df 12 1967–1976 Migration 2 12.153 <0.001 Breeding habitat 2 3.252 0.047 Europe UK Other Wood 0.000 0.001 0.040 0.042 1 53 5.575 0.022 0.060 0.056 0.059 0.051 0.049 4.836 3.704 2.112 2.080 Body mass Residual df 0.288 0.207 0.124 0.105 0.117 African migrants Bioclimatic zone Breeding habitat 1 2 10.129 25.709 0.015 <0.001 Humid Other Wood 0.210 0.438 0.465 0.066 0.140 0.066 3.183 3.140 7.084 0.015 0.016 0.000 Residual df 12 1977–1986 Migration 2 6.012 0.004 Breeding habitat 2 8.154 <0.001 Europe UK Other Wood 0.002 0.006 0.156 0.000 1 1 52 6.305 13.776 0.015 <0.001 0.065 0.056 0.060 0.051 0.033 0.042 3.284 2.851 1.440 3.925 Breeding population size Body mass Residual df 0.215 0.159 0.087 0.199 0.082 0.157 1987–1996 Nesting habitat 2 4.405 0.017 Ground Cavity 0.213 0.121 0.078 0.064 2.725 1.901 0.009 0.063 Residual df 56 African migrants Bioclimatic zone Nesting habitat 1 2 10.962 6.159 0.008 0.018 Humid Ground Cavity 0.254 0.374 0.057 0.077 0.107 0.084 3.311 3.509 0.683 0.008 0.006 0.510 Residual df 12 1997–2006 Latitudinal midpoint Residual brain mass Breeding population size Residual df 1 1 1 55 4.236 7.297 12.078 0.044 0.009 <0.001 0.017 0.051 0.083 0.008 0.019 0.024 Other Wood African migrants None significant African migrants None significant bers of species declined (20 and 16, respectively), and species generally fared better during the early part of the time series (1967–1976) when only nine species experienced a significant decline. 3.2. Breeding habitat We detected significant differences for breeding habitat in the early part of our time series, (1967–1976, 1977–1986), as well as the total time period 1967–2006 (Table 2, Fig. 1). Farmland species showed marginally larger declines than woodland species between 1967 and 1976 (woodland, b = 0.105 ± 0.051), and larger declines between 1977 and 1986 (woodland, b = 0.199 ± 0.051, Table 2, Fig. 1), which resulted in larger overall decreases between 1967 and 2006 (woodland, b = 0.231 ± 0.121, Table 2, Fig. 1). No significant differences were observed for the periods 1987–1996 (F2,52 = 2.407, P = 0.100), and 1997–2006 (F2,51 = 0.558, P = 0.576). 2011 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 3.3. Predation risk: nesting habitat There was no significant difference in population changes of species in relation to nesting habitat between 1967 and 2006 (F2,48 = 0.285, P = 0.753), nor were any differences apparent for the periods 1967–1976 (F2,47 = 0.194, P = 0.825), 1977–1986 (F2,49 = 1.512, P = 0.231), and 1996–2006 (F2,47 = 0.008, P = 0.9). This pattern may have been due to a greater importance of breeding habitat, or a possible surrogacy of nesting habitat for breeding habitat, since 70% (7/10) species nesting on the ground were also classified as farmland species. However, ground-nesting species showed a significant decline compared to those that nest aboveground and in cavities for the period 1987–1996 (Table 2, Fig. 1). 3.4. Climatic niche The European latitudinal midpoint of species breeding ranges, was a marginally significant predictor of population size between 1967 and 2006, a significant predictor between 1997 and 2006 (Table 2), but was not significant between the periods 1967–1976 (F1,50 = 0.464, P = 0.499), 1977–1986 (F1,49 = 0.310, P = 0.580), and 1987–1996 (F1,51 = 1.722, P = 0.195). Negative coefficients (Table 2) indicated that species with more southerly European distributions were more likely show favourable trends than more northerly populations (Table 2). A further analysis of 48 species, including thermal maximum tolerance at the southern European edge, also revealed significant positive relationships between the same periods 1967– 2006 (F1,46 = 5.169, P = 0.027) and 1997–2006 (F1,44 = 7.381, P = 0.009), indicating that species generally capable of tolerating higher temperatures are more likely to show favourable populations. Maximum tolerance was not significant for any other time periods (1967–1976, F1,40 = 0.745, P = P = 0.393; 1977–1986, F1,36 = 0.492, P = 0.487; 1987–1996, F1,41 = 1.743, P = 0.194). European and UK species showed larger decreases (European b = 0.215 ± 0.065; UK b = 0.159 ± 0.056, Table 2, Fig. 1); no significant contrasts were shown between European and UK species in any period (all t-tests P > 0.05). The three category migration delineation was not significant between the periods 1987–1996 (F2,54 = 1.643, P = 0.203), and 1997–2006 (F2,47 = 0.675, P = 0.514). Due to a lack of difference between European and UK species, a separate analysis was performed grouping these species separate to Afro-tropical migrants; similar to before, African migrants experienced greater decreases than European and UK species for the periods 1967– 2006 (F1,53 = 4.46, P = 0.039; b = 0.054 ± 0.026) and 1967–1976 (F1,54 = 21.30, P < 0.001, b = 0.242 ± 0.052), greater increases for 1977–1986 (F1,53 = 10.19, P = 0.002, b = 0.173 ± 0.054), but marginal decreases were also detected for the periods 1987–1996 (F1,55 = 4.11, P = 0.048, b = 0.131 ± 0.064), and 1997–2006 (F1,55 = 4.08, P = 0.048, b = 0.079 ± 0.039). 