Combined effects of heat waves and droughts on avian ...silvis.forest.wisc.edu/wp-content/uploads/pubs/SILVIS/Albright_et_al... · ate North America, changes in the interannual variability

Combined effects of heat waves and droughtson avian communities across the conterminous United States

THOMAS P. ALBRIGHT,1,5,� ANNA M. PIDGEON,1 CHADWICK D. RITTENHOUSE,1 MURRAY K. CLAYTON,2 BRIAN D.

WARDLOW,3 CURTIS H. FLATHER,4 PATRICK D. CULBERT,1 AND VOLKER C. RADELOFF1

1Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, Wisconsin 53706 USA2Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706 USA

3National Drought Mitigation Center, University of Nebraska, Lincoln, Nebraska 68583 USA4Rocky Mountain Research Station, United States Department of Agriculture, Forest Service, Fort Collins, Colorado 80526 USA

Abstract. Increasing surface temperatures and climatic variability associated with global climate change

are expected to produce more frequent and intense heat waves and droughts in many parts of the world.

Our goal was to elucidate the fundamental, but poorly understood, effects of these extreme weather events

on avian communities across the conterminous United States. Specifically, we explored: (1) the effects of

timing and duration of heat and drought events, (2) the effects of jointly occurring drought and heat waves

relative to these events occurring in isolation, and (3) how effects vary among functional groups related to

nest location and migratory habit, and among ecoregions with differing precipitation and temperature

regimes. Using data from remote sensing, meteorological stations, and the North American Breeding Bird

Survey, we used mixed effects models to quantify responses of overall and functional group abundance to

heat waves and droughts (occurring alone or in concert) at two key periods in the annual cycle of birds:

breeding and post-fledging. We also compared responses among species with different migratory and

nesting characteristics, and among 17 ecoregions of the conterminous United States. We found large

changes in avian abundances related to 100-year extreme weather events occurring in both breeding and

post-fledging periods, but little support for an interaction among time periods. We also found that jointly-,

rather than individually-occurring heat waves and droughts were both more common and more predictive

of abundance changes. Declining abundance was the only significant response to post-fledging events,

while responses to breeding period events were larger but could be positive or negative. Negative

responses were especially frequent in the western U.S., and among ground-nesting birds and Neotropical

migrants, with the largest single-season declines (36%) occurring among ground-nesting birds in the desert

Southwest. These results indicate the importance of functional traits, timing, and geography in determining

avian responses to weather extremes. Because dispersal to other regions appears to be an important avian

response, it may be essential to maintain habitat refugia in a more climatically variable future.

Key words: birds (Aves); climate change; drought; extreme weather; heat wave; land surface temperature; mixed effects

models; MODIS; North American Breeding Bird Survey; standardized precipitation index; United States.

Received 26 August 2010; revised 15 October 2010; accepted 26 October 2010; published 23 November 2010.

Corresponding Editor: B. Wolf.

Citation:Albright, T. P., A. M. Pidgeon, C. D. Rittenhouse, M. K. Clayton, B. D. Wardlow, C. H. Flather, P. D. Culbert, and

V. C. Radeloff. 2010. Combined effects of heat waves and droughts on avian communities across the conterminous

United States. Ecosphere 1(5):artX. doi:10.1890/ES10-00057.1

Copyright: � 2010 Albright et al. This is an open-access article distributed under the terms of the Creative Commons

Attribution License, which permits restricted use, distribution, and reproduction in any medium, provided the original

author and sources are credited.5 Present address: Laboratory for Conservation Biogeography, Department of Geography, University of Nevada-Reno,

104A Mackay Science Hall MS0154, Reno, Nevada 89557-0154 USA.� E-mail: [email protected]

v www.esajournals.org 1 November 2010 v Volume 1(5) v Article 12

INTRODUCTION

Episodes of extreme weather can alter bioticcommunities by affecting survival, reproduction,habitat selection, and resources on which organ-isms depend. Under a changing climate, extremeweather events such as heat waves and droughtsare likely to become more frequent and intense inmany locations (IPCC 2007). In much of temper-ate North America, changes in the interannualvariability in temperature and precipitation arepredicted to be the most drastic aspects ofclimate change in the 21st century (Diffenbaughet al. 2008). Extreme events, which exceedecological or physiological tolerances of somespecies, may have greater influence on popula-tion persistence than changes in mean conditions(Jentsch et al. 2007). As societies and ecosystemsare confronted with a changing climate, it iscritical to understand how events such as heatwaves and drought affect biodiversity (Archauxand Wolters 2006). However, such an under-standing is often limited to individual species,sites, and disturbance events, while a broaderperspective that considers communities, diverseregions, and interactions among events is lack-ing.

Drought has been associated with lowerhabitat quality (Mueller et al. 2005), highermortality (Mooij et al. 2002), and reducedreproductive effort (Christman 2002), and candecrease abundance and species richness of aviancommunities (Albright et al. 2010). Heat wavescan also stress avian communities by increasingwater requirements (Guthery et al. 2005), elicit-ing altered behavior on birds (Guthery et al.2001), and reducing reproduction and survival(Becker et al. 1997, Christman 2002), resulting inaltered community structure and lower speciesrichness (Albright et al., in press). There is someevidence that the effects of both heat waves anddrought vary among birds according to theirmigratory strategy (Albright et al. 2010), bodysize (McKechnie and Wolf 2010) and otherfunctional traits (Jiguet et al. 2006), and amongregions with differing climate regimes (Albrightet al., in press).

The timing of disturbances influences theireffects on vegetation and ecological communities(Pickett and White 1985). For example, theimpacts of drought on primary productivity can

depend on whether drought occurs before,during, or after the main period of vegetationgrowth (Heitschmidt et al. 1999). The timing ofevents may also be important to birds, becausethey have different requirements at differenttimes in their annual cycles. Caloric needs maybe higher while caring for nestlings (Williams1988) and prior to and during migration (Jenni-Eiermann and Jenni 1996), which may affect thesensitivity of birds to extreme weather events.The periods of the year during which bird speciesare most sensitive to heat waves may alsodepend on the functional characteristics of thespecies (Albright et al., in press).

Heat waves often, but not always, accompanydroughts (de Boeck et al. 2010). In most non-polar terrestrial regions, summer temperatureanomalies are negatively correlated with precip-itation (Trenberth and Shea 2005). A key contrib-utor to this relationship is that low soil moistureassociated with drought results in an enhancedratio of sensible-to-latent heat (the Bowen ratio)leading to greater surface and air temperatures.In Europe, for instance, the extreme heat wave of2003 was associated with both sustained elevatedtemperatures and below-normal precipitation(Fischer et al. 2007). However, heat waves mayalso be accompanied by normal or even above-normal precipitation (Gershunov et al. 2009).Similarly, summer droughts may occur duringnormal or abnormally cool periods (Trenberthand Shea 2005). For most organisms, the co-occurrence of drought and heat waves may beespecially challenging as water requirements aregreatly increased when temperatures are elevat-ed. Thus, knowledge of the effects of temperatureand precipitation extremes, occurring both sep-arately and in concert, is important for under-standing biotic responses to contemporary andfuture environmental variability.

Here, our goal was to elucidate the fundamen-tal, but poorly understood, effects of heat wavesand droughts on avian communities across theconterminous United States at key time periodsof the annual cycle of birds (bioperiods): earlybreeding and post fledging. First, we exploredthe temporal dimensions of these extreme weath-er events by asking whether avian assemblagesare more responsive during a particular biope-riod and whether the effects of extreme eventsoccurring in consecutive bioperiods are greater


ALBRIGHT ET AL.

than the sum of their effects individually. Wehypothesized that especially deleterious effectswould follow a sustained period of high temper-atures and moisture deficits. While drought andheat waves are often coincident, we also askedwhether the effects on avian assemblages varyaccording to whether these extreme weatherevents occur in concert or alone (e.g., a droughtnot accompanied by extremely high tempera-tures). Because of the increased demand forwater at high temperatures, we predicted thatperiods of coincident heat and drought would bethe most influential on avian assemblages.Throughout, we also sought to understand howavian responses vary according to key functionalattributes (migratory habit and nest placement)and among ecoregions with differing climaticand physiographic characteristics. We hypothe-sized that relationships would be most stronglynegative in hot and dry regions, which aresubject to greater extremes, and that residentand ground-nesting species would be moreaffected by the extremes than migratory birdsand canopy-nesting birds. Our hypothesis re-garding resident species was based on theirreliance on local resources and their duration ofexposure to local conditions. We expectedground-nesting species to be more affected thancanopy-nesting species because of the greatertemperature extremes experienced at the landsurface compared to the vegetation canopy.

