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Environmental drivers and spatial scaling of species abundance distributions in Palaearctic grassland vegetation

Abstract

We thank all vegetation scientists who carefully collected the plant diversity data and contributed them to GrassPlot. The Eurasian Dry Grassland Group (EDGG) and the International Association for Vegetation Science (IAVS) supported the EDGG field workshops, which generated a core part of the GrassPlot data. The Bavarian Research Alliance (via the BayIntAn scheme) and the Bayreuth Center of Ecology and Environmental Research (BayCEER) funded the initial GrassPlot workshop during which the database was established (grants to Jurgen Dengler). Werner Ulrich acknowledges support from the Polish National Science Centre (Grant 2017/27/B/NZ8/00316). Idoia Biurrun and Juan Antonio Campos were partly supported by the Basque Government (IT936-16). Goffredo Filibeck was partly supported by the MIUR initiative "Department of Excellence" (Law 232/2016) granted to DAFNE. Peter Torok was supported by the NKFIH K 119225 and K 137573 projects and the HAS Momentum Program during the manuscript preparation. Franz Essl appreciates funding by the Austrian Science Foundation FWF (Grant I 3757-B29).

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Environmental drivers and spatial scaling of species abundance distributions in Palaearctic grassland vegetation

Author: Ulrich, Werner,Matthews, Thomas J.,Biurrun Galarraga, Miren Idoia,Campos Prieto, Juan Antonio,Czortek, Patryk,Dembicz, Iwona,Essl, Franz,Filibeck, Goffredo,Giusso del Galdo, Gian Pietro,Guler, Behlul,Naqinezhad, Alireza,Torok, Peter,Dengler, Juergen
Publisher: Wiley
Year: 2022
DOI: 10.1002/ecy.3725
Source: https://addi.ehu.eus/bitstream/10810/57420/1/Ecology%20-%202022%20-%20Ulrich%20-%20Environmental%20drivers%20and%20spatial%20scaling%20of%20species%20abundance%20distributions%20in%20Palaearctic.pdf
ARTICLE
En i onmen al d i e s and spa ial scaling o species
abundance dis ibu ions in Palaea c ic g assland ege a ion
We ne Ul ich
1
| Thomas J. Ma hews
2,3
| Idoia Biu un
4
|
Juan An onio Campos
4
| Pa yk Czo ek
5
| Iwona Dembicz
6
|
F anz Essl
7
| Go edo Filibeck
8
| Gian-Pie o Giusso del Galdo
9
|
Behlül Güle
10
| Ali eza Naqinezhad
11
| Pé e Tö ök
12,13,14
|
Jü gen Dengle
15,16
1
Depa men o Ecology and Biogeog aphy, Nicolaus Cope nicus Uni e si y, To u
n, Poland
2
GEES (School o Geog aphy, Ea h and En i onmen al Sciences) and Bi mingham Ins i u e o Fo es Resea ch, Uni e si y o Bi mingham,
Bi mingham, UK
3
cE3c –Cen e o Ecology, E olu ion and En i onmen al Changes/Azo ean Biodi e si y G oup/CHANGE –Global Change and Sus ainabili y
Ins i u e and Uni e sidade dos Aço es (FCAA), Ang a do He oísmo, Po ugal
4
Depa men o Plan Biology and Ecology, Uni e si y o he Basque Coun y UPV/EHU, Bilbao, Spain
5
Białowieża Geobo anical S a ion, Facul y o Biology, Uni e si y o Wa saw, Białowieża, Poland
6
Depa men o Ecology and En i onmen al Conse a ion, Ins i u e o En i onmen al Biology, Facul y o Biology, Uni e si y o Wa saw,
Wa saw, Poland
7
Bioin asions, Global Change, Mac oecology G oup, Depa men o Bo any and Biodi e si y Resea ch, Uni e si y o Vienna, Vienna, Aus ia
8
Depa men o Ag icul u e and Fo es Science (DAFNE), Uni e si y o Tuscia, Vi e bo, I aly
9
Depa men o Biological, Geological and En i onmen al Sciences, Uni e si y o Ca ania, Ca ania, I aly
10
Biology Educa ion, Dokuz Eylul Uni e si y, _
Izmi , Tu key
11