3.6. Bioclimatic wintering zones Afro-tropical migrants (n = 15) were tested for differences in population changes in relation to their over-wintering bioclimatic zones. Overall humid species showed significantly larger declines than arid species between 1967 and 2006 (humid species, b = 0.326 ± 0.132, Tables 2 and 3, Fig. 1). However, early initial declines of migrants during 1967–1976 were driven through arid species, showing greater declines than humid species (humid, b = 0.210 ± 0.066, Tables 2 and 3, Fig. 1). There was no significant difference between humid and arid species between 1977 and 1986 (F1,10 = 2.350, P = 0.156), but thereafter humid species showed a decline greater compared to arid species between 1987 and 1996 (humid, b = 0.254 ± 0.077, Tables 2 and 3 Fig. 1); the final time period (1997–2006) also showed humid species in greater decline than arid species, albeit not significantly so (F1,12 = 1.863, P = 0.197; b = 0.071 ± 0.052). 3.5. Migration strategy 3.7. Additional variables African migrants were compared to those species reaching European destinations ‘‘European species”, and those remaining in the UK over-winter ‘‘UK species”. Between 1967 and 2006, African migrants declined significantly more than European and UK species (Table 2, Fig. 1). During the early part of the series (1967 and 1976) both European (b = 0.288 ± 0.060) and UK species (b = 0.207 ± 0.056) showed significantly more favourable population changes than African species (Table 2, Fig. 1). However, between 1977 and 1986 African migrants showed little change in population but Breeding population size was a significant predictor of population change, showing positive correlations for periods of 1967– 2006, 1977–1986, and 1997–2006 (Table 2). Thus, species with larger populations showed more favourable population changes than species with smaller populations. Brain mass, productivity and flight distance were not significant predictors for the period 1967–2006. There was also evidence to suggest species with larger body sizes decreased more than smaller bodied species between Table 3 Changes in populations of Afro-Palaearctic migrants breeding in England for periods: 1967–2006, 1967–1976, 1977–1986, 1987–1996, and 1997–2006; species by wintering bioclimatic zones. Population changes are given as +, 0.1–25% increase, + +, 26–50% increase, + + +, 51% + increase, -, 0.1–25% decrease, - -, 26–50% decrease, - - -, 51% + decrease; non-significant changes are given in brackets, all other changes are significant. Species Winter bioclimate 1967–2006 1967–1976 1977–1986 1987–1996 1997–2006 Yellow Wagtail Motacilla flava Lesser Whitethroat Sylvia curruca Redstart Phoenicurus phoenicurus Sedge Warbler Acrocephalus schoenobaenus Whitethroat Sylvia communis Reed Warbler Acrocephalus scirpaceus Chiffchaff Phylloscopus collybita Cuckoo Cuculus canorus Spotted Flycatcher Muscicapa striata Tree Pipit Anthus trivialis Turtle Dove Streptopelia turtur Willow Warbler Phylloscopus trochilus House Martin Delichon urbicum Garden Warbler Sylvia borin Swallow Hirundo rustica Arid Arid Arid Arid Arid Arid Arid Humid Humid Humid Humid Humid Humid Humid Humid --(-) (-) ---(+ + +) ++ ----------(- - -) (-) (+) (-) (+) --(- -) --(-) -(-) (+) (+) (-) (+) -(-) (-) (+) +++ --(+) + -(-) -(+) (- -) +++ - --(+) (+) +++ (+) +++ ------(- -) (-) (+) -+ (-) + + + --(-) ---(+) + 2012 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 1967 and 1976, but increased more between 1977 and 1986 (Table 2). During the period 1997–2006, species with larger relative brain size showed more favourable population changes than species with smaller relative brain sizes (b = 0.051 ± 0.019, Table 2). 4. Discussion This study has shown that population changes of breeding bird species in England were mainly driven by breeding habitat and migration strategy, whereby farmland species declined more than woodland species (hypothesis 1), and Afro-tropical migrants have declined more than species wintering in European or the UK (hypothesis 4). However a key further finding was that migratory species reaching African destinations have shown similarity in changes in population in relation to bioclimatic wintering zones in Africa (hypothesis 5). These conclusions were offset against a significant effect of climatic niche (hypothesis 3), and were independent of phylogenetic relatedness between species, and confounding variables that are also known to influence population trends. 