METHODS

We obtained 2000–2008 data from the NorthAmerican Breeding Bird Survey (BBS; (USGS2008) for the conterminous United States, whichincluded 3,418 BBS routes, each 39.5-km inlength. Along each route, 50 3-minute pointcounts are conducted near dawn annually during

peak breeding season (most often during June) inwhich all birds seen or heard within 400 m arerecorded. We removed route-years collected byfirst-year observers and those having inclementweather at the time of the survey (Link and Sauer1997, Sauer et al. 2004). For each suitable route-year, we summed counts of individual birds for(1) North American landbirds (‘‘ALL’’) (Rich et al.2004); (2) three migratory guilds, namely perma-nent resident birds (‘‘RESIDENT’’), temperate orshort distance migrant birds (‘‘SHORTDIST’’),and Neotropical migrants (‘‘NEOTROP’’) (Rap-pole 1995); and (3) a guild composed of ground-nesting birds (‘‘ground’’) (Pidgeon et al. 2007);(Table 1, complete membership lists in AppendixA). We excluded rare species (,30 route-yearoccurrences over the history of BBS in theconterminous US) and marine or aquatic species,which are poorly sampled by BBS (Bystrak 1981).We assigned each BBS route to one of 17ecoregions based on a re-aggregation of Bailey’sprovinces and divisions (Bailey 1995). Thesemodifications were made to maximize physio-graphic homogeneity within ecoregions whilereducing variation in the number of BBS routesamong ecoregions (Fig. 1).

Bioperiods and meteorological indicatorsFor this work, we focused on two bioperiods

coinciding with key stages in the annual cycle ofmost temperate North American landbirds. Theearly breeding bioperiod corresponded to nestsite selection, nest construction, egg laying, andincubation. The post-fledging bioperiod capturedthe vulnerable stage of young-of-year birds afterthey have left nests and receive decreasing levelsof parental care (Adams et al. 2006). Anindividual’s experiences during both of thesebioperiods may determine its immediate survivalas well its success during migration and subse-

Table 1. Avian guilds used in the study.

Guild theme Guild Short name Species pool Description

Avifauna All landbirds ALL 369 North American landbirdsNest location Ground-nesting GROUND 105 Nest within 1 m of groundMigratory habit Permanent residents RESIDENT 104 Do not migrate away from breeding range

Short distance migrants SHORTDIST 97 Winter north of Tropic of CancerNeotropical migrants NEOTROP 166 Winter south of Tropic of Cancer

Notes: ‘‘Species pool’’ refers to the number of species in the guild observed and included in the routes in the study area overthe period 2000–2008. Guilds within themes are mutually exclusive but not exhaustive, as some birds not assigned a guild maynest across strata or have multiple or unknown migratory habits.


ALBRIGHT ET AL.

quent life stages (Merila and Svensson 1997). Theexact timing of nesting and fledging variesaccording to ecoregion, species, and environmen-tal conditions experienced during a given year.

Previous work has documented the predictiveutility of standardized precipitation indices (SPI)(Albright et al. 2010) and remotely-sensed day-time land surface temperature (LST) exceedances(Albright et al., in press) when modeling aviancommunities in temperate latitudes. The SPIscales precipitation in units of standard devia-tions from mean precipitation for each locationand time period (McKee et al. 1993). We obtainedSPI data from 2000–2008 from the High PlainsRegional Climate Center, which consisted of anetwork of 2427 stations with precipitationmeasurements from the Applied Climate Infor-mation System hhttp://rcc-acis.orgi (Hubbard etal. 2004). Based partially on findings from

Albright et al. (2010), we selected the 32-weekSPI interval ending in June (;18 Nov–30 June) asan indicator of relevant precipitation for the earlybreeding bioperiod. We included winter precip-itation in this time period, rather than a morenarrow spring-time window, because of theinfluence that winter precipitation can have onspring soil moisture (Entin et al. 2000). We alsoincluded an 8-week SPI ending in late August(;2 Jul–26 Aug) as an indicator of precipitationduring the post-fledging period. We then pro-duced 1-km gridded SPI maps by interpolatingSPI values from the weather stations usinginverse distance weighting.

To characterize temperatures experienced bybirds, we obtained 2000–2009 8-day compositeMOD11C2 daytime land surface temperaturedata (version 5.0) from the Moderate ResolutionImaging Spectroradiometer (MODIS) flown on

Fig. 1. Ecoregions modified from Bailey (1995) and centroids of BBS routes used in this study.


ALBRIGHT ET AL.

the National Aeronautics and Space Administra-tion’s Terra satellite. We used the full availablehistorical record of MODIS in order to charac-terize mean conditions as well as possible for thisdata source. We excluded data with poorcalibration, cloud contamination, or other qualityissues, based on MODIS quality assuranceinformation. We subtracted 2000–2009 meanvalues for each 8-day time period to obtaintemperature anomalies for each year and pro-jected the resulting images into Albers equal areaprojection with 5-km 3 5-km cells. We thencalculated for the two bioperiods the mean LSTexceedance, TE, which we defined as the averagepositive anomaly (all negative anomalies aretreated as 0). Our rationale for using exceedanceswas that a cumulative index of high tempera-tures ignoring temperature variations below themean would be a better proxy for heat waveconditions (Albright et al., in press). Land surfacetemperature exceedance for the early breedingbioperiod was based on three 8-day MOD11C2composite periods spanning 2–25 June. Repre-senting the post-fledging bioperiod, we alsocalculated mean LST exceedance over six 8-dayMOD11C2 composite periods spanning 20 Jul–5Sep. Because of the June timing of the routesurveys, we relate the early season bioperiod forboth LST and SPI indicators to BBS data from thesame year but relate indicators from the post-fledging, which occurs after June, to BBS dataduring the following year. Although we ac-knowledge that the temporal windows for someof the metrics may not coincide with thephenology of some species (particularly the Junetemperature metrics in more southern locationswhere the breeding cycle occurs earlier), wechose to keep bioperiods consistent to facilitateanalysis and comparison over a large area andacross a large number of species.

In order to link the LST and SPI datasets to BBSroutes, we calculated their spatial means within

20-km-radius buffers around BBS route cen-troids. In addition to encompassing the entirelength of the route, this distance is comparable toranges of natal dispersal distances reported in theliterature (Sutherland et al. 2000, Tittler et al.2009), indicating that the buffer captures abiologically relevant area.

AnalysisIn order to reduce data dimensionality and

multicollinearity within bioperiods of SPI andLST data, we centered and standardized the fourenvironmental variables and performed a princi-pal components transformation using theprcomp command in the R language andenvironment for statistical computing (R Devel-opment Core Team 2009). The resulting trans-formed dataset contained 89% of the originalvariance in the first three principal components(PCs, Table 2). Furthermore, the loadings fromthe transformation resulted in highly interpret-able principal components. We consider the firstcomponent, ‘‘PF_STRESS’’, to describe post-fledging stress because it is loaded heavily onpost-fledging TE and -SPI, while the second,‘‘EB_STRESS’’, describes early breeding stressbecause it loads most heavily on TE and -SPIfrom this bioperiod. For example, high scores forPF_STRESS indicate unusually hot and dryconditions during the post-fledging bioperiod.The third component, ‘‘DRYCOOL’’, acts as ahybrid, indicative of coincident depressed pre-cipitation and temperatures during both periods,but weighted more heavily on the early breedingseason. Thus, a location with high values inDRYCOOL experienced drought conditions ac-companied by relatively cool temperatures.