Depa men o Plan Biology, Facul y o Basic Sciences, Uni e si y o Mazanda an, Mazanda an, I an
12
MTA-DE Lendüle Func ional and Res o a ion Ecology Resea ch G oup, Uni e si y o Deb ecen, Deb ecen, Hunga y
13
Polish Academy o Sciences, Bo anical Ga den - Cen e o Biological Di e si y Conse a ion in Powsin, Wa szawa, Poland
14
Depa men o Ecology, Uni e si y o Deb ecen, Deb ecen, Hunga y
15
Vege a ion Ecology, Ins i u e o Na u al Resou ce Managemen (IUNR), Zu ich Uni e si y o Applied Sciences (ZHAW), Wädenswil, Swi ze land
16
Plan Ecology, Bay eu h Cen e o Ecology and En i onmen al Resea ch (BayCEER), Uni e si y o Bay eu h, Bay eu h, Ge many
Co espondence
We ne Ul ich
Email: [email p o ec ed]
Funding in o ma ion
Aus ian Science Founda ion, G an /
Awa d Numbe : I 3757-B29; Basque
Go e nmen , G an /Awa d Numbe :
IT936-16; HAS Momen um P og am,
G an /Awa d Numbe s: NKFIH K 119225,
K 137573; MIUR Ini ia i e, G an /Awa d
Numbe : Law 232/2016; Na odowe
Abs ac
Species abundance dis ibu ions (SADs) link species ichness wi h species
abundances and a e an impo an ool in he quan i a i e analysis o ecological
communi ies. Niche-based and sample-based SAD models p edic di e en
spa ial scaling p ope ies o SAD pa ame e s. Howe e , empi ical esea ch on
SAD scaling p ope ies is la gely missing. He e we ex ac ed pe cen age co e
alues o all occu ing ascula plan s as p oxies o hei abundance in 1725
10-m
2
plo s om he G assPlo da abase, co e ing 47 egional da a se s o
Recei ed: 26 Oc obe 2021 Re ised: 2 Ma ch 2022 Accep ed: 7 Ma ch 2022
DOI: 10.1002/ecy.3725
This is an open access a icle unde he e ms o he C ea i e Commons A ibu ion License, which pe mi s use, dis ibu ion and ep oduc ion in any medium, p o ided
he o iginal wo k is p ope ly ci ed.
© 2022 The Au ho s. Ecology published by Wiley Pe iodicals LLC on behal o The Ecological Socie y o Ame ica.
Ecology. 2022;103:e3725. h ps://onlinelib a y.wiley.com/ /ecy 1o 16
h ps://doi.o g/10.1002/ecy.3725
Cen um Nauki, G an /Awa d Numbe :
2017/27/B/NZ8/00316; Ba a ian Resea ch
Alliance
Handling Edi o : Helmu Hilleb and
19 di e en g asslands and o he open ege a ion ypes o he Palaea c ic bio-
geog aphic ealm. Fo each plo , we i ed he Weibull dis ibu ion, a model
ha is able o e ec i ely mimic o he dis ibu ions like he log-se ies and log-
no mal, o he species–log abundance ank o de dis ibu ion. We calcula ed
he skewness and ku osis o he empi ical dis ibu ions and linked hese
momen s, along wi h he shape and scale pa ame e s o he Weibull dis ibu-
ion, o plo clima ic and soil cha ac e is ics. The Weibull dis ibu ion p o ided
excellen i s o g assland plan communi ies and iden i ied ou basic ypes o
communi ies cha ac e ized by di e en deg ees o dominance. Shape and scale
pa ame e alues o local communi ies on poo e soils we e la gely in acco -
dance wi h log-se ies dis ibu ions. P opo ions o subdominan species ended
o be lowe han p edic ed by he s anda d logno mal SAD. Successi e accu-
mula ion o plo s o he same ege a ion ype yielded nonlinea spa ial scaling
o SAD momen s and Weibull pa ame e s. This scaling was la gely indepen-
den o en i onmen al co ela es and geog aphic plo posi ion. Ou indings
cau ion agains simple gene aliza ions abou he mechanisms ha gene a e
SADs. We a gue ha in g asslands, logno mal- ype SADs end o p e ail
wi hin a wide ange o en i onmen al condi ions, including mo e ex eme
habi a s such as a id en i onmen s. In con as , log-se ies dis ibu ions a e
mainly es ic ed o compa a i ely species- ich communi ies on humid and
e ile soils.