4.1. Breeding habitat and predation risk to nest sites Greater declines for farmland species than woodland species were observed between 1967 and 2006, but were most pronounced between 1977 and 1986, thus matching the well-documented pattern observed by other studies (Chamberlain et al., 2000; Vickery et al., 2001). During this period, intensification of agricultural practice has taken place, and changes in farming practice have led to changes in land use, such as reduced over-winter stubbles, reducing available food for species, thus influencing survival (Chamberlain et al., 2000; Vickery et al., 2001; Robinson and Sutherland, 2002; Benton et al., 2003; Gillings et al., 2005). Within breeding habitats, we detected only limited support for predation risk to nest sites influencing their trend (hypothesis 3). However, there was some evidence to suggest that ground-nesting species have showed greater declines than cavity nesters or above-ground nesters between 1987 and 1996, in line with previous findings of Gregory et al. (2007) for European woodland species. reduced food availability and habitat degradation in dry open habitats across Africa (Sanderson et al., 2006). In particular, a period of aridity occurred on the Western Sahel in the late 1960’s until ca. 1990 when rainfall levels increased, albeit still lower than the 30 years prior to 1960 (Nicholson et al., 2000). Such changes most likely impact on open habitats, leading to desertification, habitat degradation, and reductions in over-winter food availability for migrants, and hence decreases in population and survival (Kanyamibwa et al., 1990, 1993; Peach et al., 1991; Baillie and Peach, 1992; Schaub et al., 2005; Robinson et al., 2008). Indeed, our most significant finding was that population changes of African migrants differed significantly depending on over-wintering bioclimatic zones that species are believed to use. Between 1967 and 1976 declines in African migrants were driven through arid zone species wintering just south of the Sahara in an arid savannah habitat, most pronounced for redstart Phoenicurus phoenicurus and whitethroat. (Table 3). Little differences were apparent between 1977 and 1986, however, between 1987 and 1996 species wintering in humid tropics, typified by Guinean forest and savannah south of the Sahel, showed significantly steeper declines than arid zone species (Table 3). Declines in humid zone species also continued between 1997 and 2006, although not significantly more so than arid zone species. Results here support previous findings of Hewson and Noble (2009), but for a wider range of migrant species, thus giving greater certainty in the relationships between wintering zones and population changes, across a longer time period than previously considered. Patterns of rainfall for open Savannah habitats prior to 1990 may therefore match the decrease in arid zone migrants prior to 1986. Significant declines in most humid species between 1987 and 1996 (Table 3), also suggests a possible common factor operating. However, the situation is likely to be more complex given that some species may use the Sahel as an important staging (Jones et al., 1996), and species may also move around during winter encountering different habitats (Jones, 1985). The exact wintering areas of most African migrants are still somewhat uncertain (Wernham et al., 2002), therefore linking finerscale habitat changes with specific population changes may not currently be achievable. However, the approach of identifying broad divisions in the environment and shared pressures experienced by species could assist conservation priorities and focus future research. 4.2. Migration strategy and bioclimatic zones 4.3. Climatic niche Migratory status was of equal importance to breeding habitat in explaining changes in population. Afro-tropical migrants showed steeper declines than species wintering in Europe or the UK between 1967 and 2006, and fluctuated similarly across the time series. This finding agrees with many other studies across Europe (Berthold et al., 1998; Berthold, 2001; Flade and Schwarz, 2004; Sanderson et al., 2006; Gregory et al., 2007). Within the UK, population declines have been recorded in migrants, including key studies on whitethroat Sylvia communis, sand martin Riparia riparia and house martin Delichon urbica (Winstanley et al., 1974; Baillie et al., 2010). However, ascribing causes to migrant population changes is often difficult, given that they may vary in relation to processes operating on their breeding grounds, wintering grounds, and migration routes (Newton, 2004a). A key driver may be climate change, and the influence on the timing of arrivals of migrants and their breeding phenology (Both et al., 2006; Moller et al., 2008). Species failing to