To quantify the relationship between thetemperature metrics and avian abundance, re-scaled as ln(abundance þ 1), we developed aseries of linear mixed effect models using thenlme package within R (Pinheiro et al. 2008). We

Table 2. Contributions and cumulative variance of the raw variables to principal component axes.

Raw variable PC1–PF_STRESS PC2–EB_STRESS PC3–DRYCOOL PC4

Post-fledging LST exceedance 0.707 –0.055 –0.267 0.652Early breeding LST exceedance –0.039 –0.705 –0.649 –0.284Post-fledging SPI –0.697 0.099 –0.339 0.624Winter/early breeding SPI 0.116 0.700 –0.627 –0.323Cumulative proportion of variance (%) 37.7 71.9 88.5 100


ALBRIGHT ET AL.

included a fixed effect for ecoregion to accountfor broad scale variation in abundance among the17 different ecoregions. We included an environ-mental metric 3 ecoregion interaction term, whichallowed fixed effects of the environmentalstressors to be estimated for each ecoregion. Wealso included a random effect for BBS route.Similarly, different BBS observers possess differ-ent skill levels in detecting birds, which mayresult in biased estimates of abundance andrichness (Sauer et al. 1994), prompting us totreat observers as random effects nested withinBBS routes. Finally, we added a continuous timeautoregressive component to account for tempo-ral autocorrelation (no residual spatial autocor-relation was encountered). The resulting generalmodel for predicting abundance, y, was:

y ¼ b0i þ b1iXjk þ bj þ bk þ eðtÞ

where the b0i and b1i were the intercept andslope vectors for the specified fixed effects atecoregion i, Xjk was a matrix of PC transformedvariables at route j observed by observer k, bj andbk were random effects for route j and observer k,and e(t) was a continuous time autoregressiveprocess of order 1.

To investigate the influence of different bio-periods and different types of extreme weather,we included ecoregion-specific fixed effects forPF_STRESS, EB_STRESS, and DRYCOOL (‘‘maineffects model’’). We also considered a model thatadditionally included an interaction betweenPF_STRESS and EB_STRESS to determine wheth-er the effects of extreme weather during succes-sive bioperiods were, for example, greater thantheir effects individually (‘‘interaction model’’).For each guild, we compared these two compet-ing models using Akaike’s information criterion(AIC) (Akaike 1974), calculating change in AIC(Di ), and examining ecoregion-specific coeffi-cients. As a rule of thumb, Di , 2.0 indicates asimilar level of support as the ‘‘best’’ model(Burnham and Anderson 2002).

Because of the log scaling and variation inbaseline abundance among the regions, coeffi-cients estimated from these models were difficultto compare and interpret. To better understandthe magnitude and variation of observed rela-tionships between the predictor variables andavian assemblages across ecoregions, we pro-duced a series of model predictions based on

different types of extreme conditions. We firstextracted the 99th percentile from each of thethree PC-transformed variables to obtain nomi-nal 100-year extreme events. We then used thecoefficients obtained from the fitted models toestimate the percentage change in avian abun-dance predicted to occur in response to each ofthe 100-year events.

RESULTS

During the nine years of this study, total birdabundance on routes ranged from 10 to 7134individuals. Abundance was highest in the northcentral and lowest in the inland southwesternportions of the conterminous US. Short distancemigrants were the most abundant guild (median¼ 249 individuals per route) and permanentresidents were the least (median ¼ 64).

The main effects models garnered much moresupport from the data than models incorporatingbioperiod interactions, as indicated by compari-son of Di. The within-guild Di values for theinteraction models were ALL: 16.57, GROUND:8.77, RESIDENT: 13.08, SHORTDIST: 1.66, NEO-TROP: 27.01. As such, subsequent results anddiscussion will focus on main effects-only mod-els. Coefficients estimated from this model for alllandbirds included numerous significant termsand considerable variation among ecoregions(Table 3).

The effects of drought and heat waves onlandbird abundance differed considerablyamong the bioperiods. The estimated effect ofstress during the post fledging bioperiod(PF_STRESS) was negative in every ecoregion,but the effect of extreme weather associated withthe early breeding period (EB_STRESS) was aslikely to be positive as negative. The magnitudeof the abundance changes varied considerablyamong bioperiods, as illustrated by the modeledchanges in abundance following events of equiv-alent likelihood (Fig. 2, Appendix B). The largestmodeled declines in overall avian abundancewere associated with EB_STRESS, and includedthose in the temperate (�11.0%) and subtropicaldeserts (�23.1%) of the West. Although there wasconsiderable variation in effect size amongfunctional guilds, the pattern of consistentlynegative effects of PF_STRESS and varyingeffects of EB_STRESS generally held regardless


ALBRIGHT ET AL.

of guild (Fig. 2; Appendices B–F). As withlandbirds overall, the largest declines withinspecific guilds were in association with of EB_STRESS.

Avifauna response to DRYCOOL was bothmixed and muted, with only two ecoregions(Temperate Desert and Tropical/Subtropical Des-ert) having significantly negative coefficients andone region (West Coast Mountains) having asignificant positive coefficient. 100-year extremeconditions for DRYCOOL had only modestmodeled changes in avian abundance, with amaximum decline of 5.5% occurring in theTropSubDesert ecoregion. This mixed and mutedpattern generally held among the functionalguilds. However, there were some cases in whichabundance changes were greater in associationwith 100-year DRYCOOL events than for stressin either of the bioperiods. This was most notablein the ground nesting guild in the WestMtns andPrairie Subtropical ecoregions, which sawGROUND increases of 8.9% and 6.6%, respec-tively (Appendix B).

The distinct response of ground nesting birdsto DRYCOOL is but one example of a largeamount of variation in avian responses accordingto functional traits. Ground nesting birds ap-peared the most susceptible to large declines inassociation with extreme weather events duringeither of the bioperiods, having larger declines(including a 35.9% decline in the TropSubDesertecoregion) than any other guild and compara-

tively few increases in abundance (Appendix C).Among migratory guilds (Appendices D–F),short distance migrants had the largest modeleddeclines, although Neotropical migrants were theonly group to not include any significant positiveresponses to the 100-year events. Permanentresidents were notable for the range of modeledresponses, which included both large negativeand positive changes, depending on ecoregion.

As noted above, the relationship between theenvironmental variables and avian abundancevaried considerably among the ecoregions. Al-though declines in abundance were the onlysignificant response to post fledging stress, themagnitude of declines varied considerably, withthe largest declines occurring in the Southwest. Anotable exception to this geographic trend wasthe relatively large, 10.6% modeled decline inground nesting birds following 100-yearPF_STRESS event in the Warm ContinentalMountains ecoregion in the northeastern U.S. Incontrast to PF_STRESS, EB_STRESS produced awide range of significant positive and negativechanges in avian abundance. Ecoregions thatexperienced abundance increases following EB_STRESS were concentrated in northern andmountainous areas, while declines were concen-trated in the West and Southwest. In particular,the TropSubDesert ecoregion stood out as havingthe largest and most consistent declines.

Table 3. Ecoregion-specific coefficients (multiplied by 100) estimated for main effects model of overall avian

abundance and 95% confidence intervals.