KEYWORDS
logno mal dis ibu ion, log-se ies dis ibu ion, Palaea c ic g assland, plan co e , spa ial
scaling, species abundance, Weibull dis ibu ion
INTRODUCTION
Mo e han 80 yea s a e he seminal wo k o Mo omu a
(1932), he concep o he species abundance dis ibu ion
(SAD) in ecological communi ies emains a ocus o eco-
logical in e es (Ma hews & Whi ake , 2014; McGill
e al., 2007; Ul ich e al., 2010). SADs link species ich-
ness wi h ela i e species abundances and exhibi a con-
sis en gene al o m wi h many a e and ew abundan
species (McGill e al., 2007). They a e impo an in he
quan i a i e analysis o ecological communi ies, pa icu-
la ly in he quan i ica ion o a i y (Kunin, 1997), com-
pe i i e hie a chies (Mac Nally e al., 2014), niche
pa i ioning (Sugiha a e al., 2003; Tokeshi, 1999),
changes in species unc ional ai s (Dan as de Mi anda
e al., 2019), and he concep o neu al communi y
assembly (Hubbell, 2001; May, 1975). Recen in e es has
shi ed om s a is ical dis ibu ion i ing (Alonso
e al., 2008; Bald idge e al., 2016; Mo lon e al., 2009;
Ul ich e al., 2010) and he es ing o he unde lying
niche-based and s ochas ic heo ies (Connolly
e al., 2005; Magu an & Hende son, 2003) owa d he
analysis o obse ed and p edic ed changes in ela i e
abundances ac oss spa ial (Bo da-De-
Agua, e al., 2012;
Fe ei a de Lima e al., 2020;Šizling e al., 2009) and em-
po al (Tomašo ých & Kidwell, 2010) scales. A g ea e
unde s anding o he scaling o SADs and he unc ional
consequences o SAD scaling pa e ns a e no jus o he-
o e ical in e es , and will likely be use ul in biodi e si y
managemen (Ma hews & Whi ake , 2015).
Compe i i e and niche-o ien a ed app oaches ha e
o en assumed SADs o be gene ic p ope ies o ecological
communi ies de e mined by species in e ac ions (Cen u i
on
&L

opez Gappa, 2011;Tokeshi,1999)andnichepa -
i ioning (Sugiha a, 1980). Niche-o ien a ed SAD model
pa ame e s a e de e mined by species ichness and he
speci ic pa e n o niche di ision, bu no by he empo al
o spa ial dynamics o communi y assembly. Howe e ,
sample-based heo e ical wo k has demons a ed ha he
pa ame e s o impo an SAD models change wi h inc eas-
ing sample size (G een & Plo kin, 2007;Šizling e al., 2009)
and pa e ns o spa ial agg ega ion (Do nelas & Connolly,
2008).Thesemodelsinclude heexponen ialse ies,cha ac-
e ized by iden ical p opo ions o species along he g adien
2o 16 ULRICH ET AL.
o log- ans o med species abundance (Mo omu a, 1932),
he log-se ies sample dis ibu ion, cha ac e ized by a ew
highly abundan species and an excess o species ep esen-
ed by a single indi idual (Fishe e al., 1943), and he log-
no mal dis ibu ion, cha ac e ized by a compa a i ely high
numbe o species wi h in e media e abundance and simila
numbe s o ela i ely abundan and a e species (Gas on &
Blackbu n, 2000;P es on,1948). Impo an ly, Locey and
Whi e (2013)demons a ed ha heshapeo SADsisde e -
mined by he in e play o he o al numbe s o indi iduals
and species. Bo h inc ease wi h inc easing sample a ea.
The e o e, he sample beha io o SADs should au oma i-
cally ansla e in o changes in SAD shape ac oss spa ial
scales. The si ua ion is complica edby he ac ha local
communi ies a e no simply andomsamples om he
la ge egional species pools. Ins ead, hey esul om h ee
basic p ocesses: species-speci ic dispe sal, habi a il e ing,
and local species in e ac ions (e.g., D’Amen e al., 2017;
Tö ök e al., 2018;Vellend,2016). These h ee p ocesses
ope a e di e en ly a di e en spa ial scales. As such, o
his eason, we also canno expec SADs o be in a ian o
spa ial scale.