adjust breeding and migration strategies may face trophic mis-matches, rendering them at a competitive disadvantage compared to resident species (Moller et al., 2008). The use of stop-over sites on migration routes may also have bearing on survival and population trends (Schaub et al., 2005). However, declines in some species of migrants may be linked to Species with more northerly distributions within Europe exhibited larger population declines between 1967 and 2006 in England than those with a more southerly European distributions. This result agrees with findings in other studies (Jiguet et al., 2007; Moller et al., 2008), and probably reflects broader patterns of climate change impacting on biological diversity in northern latitudes (Parmesan and Yohe, 2003). Likewise, in accordance with Jiguet et al. (2007), we observed that species with a lower thermal maximum (temperature at the hot edge of the climate envelope) showed larger population declines that species with a higher tolerance of temperatures. These species may be considered most sensitive to climate warming, with population declines in turn driven by associated changes to environments and communities (Jiguet et al., 2007; Moller et al., 2008). 4.4. Additional factors Relationships between annual fecundity (or correlated life history traits) and population change (or proxies for extinction risk) have previously been recorded in other studies (Owens and Bennett, 2000; Cardillo et al., 2005; Amano and Yamaura, C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 2007; Jiguet et al., 2007). However, we found no significant relationship between our measure of productivity and population change. Changes in populations may also occur in relation to range contractions or population sizes, regulated by density dependence (Sæther and Engen, 2002); in this study, species with larger populations have shown more favourable population changes between 1967–2006, 1977–1986, and 1997–2006. We also recorded significant negative and positive relationships for body mass during consecutive periods of 1967–1976 and 1977–1986, respectively. The explanation behind these results is unclear, but similar to Moller et al. (2008), may have been driven by a small number of larger species that showed considerable population changes during these periods. Species with larger relative brain size showed more favourable population changes than species with smaller relative brain sizes during 1997–2006. One reason for this slight discrepancy could be due to African migratory species having smaller brains on average than resident species (Sanderson et al., 2006). The results, however, agree with a separate study (Shultz et al., 2005), suggesting species with larger relative brain mass may be more 140 adaptable to changes in resource availability than species with smaller relative brain mass. A previous study for European breeding birds also found that species with longer flight distances, and thus greater risks they may take when approached by a predator, showed steeper population declines (Moller, 2008). However, we found no such pattern in this study, possibly due to a reduced number of species (N = 47) where this information was available, or behavioural differences that may exist between European and UK populations. 4.5. Conservation importance This study has shown that breeding bird populations in England are related not only to processes operating on breeding grounds, but also whether species travel to African wintering destinations, and in turn the over-wintering zones that migrants may utilise. Within the UK, BTO and JNCC operate an alerts system to highlight rapid (>50%) and moderate (>25%, <50%) declines that may be of conservation concern, as well as population recoveries where the status of a species has improved (Baillie et al., 2010). Currently, Cuckoo 350 Index (1966 = 100) Index (1966 = 100) 120 100 80 60 300 250 200 150 50 1966 1972 1978 1984 1990 1996 2002 2008 20 1966 1972 1978 1984 1990 1996 2002 2008 Garden Warbler 400 Green Woodpecker 350 120 Index (1966 = 100) Index (1966 = 100) Nuthatch 100 40 140 2013 100 80 60 300 250 200 150 100 50 1966 1972 1978 1984 1990 1996 2002 2008 40 1966 1972 1978 1984 1990 1996 2002 2008 Spotted Flycatcher Index (1966 = 100) 120 100 80 60 40 160 Index (1966 = 100) 140 Blue Tit 140 120 100 20 0 1966 1972 1978 1984 1990 1996 2002 2008 80 1966 1972 1978 1984 1990 1996 2002 2008 Fig. A1. Smoothed trend indices for England showing changes in abundance between 1966 and 2006 for: left-hand side, two declining humid species (cuckoo and spotted flycatcher) and an arid species (garden warbler) showing an initial decrease prior to 1974; right-hand side, increasing trends for three resident species; dashed lines show the 95% confidence intervals. 