Ecoregion PF_STRESS EB_STRESS DRYCOOL

HotContiEast –0.41 6 0.89 1.27 6 1.59 –1.34 6 1.49HotContiMtn –0.06 6 1.04 2.38 6 1.55 –1.17 6 1.51HotContiWest –0.95 6 0.61 –0.06 6 0.74 0.00 6 0.95PrairieSubtrop –1.22 6 1.12 0.47 6 1.56 –1.82 6 2.50PrairieTemp –0.94 6 0.91 1.55 6 0.97 –1.10 6 1.47SEMixedForest –0.56 6 0.67 –0.31 6 0.86 –1.44 6 1.54SWMountains –1.03 6 1.29 –0.88 6 1.34 –1.19 6 2.89SubCoastPlain –0.63 6 0.87 –0.47 6 1.10 –1.68 6 1.82TempDesert –0.94 6 1.27 –3.32 6 0.83 1.94 6 1.65TempSteppe –0.78 6 0.64 –1.88 6 0.56 –0.06 6 1.26TempStpMtns –0.92 6 0.79 1.27 6 0.74 0.28 6 1.44TropSubDesert –3.62 6 1.41 –7.47 6 1.33 3.14 6 2.78TropSubSteppe –1.44 6 0.69 –1.08 6 0.75 –0.70 6 1.69WarmConti –0.75 6 0.93 –0.05 6 1.14 –0.49 6 1.26WarmContiMtn –1.22 6 1.31 1.01 6 1.86 –0.89 6 1.48WestLowlands –2.50 6 2.34 0.70 6 2.11 –0.45 6 2.29WestMtns –1.04 6 1.21 0.30 6 1.17 –1.81 6 1.17

Note: Values in boldface indicate significant effects (P , 0.05).


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DISCUSSION

The co-occurrence of drought and heat waves

wielded strong influence on avian abundance in

the conterminous U.S. over our 9-year study

period. Modeled responses to periods of extreme

Fig. 2. Maps of modeled changes in community abundances of five different avian assemblages (rows) for three

different 100-year extreme events based on principal component axes used in this study (columns). The maps

show percent change in abundance increases (green) and decreases (magenta), with non-significant (P . 0.05)

changes shown with cross-hatching.


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weather, with avian abundance changing bymore than 15% in many cases, appeared moredramatic than found in previous studies in thecentral U.S. examining drought and heat wavesseparately (Albright et al. 2010, in press). Extremeweather occurring in both post-fledging andearly nesting periods influenced avian commu-nities, but in different ways. PF_STRESS consis-tently produced negative responses, but bothdeclines and increases in abundance were ofgreater magnitude following EB_STRESS. Julyand August temperatures (used in PF_STRESS),which are generally the highest of the year, areoften used in physiological studies of avianthermal stress (Guthery et al. 2001, McKechnieand Wolf 2010), so there is reason to expect thisperiod to be highly influential. However, becauseof the timing of surveys associated with the BBS,there is a much longer lag between the post-fledging bioperiod and the dates of avian datacollection used in this study. So, while heat anddrought occurring during the early breedingperiod may influence habitat selection, survival,and induce post-migratory movements amongadult birds, this approximately 10-month lagcould dampen the effects of PF_STRESS due tothe intervention of mortality during migration,density dependence, and other factors (Robinsonet al. 2007). We found little support for bioperiodinteractions, refuting our hypothesis that effectswould be greater following successively occur-ring PF_STRESS and EB_STRESS events than thesum of their effects individually.

In contrast to the jointly occurring droughtsand heat waves described above, droughtsaccompanied by relatively cool temperatures(and by corollary, heat waves with relativelyabundant precipitation) were associated withrelatively minor changes in avian abundance.There is a strong biophysical basis for increasedwater requirements of individual birds underhigh ambient temperatures (Williams and Tiele-man 2005). Thus, it is not surprising that evenextreme drought, if accompanied by coolertemperatures, would not affect avian abundanceas much as a more common hot drought. Anexplanation for the number of positive responsesto drought and heat is not clear.

Our findings reinforce and extend the impor-tance of functional characteristics in differentiat-ing the response of birds to extreme weather.

Most striking was the wide variation amongmigratory guilds in response to extremes associ-ated with EB_STRESS. In a number of ecore-gions, the response to EB_STRESS by permanentresidents was much more positive than that byNeotropical migrants. For the most part, theseregions tended to be either mountainous ornorthern, suggesting an influence of wintersnowfall (snow water equivalent is included inSPI) on avian community dynamics. The in-creased abundances associated with dry condi-tions could thus indicate less of a snow pack tochallenge resident birds’ access to resources(Albright et al. 2010). Although no migratoryguild responded positively, extreme weatherduring the post-fledging period was most influ-ential in reducing abundance of short distancemigrant birds, which may make decisions aboutdispersal during this period, potentially influ-encing their selection of habitat during thefollowing breeding season. Following this logic,the reduced abundance measured by BBS wouldreflect a tendency among short distance migrantbirds to avoid routes that experienced hot anddry conditions during the previous post-fledgingperiod. Among Neotropical migrants, this effectmay be overwhelmed by high mortality ratesfrom migration to and from their winteringgrounds (Sillett and Holmes 2002). Consideringnest location, we found that declines amongground nesting birds associated with droughtand heat waves were nearly always larger thanthose among landbirds overall across the entirestudy region. The declines in the deserts of theSouthwest were even stronger than found in astudy focusing on land surface temperature alone(Albright et al., in press) and the extension of thisground nesting effect to heavily forested regionsof the East was not expected. Unless heavilythinned, temperatures under forest canopies atground level tend to be less extreme than at thetop of the canopy (Rambo and North 2009).

This study covered a much greater diversity ofecoregions than any previous study. While someaspects of the influence of ecoregional variationon the response of birds to drought and heathave already been discussed, a few others meritemphasis here. The effects of drought and heatwaves were felt more strongly in the subtropicaldeserts of the Southwest than in any other region,despite the likely temporal mismatch between


ALBRIGHT ET AL.

the temperature metrics and the reproductivecycle of most species in this region. This suggeststhat these extremes can have large effects onobserved populations even outside of the periodsin breeding phenology to which we hypothe-sized avian species would be especially sensitive.Not only is this region subject to extremely hightemperatures that can exceed physiological limitsof birds (McKechnie and Wolf 2010), it isconsidered a climate change hot spot that ispredicted to see increasing interannual variabilityin precipitation (Diffenbaugh et al. 2008). On theother hand, more modest avian responses werefound in other regions, including much of thelowland portion of the eastern US. While wehave already discussed the tendency of somefunctional groups to respond positively to earlybreeding stress in northern and mountainousareas, we also uncovered surprisingly negativeresponses by ground-nesting and resident birdsin the WarmContiMtn region encompassing thenorthern Appalachian Mountains, for which anexplanation remains elusive.

While our study was not focused on identify-ing mechanisms associated with the changes inavian abundances we described, it provides someinsight. We can considered three broad processesby which environmental stresses, such asdrought and heat waves, affect avian abundance:(1) adult survival, (2) reproduction and recruit-ment, and/or (3) dispersal. While the effects ofeach of these in response to PF_STRESS could bedetected by our study, changes in survival anddispersal are the only possible responses toEB_STRESS detectable in BBS data collectedduring June of the same year. Given that someof the strongest responses were associated withthis early breeding bioperiod, it appears thatchanges in adult mortality and dispersal are thepredominant processes behind the observedchanges in abundance in our study. The relativecontribution of adult mortality and dispersalremains an important question. During times ofextreme weather, normally philopatric birds maydisperse to other regions, which serve as refugia.While there is evidence of this occurring inresponse to drought (Martin et al. 2007), theliterature does not provide examples of thisduring heat waves, which are a more suddenly-developing phenomenon. It is possible that birdsmay be limited in their ability to undertake a

demanding dispersal under duress to avoid theconsequences of a heat wave, especially when thespatial scale of the heat wave is broad. Morecommon in the literature are examples of heatwave-induced mortality (e.g., Finlayson 1932,Becker et al. 1997).

Our results highlight both important implica-tions and questions for a more climaticallyvariable future. Drought and heat waves influ-ence avian community structure across a broadrange of ecoregions, but reductions in avianabundance were the greatest in the arid South-west. Because the arid Southwest is predicted toexperience among the greatest increases ininterannual temperature and precipitation vari-ability, this finding merits special attention.While understanding the response to theseevents at the scale of one year is an importantstep, understanding the longer term demograph-ic consequences of altered variability regimes isan important emerging question. Theory andmodeling studies suggest reduced populationgrowth rates in more variable climates (Boyce etal. 2006). The degree to which this expresses itselfon real landscapes will be an interesting futurediscovery. The potential of birds undertakingenergetically-costly migrations to be especiallysusceptible to extreme events such as heat wavesand drought also deserves further study. Finally,we caution that because of our identification ofdispersal as a key response to environmentalextremes in this work, management and conser-vation decisions should consider the importanceof suitable refugium areas even if they are usedinfrequently.