A spa ial ex en s abo e he local communi y, wo
con as ing heo e ical app oaches p edic di e en SAD
shapes. Neu al app oaches gene ally p edic ha log-
se ies SADs will cha ac e ize egional species pools
(Hubbell, 2001), as epo ed by Wu e al. (2019). In con-
as , Connolly e al. (2005) epo ed scale-in a ian log-
no mal egional SADs o exhaus i ely sampled ma ine
ish and co al ee communi ies, a guing ha he
obse ed in a iance esul s om he co esponding scal-
ing o mul iple ecological p ocesses ha o ce SADs in o
a logno mal shape. We no e ha Šizling e al. (2009)
a gued agains exac scale in a iance o logno mal SADs.
These au ho s showed ha , i he SAD a one scale is log-
no mal, he SADs a o he scales con e ge on igh -
skewed dis ibu ions ha can appea oughly logno mal,
esul ing in appa en scale in a iance.
Ac oss axa, s udies ha e epo ed changes in he
(i) pa ame e s o he models ha bes i local SADs wi h
inc easing spa ial scale and (ii) ype o SAD model ha
p o ides he mos accu a e ep esen a ion o he empi i-
cal dis ibu ion (in wha ollows e e ed o as he SAD
shape). Fo example, Bo da-de-
Agua e al. (2017)
epo ed ha he a iance and skewness o a h opod
SADs changed p edic ably acco ding o an allome ic
unc ion along spa ial g adien s. Wu e al. (2019) ound
consis en di ec ional empo al changes in ini ially a i-
ably shaped local o es ee SADs owa d egional log-
se ies dis ibu ions as p edic ed by neu al, dispe sal-
d i en models (Hubbell, 2001). Fe ei a de Lima
e al. (2020) iden i ied a dec easing hie a chy o ac o s
ha igge a iabili y in B azilian A lan ic o es SAD
shapes ac oss spa ial and empo al scales: sample size,
conspeci ic agg ega ion, and β-di e si y. An ˜
ao e al. (2021)
ound ha Poisson logno mal models, including hose
wi h mul iple modes, p o ided he bes i o la ge-scale
SADs o mul iple axa ( he log-se ies ne e p o ided he
bes i o he la ges -scale SADs), whe eas a mix o log-
se ies and Poisson logno mal models p o ided he bes
i s o he SADs o smalle a eas.
This p io wo k has no esol ed he ques ion o
whe he obse ed changes in SAD shapes wi h g ain
size and in esponse o he a o emen ioned h ee
basic p ocesses (in e ac ions, il e ing, dispe sal) occu
in a p edic able way and whe he hey a e axon- o
communi y-speci ic. I also emains unclea whe he
SAD scaling in ol es g adual changes in pa ame e
alues wi hin he same ype o dis ibu ion o , ins ead,
la ge and ab up shi s (i.e., b eakpoin s) in pa ame e
alues and hus swi ching be ween di e en ypes o
dis ibu ions. Sample heo y (G een & Plo kin, 2007)
assumes g adual changes in SAD model pa ame e alues
wi hin he same gene al dis ibu ion shape, whe eas ce ain
neu al models (e.g., Hubbell, 2001) p edic la ge shi s
om egional log-se ies SADs owa d local logno mal- ype
dis ibu ions, depending on he deg ee o dispe sal limi a-
ion. Such changes in ela i e abundance ha e s ong impli-
ca ions o he scaling o he ecological p ocesses ha
de e mine he hie a chy o species abundances. An empi i-
cal assessmen o he ype o scaling and he espec i e scal-
ing pa ame e s would allow o an imp o ed ex apola ion
o obse ed abundance dis ibu ions.
Excep o he in luence o dispe sal, ew empi ical
s udies ha e deal wi h he ecological d i e s ha in lu-
ence he spa ial scaling o SADs, pa icula ly o plan s.