2014 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 Falco.tinnunculus Columba.palumbus Columba.oenas Streptopelia.turtur Strix.aluco Buteo.buteo Cuculus.canorus Vanellus.vanellus Numenius.arquata Picus.viridis Dendrocopos.major Regulus.regulus Sturnus.vulgaris Turdus.philomelos Turdus.merula Turdus.viscivorus Muscicapa.striata Erithacus.rubecula Phoenicurus.phoenicurus Certhia.familiaris Troglodytes.troglodytes Sitta.europaea Alauda.arvensis Sylvia.communis Sylvia.curruca Sylvia.borin Sylvia.atricapilla Aegithalos.caudatus Hirundo.rustica Delichon.urbicum Acrocephalus.schoenobaenus Acrocephalus.scirpaceus Phylloscopus.collybita Phylloscopus.trochilus Garrulus.glandarius Pica.pica Corvus.corone Corvus.monedula Poecile.palustris Poecile.montanus Parus.major Cyanistes.caeruleus Periparus.ater Prunella.modularis Anthus.pratensis Anthus.trivialis Motacilla.alba Motacilla.flava Fringilla.coelebs Pyrrhula.pyrrhula Carduelis.carduelis Carduelis.chloris Carduelis.flammea Carduelis.cannabina Emberiza.schoeniclus Emberiza.citrinella Emberiza.calandra Passer.montanus Perdix.perdix Fig. A2. Phylogenetic tree of all species used in the study of population changes for breeding birds in England. between 1967 and 2007, 61% of farmland species and 31% of woodland species have declined more than 25%, and evidence here suggests that this trend has continued within the last 25 years (56% and 24% of farmland and woodland species, respectively). Likewise, 53% of those species migrating to Africa have declined more than 25% between 1967 and 2006. These declines have been more pronounced for migrants using humid zones (63% and 43% humid and arid species, respectively), and within the last 25 years, most humid zone species have continued to decline, shown for spotted flycatcher Muscicapa striata, turtle dove Streptopelia turtur, tree pipit Anthus trivialis, cuckoo Cuculus canorus, and willow warbler Phylloscopus trochilus (Table 3). Most European countries are required to protect migratory species under the Convention on the Conservation of Migratory Species of Wild Animals (CMS or Bonn Convention), including protection from human activities such as hunting persecution, as well as conserving their wintering, migratory, and breeding habitats. To fully protect migrants, a knowledge is required of geographically separated processes occurring at different periods of the year (Webster et al., 2002). Success of conservation strategies for migratory animals will depend upon knowledge of migratory connectivity, and a correct identification of the conservation problem; the failure to do so could lead to regional extinctions (Martin et al., 2007). Segregating migrants by broad wintering zones may therefore represent an important first step in assessing where conservation priorities are needed, for instance directing conservation focus to processes occurring in the humid African bioclimatic zone. More work is therefore needed to relate specific environmental conditions occurring in these areas to population changes, including use of Normalized Difference Vegetation Index (NDVI) to assess habitat suitability, and understanding connectivity for breeding populations to wintering zones through telemetry. Pending more precise information of species’ wintering areas, the production of an indicator specific to wintering zones for Afro-Palaearctic migrant species could be a useful tool for assessing conservation status and management. Acknowledgements We would like to thank the many individual professional and volunteer fieldworkers that collected and collated the data under the Common Bird Census and the Breeding Bird Survey. We also thank Chris Hewson, Phil Atkinson, Nancy Ockendon, Alison Johnston, and Richard Duncan for useful comments and statistical advice. The CBC and BBS were funded by the Joint Nature Conservation Committee (on behalf of the Countryside Council for Wales, Natural England, the Council for Nature Conservation and the Countryside and Scottish Natural Heritage) and by the British Trust for Ornithology. The BBS was also funded by the Royal Society for the Protection of Birds. Appendix A See Figs. A1 and A2. See Tables A1–A3. Species Latitudinal midpoint Thermal maximum Winter in Africa Migrationa Bio- climatic zone Breeding habitat Nesting habitat Breeding population size Productivity Flight distance Body mass Brain mass Blackbird Turdus merula Blackcap Sylvia atricapilla Blue Tit Cyanistes caeruleus Bullfinch Pyrrhula pyrrhula Buzzard Buteo buteo Carrion Crow Corvus corone Chaffinch Fringilla coelebs Coal Tit Periparus ater Corn Bunting Emberiza calandra Curlew Numenius arquata Dunnock Prunella modularis Goldcrest Regulus regulus Goldfinch Carduelis carduelis Great Spotted Woodpecker Dendrocopos major