ACKNOWLEDGMENTS

We gratefully acknowledge support for this researchby the NASA Biodiversity Program and the NASAInterdisciplinary Science Program. We thank thedevelopers of the R project, the nlme module, andColorBrewer.org. MODIS data were reprojected withthe MODIS reprojection tool 4.0 (USGS EROS, SiouxFalls, SD, USA). All spatial summaries were calculatedusing ERDAS 9.0 (ERDAS, Inc., Atlanta, GA, USA) andArcGIS 9.2 with the aid of Python 2.4 (ESRI, Redlands,CA, USA). We thank D. Helmers for assistance withPython scripts. We also thank B. Wolf and twoanonymous reviewers for comments that improvedthis manuscript. Finally, we thank the many coordina-tors and volunteers who make BBS possible.


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APPENDIX A

Classification of species by functional group. Due to intraspecific variation, not all species were assigned a

migratory habit or nesting location.

Scientific name Common name

Migratory habitNest location

Resident Shortdist Neotrop Ground

Ortalis vetula Plain Chachalaca XBonasa umbellus Ruffed Grouse XCentrocercus urophasianus Greater Sage-Grouse XCentrocercus minimus Gunnison Sage-Grouse XFalcipennis canadensis Spruce Grouse XLagopus lagopus Willow Ptarmigan XLagopus muta Rock Ptarmigan XLagopus leucura White-Tailed Ptarmigan XDendragapus obscurus or fuliginosus Blue Grouse XTympanuchus cupido Greater Prairie-Chicken X XTympanuchus pallidicinctus Lesser Prairie-Chicken X XMeleagris gallopavo Wild Turkey X XOreortyx pictus Mountain Quail XCallipepla squamata Scaled Quail XCallipepla californica California Quail XCallipepla gambelii Gambel’s Quail XColinus virginianus Northern Bobwhite X XCyrtonyx montezumae Montezuma Quail XCoragyps atratus Black Vulture XCathartes aura Turkey Vulture XGymnogyps californianus California Condor XPandion haliaetus Osprey XChondrohierax uncinatus Hook-Billed KiteElanoides forficatus Swallow-Tailed Kite XElanus leucurus White-Tailed Kite XRostrhamus sociabilis Snail Kite XIctinia mississippiensis Mississippi Kite XHaliaeetus leucocephalus Bald Eagle XCircus cyaneus Northern Harrier X XAccipiter striatus Sharp-Shinned Hawk XAccipiter cooperii Cooper’s Hawk XAccipiter gentilis Northern Goshawk XButeogallus anthracinus Common Black-Hawk XParabuteo unicinctus Harris’s Hawk XButeo lineatus Red-Shouldered Hawk XButeo platypterus Broad-Winged Hawk XButeo nitidus Gray Hawk XButeo brachyurus Short-Tailed Hawk XButeo swainsoni Swainson’s Hawk XButeo albicaudatus White-Tailed Hawk XButeo albonotatus Zone-Tailed Hawk XButeo jamaicensis Red-Tailed Hawk XButeo regalis Ferruginous Hawk XButeo lagopus Rough-Legged Hawk XAquila chrysaetos Golden Eagle XCaracara cheriway Crested Caracara XFalco sparverius American Kestrel XFalco columbarius Merlin XFalco femoralis Aplomado Falcon XFalco rusticolus Gyrfalcon XFalco peregrinus Peregrine Falcon XFalco mexicanus Prairie Falcon XPatagioenas leucocephala White-Crowned Pigeon XPatagioenas flavirostris Red-Billed Pigeon XPatagioenas fasciata Band-Tailed Pigeon XZenaida asiatica White-Winged Dove XZenaida macroura Mourning Dove XColumbina inca Inca Dove XColumbina passerina Common Ground-Dove XLeptotila verreauxi White-Tipped Dove X


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Aratinga holochlora Green ParakeetRhynchopsitta pachyrhyncha Thick-Billed Parrot XAmazona viridigenalis Red-Crowned Parrot XCoccyzus americanus Yellow-Billed Cuckoo XCoccyzus minor Mangrove Cuckoo XCoccyzus erythropthalmus Black-Billed Cuckoo XGeococcyx californianus Greater Roadrunner XCrotophaga ani Smooth-Billed Ani XCrotophaga sulcirostris Groove-Billed Ani XTyto alba Barn Owl XOtus flammeolus Flammulated Owl XMegascops kennicottii Western Screech-Owl XMegascops asio Eastern Screech-Owl XMegascops trichopsis Whiskered Screech-Owl XBubo virginianus Great Horned Owl XBubo scandiacus Snowy Owl XSurnia ulula Northern Hawk Owl XGlaucidium gnoma Northern Pygmy-OwlGlaucidium brasilianum Ferruginous Pygmy-Owl XMicrathene whitneyi Elf Owl XAthene cunicularia Burrowing Owl XStrix occidentalis Spotted Owl XStrix varia Barred Owl XStrix nebulosa Great Gray Owl XAsio otus Long-Eared Owl XAsio flammeus Short-Eared Owl X XAegolius funereus Boreal Owl XAegolius acadicus Northern Saw-Whet Owl XChordeiles acutipennis Lesser Nighthawk X XChordeiles minor Common Nighthawk X XChordeiles gundlachii Antillean NighthawkNyctidromus albicollis Common Pauraque XPhalaenoptilus nuttallii Common Poorwill X XCaprimulgus carolinensis Chuck-Will’s-Widow X XCaprimulgus ridgwayi Buff-Collared Nightjar XCaprimulgus vociferus Whip-Poor-Will X XCypseloides niger Black Swift XChaetura pelagica Chimney Swift XChaetura vauxi Vaux’s Swift XAeronautes saxatalis White-Throated Swift XCynanthus latirostris Broad-Billed Hummingbird XHylocharis leucotis White-Eared HummingbirdAmazilia beryllina Berylline HummingbirdAmazilia yucatanensis Buff-Bellied Hummingbird XAmazilia violiceps Violet-Crowned Hummingbird XLampornis clemenciae Blue-Throated Hummingbird XEugenes fulgens Magnificent Hummingbird XCalothorax lucifer Lucifer Hummingbird XArchilochus colubris Ruby-Throated Hummingbird XArchilochus alexandri Black-Chinned Hummingbird XCalypte anna Anna’s Hummingbird XCalypte costae Costa’s Hummingbird XStellula calliope Calliope Hummingbird XSelasphorus platycercus Broad-Tailed Hummingbird XSelasphorus rufus Rufous Hummingbird XSelasphorus sasin Allen’s Hummingbird XTrogon elegans Elegant Trogon XMegaceryle torquata Ringed Kingfisher XMegaceryle alcyon Belted Kingfisher XChloroceryle americana Green Kingfisher XMelanerpes lewis Lewis’s Woodpecker XMelanerpes erythrocephalus Red-Headed Woodpecker XMelanerpes formicivorus Acorn Woodpecker XMelanerpes uropygialis Gila Woodpecker XMelanerpes aurifrons Golden-Fronted Woodpecker XMelanerpes carolinus Red-Bellied Woodpecker X


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Continued.