Global compa isons o woody (Ma hews e al., 2019;
Ul ich e al., 2018) and d yland plan s (Ul ich e al.,
2016) and local compa isons o o es gaps (Sal ado - an
Eysen ode e al., 2003) ha e highligh ed he impo ance
o clima ic a iabili y and en i onmen al s ess. Wo k on
o he plan g oups is lacking, as a e scaling analyses
ocused on ine, local-scale SAD da a. He e we ill his
knowledge gap by ocusing on ex a- opical g asslands
and o he open ege a ion communi ies. We use an
excep ionally la ge Palaea c ic da a se , he G assPlo
da abase (Biu un e al., 2019,2021; Dengle e al., 2018),
o add ess he ques ions a ound he scaling o abundance
dis ibu ions, using pe cen age co e es ima es as p oxies
o abundance. The G assPlo da a s em om di e se si e
condi ions (e.g., om sea le el o mo e han
5000 m abo e sea le el [a.s.l.], om e y we o e y d y
si es, and om humid o semia id clima es) and manage-
men egimes (e.g., na u al, semina u al, in ensi ied)
(Dengle e al., 2020). This a ia ion makes i possible o
link he obse ed changes in SAD pa ame e alues o
ECOLOGY 3o 16
en i onmen al cha ac e is ics. Impo an ly, ou da a
allow us o s udy he scaling o SADs wi hin iden ical
ege a ion ypes and o compa e he pa e ns o scaling
among ege a ion ypes.
Based on he p eceding discussion o empi ical and
sample heo e ical p edic ions, we examine (i) which
ypes o SADs a e ealized in ex a- opical g asslands,
(ii) how SAD shape changes ac oss en i onmen al g adi-
en s ac oss he Palaea c ic, and (iii) whe he and how he
scaling o SADs along spa ial g adien s migh in luence
in e ences o SAD a iabili y a la ge , geog aphical spa-
ial scales.
MATERIALS AND METHODS
Vege a ion-plo da a
We compiled da a om 3531 plo s ac oss 56 da a se s om
he collabo a i e ege a ion-plo da abase G assPlo
(Biu un e al., 2019; Dengle e al., 2018,h ps://edgg.o g/
da abases/G assPlo ). Using a minimum species ichness
h eshold o 20 o il e hese da a, we ex ac ed ascula
plan da a om 1725 single plo s ac oss 47 da a se s each
co e ing an a ea o 10 m
2
(da a se s, me ada a, and e e -
ences in Ul ich e al., 2021). In o al, hese plo s come om
20 di e en coun ies in Eu ope and Asia (Appendix S1:
Figu e S1) and co e 19 b oad ege a ion ypes (2nd le el
o he ecological-physiognomic ypology o G assPlo ;
Biu un e al., 2019). The lowe ichness bounda y
(20) allowed o su icien ly p ecise SAD i s and enabled
us o assess he change in communi y pa ame e s along
g adien s o inc easing ichness and abundance (c . Ul ich
e al., 2010). Abundances o all species in a plo we e
assessed by he pe cen age co e ( ypically used in plan
SAD s udies a he han ac ual abundances) (Ande son
e al. 2012; Chia ucci e al., 1999). Co e da a a e o en
mo e s ongly co ela ed wi h plan biomass han wi h he
numbe o ame s, ha is, single shoo s (Chia ucci
e al., 1999). The e o e, co e -based SADs a e pa icula ly
e ec i e a quan i ying he dis ibu ion o plan species bio-
mass wi hin and ac oss ege a ion plo s.
Fo he analysis o spa ial SAD scaling, we selec ed
40 plo clus e s om he da a se s, ha is, g oups o plo s
om he o iginal da a se wi h iden ical ege a ion ype
ha con ained a leas 15 indi idual plo s (in o al 1550
plo s) (Ul ich e al., 2021). Fo each clus e , we s a ed
SAD i ing wi h a andomly chosen plo o a leas 20 spe-
cies and g adually added he co e alues o all o he
plo s in andom o de o ob ain a cumula i e plo
sequence (CPS), which also e lec s inc easing sample
a ea. This addi i e p ocess implies ha cumula i e co e
alues migh be la ge han 100. We no e ha hese CPSs
do no o m sequences o spa ially con inuous ege a ion
bu a e agg ega ions o discon inuous plo s. O cou se,
he SAD a he s a ing poin and he speci ic o de ing o
plo s du ing accumula ion migh in luence he in e ed
scaling beha io and inc ease he a iance in scaling pa -
e ns ac oss hese CPSs. Howe e , we did no a e age
alues o se e al uns o andom accumula ion wi hin
each plo se ies because such a e aging would a i icially
smoo h he spa ial scaling and bias he pa e n owa d
wha is p edic ed om sample heo y in homogeneous
en i onmen s. The high numbe o indi idual plo s
wi hin each CPS gua an eed ha he assessmen o
changes in SAD pa ame e s ac oss a CPS would no be
in luenced by he o de ing o plo combina ion.