Great Tit Parus major Green Woodpecker Picus viridis Greenfinch Carduelis chloris Grey Partridge Perdix perdix Jackdaw Corvus monedula Jay Garrulus glandarius Kestrel Falco tinnunculus Lapwing Vanellus vanellus Lesser Redpoll Carduelis flammea Linnet Sylvia curruca Long-tailed Tit Aegithalos caudatus Magpie Pica pica Marsh Tit Poecile palustris Meadow Pipit Anthus pratensis Mistle Thrush Turdus viscivorus Nuthatch Sitta europaea Pied Wagtail Motacilla alba 52.98 53.44 52.31 55.25 51.86 52.98 52.76 52.75 46.93 57.03 54.79 53.45 49.84 53.21 20.52 20.49 20.47 18.87 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 2 1 1 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 3 3 1 1 2 3 1 1 2 1 1 1 3 1 1 1 1 3 2 2 1 1 1 3 8,800,000 1,160,000 6,600,000 380,000 29,000 1,940,000 10,800,000 1,220,000 39,000 71,000 4,000,000 1,120,000 440,000 55,000 10.0 7.5 16.5 6.8 3.0 4.0 6.8 16.0 6.4 4.0 10.0 13.6 10.0 5.3 7.8 6.0 6.1 5.9 51.1 29.3 8.9 5.1 12.6 108.2 18.5 10.7 25.8 1018.0 517.0 20.7 9.5 43.9 1001.0 21.7 5.6 15.5 89.6 1.92 0.67 0.65 0.89 7.90 8.14 0.77 0.51 1.17 3.68 0.71 0.38 0.59 2.51 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 1 1 1 2 2 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 2 2 1 2 2 1 2 1 3 1 3 3 1 3 3 3 1 2 3 1 1 2 1 1 1 1 3 2 1 3 1 3,200,000 30,000 1,060,000 290,000 780,000 320,000 100,000 430,000 320,000 1,040,000 420,000 1,180,000 120,000 3,800,000 460,000 260,000 600,000 11.9 4.9 12.5 15.0 4.5 4.5 4.5 4.0 6.7 12.5 7.1 6.0 11.7 9.0 8.0 7.0 8.3 19.2 198.0 28.3 390.0 231.0 158.5 252.0 189.0 11.2 17.3 7.7 206.5 10.5 17.7 139.1 23.4 23.6 0.85 4.35 0.89 1.89 4.69 4.15 3.68 2.16 0.59 0.67 0.41 5.34 0.58 0.68 2.21 1.11 0.58 52.98 51.64 52.54 52.54 52.08 51.42 52.54 53.65 55.49 50.52 52.99 53.65 51.42 57.04 52.99 51.19 52.98 20.46 20.57 20.08 20.50 19.05 18.86 20.59 20.08 20.57 20.11 20.51 19.51 20.40 20.49 20.54 20.27 20.44 19.33 16.97 20.09 19.97 20.24 5.5 4.0 7.7 11.7 5.6 17.1 7.1 23.4 10.8 18.0 36.5 13.9 4.2 15.6 7.1 13.3 20.8 7.6 11.9 2015 (continued on next page) C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 Table A1 List of species and ecological variables included in the studya. Latitudinal midpoint Reed Bunting Emberiza schoeniclus Robin Erithacus rubecula Skylark Alauda arvensis Song Thrush Turdus philomelos Starling Sturnus vulgaris Stock Dove Columba oenas Tawny Owl Strix aluco Tree Sparrow Passer montanus Treecreeper Certhia familiaris Willow Tit Poecile montanus Woodpigeon Columba palumbus Wren Troglodytes troglodytes Yellowhammer Emberiza citrinella Chiffchaff Phylloscopus collybita Lesser Whitethroat Sylvia curruca Redstart Phoenicurus phoenicurus Reed Warbler Acrocephalus scirpaceus Sedge Warbler Acrocephalus schoenobaenus Whitethroat Sylvia communis Yellow Wagtail Motacilla flava Cuckoo Cuculus canorus Garden Warbler Sylvia borin House Martin Delichon urbicum Spotted Flycatcher Muscicapa striata Swallow Hirundo rustica Tree Pipit Anthus trivialis Turtle Dove Streptopelia turtur Willow Warbler Phylloscopus trochilus 53.89 53.21 52.98 54.79 53.89 51.64 50.75 50.52 54.12 55.25 52.54 52.31 54.11 53.44 54.34 53.65 50.01 Thermal maximum 20.42 20.08 19.69 19.96 19.24 20.20 20.10 17.84 20.26 20.40 19.35 19.87 19.71 19.70 54.10 51.42 53.65 53.65 53.89 52.98 52.76 52.98 53.66 51.42 55.92 20.35 20.46 19.39 20.55 20.52 19.55 20.53 17.70 Winter in Africa Migrationa Bio- climatic zone Breeding habitat Nesting habitat Breeding population size Productivity Flight distance 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 1 1 1 2 1 2 1 1 1 1 1 1 1 3 3 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 2 1 2 1 2 2 1 2 1 1 2 1 2 1 1 1 3 2 1 2 1 3 3 3 3 3 3 1 1 2 1 1 3 1 440,000 8,400,000 4,000,000 1,980,000 2,200,000 480,000 40,000 220,000 400,000 50,000 4,700,000 14,200,000 2,400,000 1,280,000 160,000 180,000 120,000 11.3 10.0 8.7 10.0 6.8 5.0 2.7 12.5 10.5 7.1 6.0 5.7 8.8 8.2 4.7 12.5 3.9 12.8 5.4 13.9 11.4 14.7 2 3 1 3 1 500,000 5.0 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 1 1 2 2 2 2 2 2 2 2 2 2 3 1 3 1 3 1 2 1 1 2 1 1 3 3 3 2 1 1 1,320,000 100,000 39,000 400,000 750,000 240,000 1,140,000 240,000 150,000 4,600,000 9.3 7.9 10.0 4.3 11.3 4.3 11.3 7.3 3.9 8.9 4.9 4.6 4.9 11.0 5.8 12.5 6.7 9.0 8.0 9.7 21.0 6.2 8.5 10.2 13.3 8.5 Body mass Brain mass 19.2 19.9 35.8 84.8 79.9 299.0 530.0 20.8 9.0 10.0 480.0 9.2 27.4 7.8 10.7 13.4 10.8 0.68 0.66 0.97 1.59 1.70 2.27 9.36 0.79 0.55 0.79 2.38 0.50 0.82 0.38 0.53 0.54 0.58 11.5 0.45 14.7 18.3 98.0 18.4 17.6 14.8 19.2 21.3 152.0 9.2 0.56 0.47 2.24 0.62 0.59 0.53 0.58 0.68 1.39 0.31 a Latitudinal midpoint of EBCC distribution of species breeding range (Lemoine et al., 2007), thermal maximum (Jiguet et al., 2007), winter in Africa (1 = no, 2 = yes), migration destination (1 = UK, 2 = Europe, 3 = Africa, Wernham