Sphyrapicus thyroideus Williamson’s Sapsucker XSphyrapicus varius Yellow-Bellied Sapsucker XSphyrapicus nuchalis Red-Naped Sapsucker XSphyrapicus ruber Red-Breasted Sapsucker XPicoides scalaris Ladder-Backed Woodpecker XPicoides nuttallii Nuttall’s Woodpecker XPicoides pubescens Downy Woodpecker XPicoides villosus Hairy Woodpecker XPicoides arizonae Arizona Woodpecker XPicoides borealis Red-Cockaded Woodpecker XPicoides albolarvatus White-Headed Woodpecker XPicoides dorsalis American Three-Toed Woodpecker XPicoides arcticus Black-Backed Woodpecker XColaptes auratus Northern Flicker XColaptes chrysoides Gilded FlickerDryocopus pileatus Pileated Woodpecker XCamptostoma imberbe Northern Beardless-Tyrannulet XContopus cooperi Olive-Sided Flycatcher XContopus pertinax Greater Pewee XContopus sordidulus Western Wood-Pewee XContopus virens Eastern Wood-Pewee XEmpidonax flaviventris Yellow-Bellied Flycatcher X XEmpidonax virescens Acadian Flycatcher XEmpidonax alnorum Alder Flycatcher X XEmpidonax traillii Willow Flycatcher XEmpidonax minimus Least Flycatcher XEmpidonax hammondii Hammond’s Flycatcher XEmpidonax wrightii Gray Flycatcher XEmpidonax oberholseri Dusky Flycatcher XEmpidonax difficilis Pacific-Slope Flycatcher XEmpidonax occidentalis Cordilleran Flycatcher XEmpidonax fulvifrons Buff-Breasted Flycatcher XSayornis nigricans Black Phoebe XSayornis phoebe Eastern Phoebe XSayornis saya Say’s Phoebe XPyrocephalus rubinus Vermilion Flycatcher XMyiarchus tuberculifer Dusky-Capped Flycatcher XMyiarchus cinerascens Ash-Throated Flycatcher XMyiarchus crinitus Great Crested Flycatcher XMyiarchus tyrannulus Brown-Crested Flycatcher XPitangus sulphuratus Great Kiskadee XMyiodynastes luteiventris Sulphur-Bellied Flycatcher XTyrannus melancholicus Tropical Kingbird XTyrannus couchii Couch’s Kingbird XTyrannus vociferans Cassin’s Kingbird XTyrannus crassirostris Thick-Billed Kingbird XTyrannus verticalis Western Kingbird XTyrannus tyrannus Eastern Kingbird XTyrannus dominicensis Gray Kingbird XTyrannus forficatus Scissor-Tailed Flycatcher XPachyramphus aglaiae Rose-Throated BecardLanius ludovicianus Loggerhead Shrike XLanius excubitor Northern Shrike XVireo griseus White-Eyed Vireo X XVireo bellii Bell’s Vireo X XVireo atricapilla Black-Capped Vireo XVireo vicinior Gray Vireo XVireo flavifrons Yellow-Throated Vireo XVireo plumbeus Plumbeous Vireo XVireo cassinii Cassin’s Vireo XVireo solitarius Blue-Headed Vireo XVireo huttoni Hutton’s Vireo XVireo gilvus Warbling Vireo XVireo philadelphicus Philadelphia Vireo XVireo olivaceus Red-Eyed Vireo XVireo flavoviridis Yellow-Green Vireo X


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Continued.




Vireo altiloquus Black-Whiskered Vireo XPerisoreus canadensis Gray Jay XCyanocitta stelleri Steller’s Jay XCyanocitta cristata Blue Jay XCyanocorax yncas Green Jay XCyanocorax morio Brown JayAphelocoma coerulescens Florida Scrub-Jay X XAphelocoma insularis Island Scrub-Jay XAphelocoma californica Western Scrub-Jay XAphelocoma ultramarina Mexican Jay XGymnorhinus cyanocephalus Pinyon Jay XNucifraga columbiana Clark’s Nutcracker XPica hudsonia Black-Billed Magpie XPica nuttalli Yellow-Billed Magpie XCorvus brachyrhynchos American Crow XCorvus caurinus Northwestern Crow XCorvus imparatus Tamaulipas CrowCorvus ossifragus Fish Crow XCorvus cryptoleucus Chihuahuan Raven XCorvus corax Common Raven XEremophila alpestris Horned Lark X XProgne subis Purple Martin XTachycineta bicolor Tree Swallow XTachycineta thalassina Violet-Green Swallow XStelgidopteryx serripennis Northern Rough-Winged Swallow XRiparia riparia Bank Swallow XPetrochelidon pyrrhonota Cliff Swallow XPetrochelidon fulva Cave Swallow XHirundo rustica Barn Swallow XPoecile carolinensis Carolina Chickadee XPoecile atricapillus Black-Capped Chickadee XPoecile gambeli Mountain Chickadee XPoecile sclateri Mexican Chickadee XPoecile rufescens Chestnut-Backed Chickadee XPoecile hudsonica Boreal Chickadee XPoecile cincta Gray-Headed Chickadee XBaeolophus wollweberi Bridled Titmouse XBaeolophus inornatus Oak Titmouse XBaeolophus ridgwayi Juniper Titmouse XBaeolophus bicolor Tufted Titmouse XBaeolophus atricristatus Black-Crested Titmouse XAuriparus flaviceps Verdin XPsaltriparus minimus Bushtit XSitta canadensis Red-Breasted Nuthatch XSitta carolinensis White-Breasted Nuthatch XSitta pygmaea Pygmy Nuthatch XSitta pusilla Brown-Headed Nuthatch XCerthia americana Brown Creeper XCampylorhynchus brunneicapillus Cactus Wren XSalpinctes obsoletus Rock Wren X XCatherpes mexicanus Canyon Wren X XThryothorus ludovicianus Carolina Wren X XThryomanes bewickii Bewick’s Wren X XTroglodytes aedon House Wren XTroglodytes troglodytes Winter Wren X XCistothorus platensis Sedge Wren X XCistothorus palustris Marsh Wren X XCinclus mexicanus American Dipper X XRegulus satrapa Golden-Crowned Kinglet XRegulus calendula Ruby-Crowned Kinglet XPhylloscopus borealis Arctic WarblerPolioptila caerulea Blue-Gray Gnatcatcher XPolioptila californica California Gnatcatcher XPolioptila melanura Black-Tailed Gnatcatcher XPolioptila nigriceps Black-Capped GnatcatcherLuscinia svecica Bluethroat


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Continued.




Oenanthe oenanthe Northern WheatearSialia sialis Eastern Bluebird XSialia mexicana Western Bluebird XSialia currucoides Mountain Bluebird XMyadestes townsendi Townsend’s Solitaire X XCatharus fuscescens Veery X XCatharus minimus Gray-Cheeked Thrush X XCatharus bicknelli Bicknell’s Thrush XCatharus ustulatus Swainson’s Thrush X XCatharus guttatus Hermit Thrush X XHylocichla mustelina Wood Thrush XTurdus grayi Clay-Colored RobinTurdus migratorius American Robin XIxoreus naevius Varied Thrush XChamaea fasciata Wrentit X XDumetella carolinensis Gray Catbird XMimus polyglottos Northern Mockingbird XOreoscoptes montanus Sage Thrasher X XToxostoma rufum Brown Thrasher XToxostoma longirostre Long-Billed Thrasher XToxostoma bendirei Bendire’s Thrasher XToxostoma curvirostre Curve-Billed Thrasher XToxostoma redivivum California Thrasher XToxostoma crissale Crissal Thrasher X XToxostoma lecontei Le Conte’s Thrasher X XMotacilla alba White WagtailAnthus cervinus Red-Throated PipitAnthus rubescens American Pipit XAnthus spragueii Sprague’s Pipit X XBombycilla garrulus Bohemian Waxwing XBombycilla cedrorum Cedar Waxwing XPhainopepla nitens Phainopepla XPeucedramus taeniatus Olive Warbler XVermivora pinus Blue-Winged Warbler X XVermivora chrysoptera Golden-Winged Warbler X XVermivora peregrina Tennessee Warbler X XVermivora celata Orange-Crowned Warbler X XVermivora ruficapilla Nashville Warbler X XVermivora virginiae Virginia’s Warbler X XVermivora crissalis Colima Warbler XVermivora luciae Lucy’s Warbler XParula americana Northern Parula XParula pitiayumi Tropical Parula XDendroica petechia Yellow Warbler XDendroica pensylvanica Chestnut-Sided Warbler X XDendroica magnolia Magnolia Warbler XDendroica tigrina Cape May Warbler XDendroica caerulescens Black-Throated Blue Warbler XDendroica coronata Yellow-Rumped Warbler XDendroica nigrescens Black-Throated Gray Warbler XDendroica chrysoparia Golden-Cheeked Warbler XDendroica virens Black-Throated Green Warbler XDendroica townsendi Townsend’s Warbler XDendroica occidentalis Hermit Warbler XDendroica fusca Blackburnian Warbler XDendroica dominica Yellow-Throated Warbler XDendroica graciae Grace’s Warbler XDendroica pinus Pine Warbler XDendroica kirtlandii Kirtland’s Warbler XDendroica discolor Prairie Warbler X XDendroica palmarum Palm Warbler X XDendroica castanea Bay-Breasted Warbler XDendroica striata Blackpoll Warbler XDendroica cerulea Cerulean Warbler XMniotilta varia Black-And-White Warbler X XSetophaga ruticilla American Redstart X


ALBRIGHT ET AL.

Continued.




Protonotaria citrea Prothonotary Warbler XHelmitheros vermivorum Worm-Eating Warbler X XLimnothlypis swainsonii Swainson’s Warbler X XSeiurus aurocapilla Ovenbird X XSeiurus noveboracensis Northern Waterthrush X XSeiurus motacilla Louisiana Waterthrush X XOporornis formosus Kentucky Warbler X XOporornis agilis Connecticut Warbler X XOporornis philadelphia Mourning Warbler X XOporornis tolmiei Macgillivray’s Warbler X XGeothlypis trichas Common Yellowthroat X XWilsonia citrina Hooded Warbler X XWilsonia pusilla Wilson’s Warbler X XWilsonia canadensis Canada Warbler X XCardellina rubrifrons Red-Faced Warbler XMyioborus pictus Painted Redstart XBasileuterus rufifrons Rufous-Capped WarblerIcteria virens Yellow-Breasted Chat X XPiranga flava Hepatic Tanager XPiranga rubra Summer Tanager XPiranga olivacea Scarlet Tanager XPiranga ludoviciana Western Tanager XPiranga bidentata Flame-Colored TanagerSporophila torqueola White-Collared Seedeater XArremonops rufivirgatus Olive Sparrow X XPipilo chlorurus Green-Tailed Towhee X XPipilo maculatus Spotted Towhee X XPipilo erythrophthalmus Eastern Towhee X XPipilo fuscus Canyon Towhee X XPipilo crissalis California Towhee X XPipilo aberti Abert’s Towhee XAimophila carpalis Rufous-Winged Sparrow X XAimophila cassinii Cassin’s Sparrow X XAimophila aestivalis Bachman’s Sparrow X XAimophila botterii Botteri’s Sparrow X XAimophila ruficeps Rufous-Crowned Sparrow X XAimophila quinquestriata Five-Striped Sparrow XSpizella arborea American Tree Sparrow XSpizella passerina Chipping Sparrow XSpizella pallida Clay-Colored Sparrow X XSpizella breweri Brewer’s Sparrow X XSpizella pusilla Field Sparrow X XSpizella atrogularis Black-Chinned Sparrow X XPooecetes gramineus Vesper Sparrow X XChondestes grammacus Lark Sparrow X XAmphispiza bilineata Black-Throated Sparrow X XAmphispiza belli Sage Sparrow X XCalamospiza melanocorys Lark Bunting X XPasserculus sandwichensis Savannah Sparrow X XAmmodramus savannarum Grasshopper Sparrow X XAmmodramus bairdii Baird’s Sparrow X XAmmodramus henslowii Henslow’s Sparrow X XAmmodramus leconteii Le Conte’s Sparrow X XAmmodramus nelsoni Nelson’s Sharp-Tailed Sparrow X XAmmodramus caudacutus Saltmarsh Sharp-Tailed Sparrow X XAmmodramus maritimus Seaside Sparrow X XPasserella iliaca Fox Sparrow X XMelospiza melodia Song Sparrow X XMelospiza lincolnii Lincoln’s Sparrow X XMelospiza georgiana Swamp Sparrow X XZonotrichia albicollis White-Throated Sparrow X XZonotrichia querula Harris’s Sparrow XZonotrichia leucophrys White-Crowned Sparrow X XZonotrichia atricapilla Golden-Crowned Sparrow XJunco hyemalis Dark-Eyed Junco X XJunco phaeonotus Yellow-Eyed Junco X


ALBRIGHT ET AL.

Continued.




Calcarius mccownii Mccown’s Longspur X XCalcarius lapponicus Lapland Longspur XCalcarius pictus Smith’s Longspur XCalcarius ornatus Chestnut-Collared Longspur X XPlectrophenax nivalis Snow Bunting XPlectrophenax hyperboreus Mckay’s Bunting XCardinalis cardinalis Northern Cardinal XCardinalis sinuatus Pyrrhuloxia XPheucticus ludovicianus Rose-Breasted Grosbeak XPheucticus melanocephalus Black-Headed Grosbeak XPasserina caerulea Blue Grosbeak X XPasserina amoena Lazuli Bunting X XPasserina cyanea Indigo Bunting X XPasserina versicolor Varied Bunting XPasserina ciris Painted Bunting XSpiza americana Dickcissel X XDolichonyx oryzivorus Bobolink X XAgelaius phoeniceus Red-Winged Blackbird X XAgelaius tricolor Tricolored Blackbird X XSturnella magna Eastern Meadowlark X XSturnella neglecta Western Meadowlark X XXanthocephalus xanthocephalus Yellow-Headed Blackbird X XEuphagus carolinus Rusty Blackbird XEuphagus cyanocephalus Brewer’s Blackbird XQuiscalus quiscula Common Grackle XQuiscalus major Boat-Tailed Grackle XQuiscalus mexicanus Great-Tailed Grackle XMolothrus bonariensis Shiny CowbirdMolothrus aeneus Bronzed Cowbird XMolothrus ater Brown-Headed Cowbird XIcterus spurius Orchard Oriole XIcterus cucullatus Hooded Oriole XIcterus pustulatus Streak-Backed OrioleIcterus bullockii Bullock’s Oriole XIcterus gularis Altamira Oriole XIcterus graduacauda Audubon’s Oriole XIcterus galbula Baltimore Oriole XIcterus parisorum Scott’s Oriole XLeucosticte spp Unid. Rosy-Finch XPinicola enucleator Pine Grosbeak XCarpodacus purpureus Purple Finch XCarpodacus cassinii Cassin’s Finch XCarpodacus mexicanus House Finch XLoxia curvirostra Red Crossbill XLoxia leucoptera White-Winged Crossbill XCarduelis flammea Common Redpoll XCarduelis hornemanni Hoary Redpoll XCarduelis pinus Pine Siskin XCarduelis psaltria Lesser Goldfinch XCarduelis lawrencei Lawrence’s Goldfinch XCarduelis tristis American Goldfinch XCoccothraustes vespertinus Evening Grosbeak X


ALBRIGHT ET AL.

APPENDIX B

APPENDIX C

Predicted changes in abundance following 100-year extreme events: All landbirds.