et al., 2002), bioclimatic zone (1 = arid, 2 = humid, Hewson and Noble, 2009, 0 = European species not tested within this variable), breeding habitat (1 = woodland, 2 = farmland, 3 = other), Nesting habitat (1 = above-ground, 2 = ground, 3 = cavity/hole), breeding population size (Wernham et al., 2002), productivity (Wernham et al., 2002), flight distance (Moller, 2008), body mass (Wernham et al., 2002), and brain mass (Garamszegi et al., 2002; Moller et al., 2008). C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 Species 2016 Table A1 (continued) 2017 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 Table A2 Changes in abundance, expressed as a proportion of 1.0 in the first year of the time period, for periods: 1967–2006, 1967–1976, 1977–1986, 1987–1996 and 1997–2006 (95% confidence intervals are in parentheses). Changes with an asterisk are significant (95% confidence intervals do not overlap 1). Proportional changes less than 1 imply a decrease and values greater than 1 imply an increase i.e. 0.86 is a 24% decline between the two time periods, whereas 1.55 is a 55% increase. Species Tree Sparrow Lesser Redpoll Grey Partridge Spotted Flycatcher Turtle Dove Corn Bunting Starling Tree Pipit Willow Tit Linnet Yellow Wagtail Marsh Tit Whitethroat Cuckoo Skylark Willow Warbler Yellowhammer House Martin Bullfinch Song Thrush Mistle Thrush Meadow Pipit Sedge Warbler Dunnock Curlew Reed Bunting Garden Warbler Blackbird Redstart Lesser Whitethroat Lapwing Jay Tawny Owl Treecreeper Kestrel Goldfinch Swallow Chiffchaff Chaffinch Greenfinch Blue Tit Goldcrest Robin Coal Tit Long-tailed Tit Jackdaw Reed Warbler Pied Wagtail Wren Great Tit Magpie Carrion Crow Blackcap Stock Dove Woodpigeon Nuthatch Green Woodpecker Great Spotted Woodpecker Buzzard Proportional changes in abundance (95% confidence interval) 1967–2006 1967–1976 1977–1986 1987–1996 1997–2006 0.03(0.01–0.06)* 0.10(0.04–0.22)* 0.12(0.09–0.18)* 0.13(0.08–0.18)* 0.15(0.09–0.24)* 0.16(0.07–0.26)* 0.17(0.12–0.23)* 0.17(0.08–0.29)* 0.17(0.08–0.30)* 0.25(0.19–0.34)* 0.28(0.15–0.62)* 0.32(0.22–0.45)* 0.37(0.27–0.50)* 0.39(0.29–0.52)* 0.41(0.34–0.49)* 0.42(0.30–0.54)* 0.43(0.34–0.54)* 0.44(0.14–1.42) 0.48(0.38–0.61)* 0.49(0.40–0.58)* 0.51(0.43–0.61)* 0.54(0.26–0.76)* 0.61(0.31–0.87)* 0.63(0.54–0.74)* 0.71(0.32–1.25) 0.78(0.59–0.99)* 0.79(0.54–1.13) 0.82(0.75–0.90)* 0.82(0.58–1.37) 0.86(0.60 –1.30) 0.89(0.41–1.29) 0.94(0.74–1.20) 0.99(0.59–1.48) 1.04(0.78–1.44) 1.06(0.77–1.53) 1.18(0.89–1.53) 1.23(0.88–1.75) 1.31(1.04–1.72)* 1.38(1.22–1.56)* 1.38(1.06–1.67)* 1.40(1.25–1.57)* 1.42(0.80 –2.97) 1.49(1.32–1.65)* 1.50(0.83–2.88) 1.77(1.28–2.68)* 1.79(1.15–2.84)* 1.80(1.22–3.02)* 1.86(1.32–2.63)* 1.90(1.65–2.18)* 2.04(1.76–2.30)* 2.05(1.61–2.56)* 2.19(1.77–2.79)* 2.39(1.97–3.05)* 2.63(1.79–3.93)* 2.68(1.36–6.81)* 2.82(1.97–4.10)* 3.05(2.33–4.27)* 4.32(3.11–6.56)* 5.83(3.68–14.60)* 0.87(0.69–1.06) 3.36(1.89–5.57)* 1.05(0.91–1.28) 0.80(0.64–1.00)* 1.04(0.84–1.22) 1.35(1.06–1.70)* 0.79(0.69–0.93)* 1.07(0.74–1.59) 1.32(0.99–1.83) 0.74(0.63–0.85)* 0.92(0.62–1.47) 0.60(0.46–0.72)* 0.25(0.20–0.30)* 0.98(0.80 –1.19) 1.05(0.94–1.17) 0.90(0.79–1.03) 1.04(0.90–1.19) 1.07(0.49–1.68) 1.10(0.98–1.25) 0.82(0.76–0.90)* 1.05(0.92–1.21) 1.18(0.76–1.63) 0.74(0.41–1.05) 0.95(0.9 –1.03) 1.29(1.00–2.08) 1.43(1.21–1.75)* 0.62(0.46–0.82)* 0.95(0.90–1.01) 0.36(0.27–0.66)* 1.10(0.82–1.49) 1.54(0.91–2.25) 1.03(0.89–1.22) 1.17(0.86–1.61) 1.38(1.09–1.80)* 1.52(1.13–1.91)* 1.37(1.14–1.70)* 0.98(0.77––1.35) 0.52(0.45–0.62)* 1.00(0.93––1.09) 1.08(0.93–1.22) 1.20(1.13–1.28)* 2.44(1.69–4.38)* 1.04(0.98–1.11) 1.68(1.15–2.48)* 1.47(1.25–1.93)* 0.97(0.77–1.31) 0.96(0.70–1.45) 2.21(1.80–2.85)* 1.76(1.63–1.92)* 1.20(1.09–1.32)* 1.28(1.09–1.52)* 1.31(1.14–1.46)* 0.95(0.80–1.13) 1.88(1.45–2.54)* 0.96(0.52–2.30) 1.11(0.90–1.44) 1.60(1.24–2.09)* 1.90(1.36–2.81)* 1.07(0.73–1.88) 0.14(0.10–0.19)* 0.44(0.30–0.59)* 0.36(0.29–0.44)* 0.69(0.55–0.86)* 0.59(0.44–0.76)* 0.32(0.20–0.45)* 0.70(0.59–0.81)* 1.00(0.73–1.39) 0.73(0.52–0.96)* 0.45(0.38–0.54)* 0.81(0.54–1.25) 0.81(0.67–0.99)* 0.72(0.61–0.87)* 0.95(0.82–1.08) 0.54(0.46–0.59)* 1.13(0.99–1.24) 0.91(0.82–1.00) 0.73(0.49–1.17) 0.64(0.56–0.74)* 0.61(0.54–0.67)* 0.74(0.67–0.83)* 0.62(0.44–0.76)** 0.66(0.49––0.83)* 0.63(0.57–0.70)* 0.68(0.38–1.07) 0.51(0.37–0.62)* 1.57(1.31–1.95)* 0.85(0.79–0.90)* 1.87(1.11–2.64)* 1.07(0.90–1.29) 0.80(0.57–0.96)* 1.09(0.98–1.21) 1.00(0.82–1.18) 0.89(0.78–1.06) 0.63(0.53–0.73)* 0.42(0.36–0.48)* 0.80(0.66–0.92)* 1.06(0.93–1.24) 1.16(1.10–1.22)* 0.85(0.75–0.96)* 1.07(1.01–1.15)* 0.52(0.45–0.66)* 0.89(0.84–0.95)* 0.78(0.67–0.95)* 0.84(0.70–0.96)* 1.42(1.18–1.76)* 1.21(0.92–1.46) 0.66(0.56–0.78)* 0.83(0.78–0.90)* 1.20(1.12–1.29)* 1.54(1.42–1.69)* 1.15(1.02–1.31)* 1.39(1.24–1.54)* 1.24(1.02–1.48)* 1.50(1.17–1.92)* 1.34(1.11–1.62)* 0.90(0.81–1.02) 0.99(0.89–1.13) 0.93(0.70–1.31) 0.25(0.12–0.39)* 0.13(0.05–0.19)* 0.52(0.42–0.63)* 0.35(0.27–0.46)* 0.63(0.45–0.77)* 0.58(0.32–0.93)* 0.51(0.42–0.59)* 0.25(0.13–0.38)* 0.49(0.31–0.69)* 1.18(0.97–1.45) 0.65(0.42–0.90)* 0.85(0.72–1.00) 1.60(1.37–1.82)* 0.79(0.70–0.88)* 0.86(0.77–0.99)* 0.62(0.52–0.71)* 0.56(0.50–0.62)* 0.59(0.24–1.43) 0.85(0.74–0.96)* 0.89(0.78–1.00) 0.84(0.76–0.94)* 0.80(0.62–1.02) 1.15(0.93–1.47) 0.93(0.84–1.03) 1.05(0.68–1.36) 0.90(0.77–1.07) 0.93(0.80–1.07) 0.90(0.86–0.94)* 1.17(1.00–1.43) 0.68(0.59–0.82)* 0.71(0.55–0.96)* 0.82(0.74–0.91)* 0.95(0.79–1.13) 1.02(0.91–1.15) 1.09(0.92––1.28) 1.69(1.39–1.94)* 1.08(0.91–1.26) 1.55(1.36–1.70)* 0.99(0.94–1.04) 1.18(0.97–1.34) 1.03(0.99––1.08) 1.13(0.82–1.34) 1.36(1.29–1.43)* 1.05(0.90–1.22) 1.57(1.39–1.75)* 1.04(0.85–1.23) 1.17(1.00–1.53) 1.21(0.99–1.55) 1.11(1.03–1.16)* 1.04(0.99–1.09) 1.00(0.93–1.09) 1.21(1.13–1.32)* 1.24(1.18–1.32)* 1.10(0.96–1.33) 1.21(1.07–1.35)* 1.18(1.03–1.36)* 1.44(1.24–1.67)* 1.16(1.02–1.33)* 3.17(2.20–5.80)* 1.22(1.05–1.55)* 0.70(0.50–1.16) 0.73(0.63–0.81)* 0.70(0.59–0.85)* 0.45(0.40–0.52)* 0.85(0.69–1.00) 0.67(0.63–0.72)* 0.77(0.59–1.02) 0.42(0.32–0.52)* 0.77(0.73–0.84)* 0.61(0.52–0.72)* 0.88(0.74–1.03) 1.11(1.06–1.16)* 0.59(0.56–0.63)* 0.91(0.87–0.95)* 0.71(0.65–0.76)* 0.88(0.85–0.93)* 1.08(1.00–1.17) 0.96(0.87–1.03) 1.25(1.20–1.31)* 0.83(0.79–0.88)* 1.00(0.89–1.12) 0.89(0.78–1.00) 1.21(1.17–1.26)* 0.83(0.77–0.90)* 1.37(1.24–1.51)* 0.78(0.70–0.87)* 1.17(1.15–1.20)* 0.86(0.76–0.99)* 1.19(1.03–1.28)* 1.12(1.02–1.22)* 1.07(0.99–1.16) 0.90(0.75–1.12) 0.90(0.79–1.01) 1.07(1.00–1.15) 1.26(1.19–1.31)* 1.23(1.16–1.31)* 1.21(1.17–1.29)* 1.15(1.12–1.20)* 1.25(1.21–1.31)* 1.05(1.02–1.07)* 1.18(1.06–1.32)* 1.20(1.17–1.23)* 1.09(0.94–1.30) 1.05(0.97–1.12) 1.23(1.15–1.30)* 1.16(1.02–1.34)* 1.05(0.99–1.10) 1.24(1.19–1.25)* 1.36(1.32–1.40)* 0.96(0.93–0.99)* 1.12(1.06–1.18)* 1.33(1.26–1.38)* 0.95(0.84–1.09) 1.29(1.25–1.33)* 1.38(1.26–1.50)* 1.35(1.27–1.42)* 1.81(1.71–1.91)* 1.64(1.51–1.83)* 2018 C.B. Thaxter et al. / Biological Conservation 143 (2010) 2006–2019 Table A3 Univariate phylogenetic least squares analyses for periods of 1967–2006, 1967–1976, 1977–1986, 1987–1996, and 1997–2006; (a) assessment of main effects, (b) b estimates and model contrasts; df = degrees of freedom, Est = parameter estimate; SE = standard error of the estimate; variables were tested for all species, except bioclimatic zone, which was tested separately for African migrants. 1967–2006 (a) Breeding habitat Nesting habitat Migration Winters in Africa Latitudinal midpoint Thermal Maximum Residual brain mass Productivity Flight distance Breeding population size Body Mass Bioclimatic zone (b) Breeding habitat Nesting habitat Migration Winters in Africa Latitudinal midpoint Thermal Maximum Residual brain mass Productivity Flight distance Breeding population size Body mass Bioclimatic zone Wood Other Ground Cavity Europe UK Humid 1967–1976 1977–1986 1987–1996 1997–2006 df F P df F P df F P df F P df F P 2,56 2,56 2,56 1,57 1,57 1,46 1,57 1,57 1,47 1,57 1,57 1,14 4.64 4.77 4.97 6.73 2.39 3.09 4.86 8.90 8.08 1.83 14.37 4.95 0.014 0.012 0.010 0.012 0.128 0.085 0.032 0.004 0.005 0.182 <0.001 0.048 2,56 2,56 2,56 1,57 1,57 1,46 1,57 1,57 1,47 1,57 1,57 1,14 0.40 0.20 6.73 16.99 2.05 0.18 2.48 0.19 0.44 0.01 1.93 2.58 0.671 0.820 0.002 <0.001 0.157 0.673 0.121 0.665 0.513 0.907 0.170 0.137 2,56 2,56 2,56 1,57 1,57 1,46 1,57 1,57 1,47 1,57 1,57 1,14 4.25 2.65 1.64 2.94 1.16 0.06 1.38 4.24 0.30 0.79 0.58 1.34 0.019 0.079 0.203 0.092 0.286 0.803 0.245 0.044 0.584 0.379 0.450 0.272 2,56 2,56 2,56 1,57 1,57 1,46 1,57 1,57 1,47 1,57 1,57 1,14 1.49 4.41 2.04 2.53 2.42 3.61 2.71 0.21 2.79 0.59 2.45 8.35 0.235 0.017 0.140 0.117 0.125 0.064 0.105 0.647 0.101 0.446 0.123 0.015 2,56 2,56 2,56 1,57 1,57 1,46 1,57 1,57 1,47 1,57 1,57 1,14 0.29 1.52 5.81 8.83 2.54 6.18 7.43 0.14 1.49 4.32 0.44 2.56 0.749 0.228 0.005 0.004 0.116 0.017 0.008 0.708 0.228 0.042 0.510 0.138 b SE P b SE P b SE P b SE P b SE P 0.12 0.15 0.15 0.12 0.16 0.13 0.12 0.03 0.08 0.06 0.02 0.01 0.08 0.09 0.19 0.005 0.085 0.051 0.637 0.078 0.238 0.16 0.19 0.18 0.15 0.19 0.17 0.16 0.04 0.07 0.08 0.02 0.01 0.10 0.11 0.22 0.819 0.118 0.009 0.062 0.135 0.054 0.09 0.10 0.08 0.07 0.10 0.09 0.09 0.02 0.05 0.04 0.01 0.00 0.06 0.06 0.12 0.482 0.557 0.126 0.596 0.023 0.001 0.47 1.10 1.27 0.28 0.54 1.06 0.86 0.14 0.33 0.32 0.11 0.04 0.26 0.68 0.84 0.33 0.36 0.41 0.31 0.42 0.35 0.33 0.09 0.19 0.14 0.04 0.01 0.19 0.18 0.38 0.162 0.004 0.003 0.363 0.200 0.003 0.07 0.12 0.08 0.07 0.50 0.38 0.47 0.04 0.03 0.10 0.01 0.00 0.01 0.16 0.33 0.16 0.13 0.16 0.13 0.14 0.13 0.11 0.03 0.07 0.06 0.02 0.01 0.08 0.11 0.21 References Amano, T., Yamaura, Y., 2007. 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