HotContiEast –1.47 6 3.14 4.53 6 5.66 2.42 6 2.71HotContiMtn –0.22 6 3.71 8.67 6 5.73 2.11 6 2.73HotContiWest –3.39 6 2.14 –0.21 6 2.54 –0.01 6 1.69PrairieSubtrop –4.34 6 3.82 1.65 6 5.41 3.31 6 4.53PrairieTemp –3.38 6 3.15 5.58 6 3.53 2.00 6 2.65SEMixedForest –2.01 6 2.38 –1.07 6 2.95 2.62 6 2.79SWMountains –3.68 6 4.44 –3.03 6 4.43 2.16 6 5.17SubCoastPlain –2.27 6 3.06 –1.63 6 3.71 3.06 6 3.30TempDesert –3.38 6 4.37 –10.98 6 2.56 –3.42 6 2.81TempSteppe –2.81 6 2.24 –6.38 6 1.81 0.11 6 2.24TempStpMtns –3.32 6 2.75 4.56 6 2.67 –0.49 6 2.54TropSubDesert –12.41 6 4.42 –23.05 6 3.50 –5.48 6 4.61TropSubSteppe –5.14 6 2.37 –3.70 6 2.50 1.26 6 3.03WarmConti –2.69 6 3.25 –0.16 6 3.91 0.88 6 2.25WarmContiMtn –4.35 6 4.48 3.61 6 6.53 1.60 6 2.66WestLowlands –8.72 6 7.47 2.48 6 7.31 0.80 6 4.05WestMtns –3.73 6 4.16 1.07 6 4.05 3.30 6 2.14


Predicted changes in abundance following 100-year extreme events: Ground-nesting birds.


HotContiEast –2.52 6 4.15 –0.14 6 7.15 3.51 6 3.64HotContiMtn –1.67 6 4.86 2.79 6 7.16 3.04 6 3.67HotContiWest –2.13 6 2.87 –1.93 6 3.31 1.33 6 2.28PrairieSubtrop –3.09 6 5.12 –4.80 6 6.73 8.85 6 6.32PrairieTemp –5.72 6 4.08 5.37 6 4.68 3.12 6 3.54SEMixedForest –6.84 6 3.00 –3.12 6 3.82 2.08 6 3.70WMountains –4.15 6 5.87 –10.77 6 5.45 –0.12 6 6.73SubCoastPlain –4.24 6 3.98 –2.99 6 4.87 2.62 6 4.38TempDesert –0.16 6 6.00 –13.51 6 3.30 –3.51 6 3.73TempSteppe –4.52 6 2.93 –9.40 6 2.35 2.15 6 3.03TempStpMtns –6.13 6 3.57 6.21 6 3.62 1.64 6 3.45TropSubDesert –18.47 6 5.44 –35.85 6 3.93 –15.06 6 5.54TropSubSteppe –7.96 6 3.04 –9.01 6 3.16 –0.21 6 3.96WarmConti –2.39 6 4.33 –0.88 6 5.15 0.47 6 2.98WarmContiMtn –10.62 6 5.58 2.73 6 8.58 0.54 6 3.50WestLowlands –6.99 6 10.08 –5.10 6 8.87 3.25 6 5.52WestMtns –1.37 6 5.70 –0.30 6 5.29 6.59 6 2.95



ALBRIGHT ET AL.

APPENDIX D

APPENDIX E

Predicted changes in abundance following 100-year extreme events: Permanent resident birds.


HotContiEast 2.97 6 7.22 14.35 6 13.24 –1.31 6 5.70HotContiMtn –0.94 6 8.02 23.44 6 13.91 –2.70 6 5.72HotContiWest –2.36 6 4.75 8.20 6 6.05 –1.21 6 3.71PrairieSubtrop –4.03 6 8.16 1.96 6 11.68 1.68 6 9.57PrairieTemp 7.52 6 7.88 16.79 6 8.73 2.85 6 5.95SEMixedForest –1.57 6 5.19 –0.04 6 6.42 1.74 6 6.08SWMountains 2.25 6 10.27 13.2 6 11.4 –6.22 6 10.44SubCoastPlain –3.70 6 6.53 0.19 6 8.21 3.30 6 7.22TempDesert –8.07 6 9.48 –8.04 6 6.03 –8.13 6 6.09TempSteppe 0.47 6 5.77 13.81 6 5.48 13.00 6 6.20TempStpMtns –6.77 6 6.02 10.64 6 6.36 1.14 6 5.80TropSubDesert –14.21 6 9.06 –27.22 6 7.25 –4.16 6 10.14TropSubSteppe –3.87 6 5.10 –0.98 6 5.65 3.21 6 6.68WarmConti –1.62 6 7.37 6.83 6 9.33 –1.72 6 4.95WarmContiMtn 2.49 6 10.70 –15.45 6 11.76 6.33 6 6.23WestLowlands 0.83 6 17.70 –5.54 6 14.23 0.02 6 8.83WestMtns –7.13 6 8.85 0.55 6 8.71 1.56 6 4.65


Predicted changes in abundance following 100-year extreme events: Short distance migrant birds.


HotContiEast –3.1 6 3.82 3.33 6 6.87 5.33 6 3.44HotContiMtn 0.35 6 4.60 9.92 6 7.12 2.57 6 3.39HotContiWest –5.90 6 2.57 –0.85 6 3.12 1.08 6 2.12PrairieSubtrop –1.63 6 4.82 6.52 6 7.00 6.51 6 5.75PrairieTemp –5.27 6 3.82 7.50 6 4.44 2.38 6 3.27SEMixedForest –1.79 6 2.94 –0.96 6 3.63 5.28 6 3.55SWMountains –12.65 6 4.98 –6.48 6 5.31 1.79 6 6.39SubCoastPlain –0.26 6 3.85 –0.26 6 4.65 1.99 6 4.05TempDesert –1.27 6 5.53 –12.32 6 3.11 –5.84 6 3.39TempSteppe –4.68 6 2.72 –3.17 6 2.33 2.29 6 2.83TempStpMtns –8.28 6 3.25 8.17 6 3.43 1.03 6 3.19TropSubDesert –13.68 6 5.32 –32.66 6 3.81 –4.70 6 5.76TropSubSteppe –5.52 6 2.89 –1.10 6 3.19 1.67 6 3.75WarmConti –3.04 6 4.01 2.00 6 4.93 1.12 6 2.79WarmContiMtn –5.30 6 5.50 7.81 6 8.39 4.96 6 3.40WestLowlands –14.89 6 8.60 5.11 6 9.15 –0.25 6 4.97WestMtns –4.38 6 5.14 8.13 6 5.33 4.05 6 2.68



ALBRIGHT ET AL.

APPENDIX F

Predicted changes in abundance following 100-year extreme events: Neotropical migrant birds.


HotContiEast –1.16 6 4.35 1.51 6 7.41 1.39 6 3.68HotContiMtn –0.09 6 5.07 2.75 6 7.30 3.84 6 3.83HotContiWest –0.92 6 2.99 –1.1 0 63.44 –1.29 6 2.30PrairieSubtrop –4.47 6 5.10 –4.58 6 6.94 2.72 6 6.10PrairieTemp –1.73 6 4.42 1.30 6 4.66 0.75 6 3.56SEMixedForest –2.01 6 3.23 –2.39 6 3.92 0.66 6 3.79SWMountains 0.86 6 6.36 –5.33 6 6.00 5.41 6 7.38SubCoastPlain –1.49 6 4.22 –3.00 6 5.03 3.28 6 4.57TempDesert –9.02 6 5.71 –11.52 6 3.47 –0.32 6 3.97TempSteppe 2.78 6 3.27 –15.12 6 2.32 –4.66 6 2.93TempStpMtns 1.63 6 4.02 1.55 6 3.59 –0.77 6 3.45TropSubDesert –5.85 6 6.42 –1.08 6 6.29 –10.95 6 6.05TropSubSteppe –5.25 6 3.19 –5.83 6 3.42 0.01 6 4.09WarmConti –2.63 6 4.46 –0.93 6 5.32 1.07 6 3.09WarmContiMtn –5.73 6 6.11 3.76 6 8.96 –0.19 6 3.58WestLowlands –5.65 6 10.65 4.94 6 9.88 1.59 6 5.65WestMtns –4.14 6 5.78 –2.22 6 5.26 2.92 6 2.93



ALBRIGHT ET AL.

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Combined effects of heat waves and droughts on avian ...silvis.forest.wisc.edu/wp-content/uploads/pubs/SILVIS/Albright_et_al... · ate North America, changes in the interannual variability