Fo each indi idual plo and each accumula ion s ep
o he CPS, we i ed he Weibull dis ibu ion o he spe-
cies ank–ln-abundance dis ibu ion (Whi ake ep e-
sen a ion) (Whi ake , 1965) using ln- ans o med
ela i e co e alues acco ding o s anda d p ac ice. The
inal s ep o each CPS p o ides a ough es ima e o he
abundance dis ibu ion o he egional species pool o
ha clus e . The comple e da a se , including i ed
pa ame e s and momen s o he SAD dis ibu ions, is
con ained in Ul ich e al. (2021).
En i onmen al a iables
The G assPlo da a se con ains a ange o en i onmen al
and geog aphical a iables known o be impo an d i e s
o plan di e si y and dis ibu ions; ce ain a iables a e
only a ailable o a subse o plo s. In his s udy, o all
plo s we used he geog aphical a iables la i ude, longi ude,
and ele a ion. Fo 1111 plo s, in o ma ion on mean soil
dep h, o 569 plo s in o ma ion on soil o ganic ma e con-
en (OMC), and o 338 plo s in o ma ion on soil C/N a io
was a ailable. Addi ionally, we e ie ed da a o a e age
annual empe a u e, annual p ecipi a ion, empe a u e
ange and p ecipi a ion a iabili y o all plo s om he
CHELSA clima e da abase (Ka ge e al., 2016). The com-
ple e geog aphical and en i onmen al aw da a o each
plo a e con ained in Ul ich e al. (2021).
Da a analysis
P io wo k on he a ia ion in SAD shape be ween si es
la gely elied on compa ing he i s o di e en s anda d
models. Howe e , eliable model compa isons need la ge
sample sizes, a leas on he o de o 20 species (Ul ich
e al., 2010; Wilson, 1993). The e o e, he e we ake a wo-
p onged app oach. Fi s , we ely on model-independen
momen s o SADs: he a iance (σ
2
, second momen ) as a
4o 16 ULRICH ET AL.
measu e o he ange in plan co e , he skewness
(γ, hi d momen ) as a measu e o an excess o ela i ely
a e o abundan species, and he ku osis (δ, ou h
momen ) as a quan i ica ion o he p opo ion o species
wi h ela i ely in e media e co e . Addi ionally, we i ed
he wo-pa ame e Weibull dis ibu ion o he obse ed
plan co e da a. Recen ly, Ul ich e al. (2018,2020) dem-
ons a ed ha his dis ibu ion is su icien ly lexible o
mimic a wide ange o obse ed SAD shapes. The model
allows o a con inuous acing o he changes in he wo
Weibull pa ame e alues (scale and shape) in o de o
assess he scaling p ope ies o obse ed SADs and o
ela e hese o en i onmen al co ela es.
Fi ing he Weibull model o empi ical SADs
The wo-pa ame e o m o he Weibull dis ibu ion has
he p obabili y densi y unc ion (PDF)
px>0;φ;λðÞ¼
φ
λ
x
λ

φ1ex
λ
ðÞ
φ
ð1Þ
whe e φis he shape and λ he scale pa ame e . The
Weibull shape pa ame e (φ) dec eases wi h inc easing
skewness o he dis ibu ion, and he scale pa ame e (λ)
inc eases wi h he obse ed ange in abundance (Ul ich
e al., 2018). Consequen ly, λand σ
2
a e posi i ely co e-
la ed (p esen da a: =0.73). The φ/λquo ien is mo e
closely ela ed o he empi ical a iance o he SAD by a
powe unc ion (c . Appendix S1: Figu e S2 o he p e-
sen da a se ). Shape pa ame e s a ound φ=2 mimic log-
no mal dis ibu ions, whe eas φ=1 e e s app oxima ely
o log-se ies dis ibu ions. When applied o species abun-
dances, he andom a ia e xmus con ain log-
ans o med abundances calcula ed o all species (S).
The Fo an code used o asymp o ic o dina y leas -
squa es i ing o he Weibull dis ibu ion (using a
pa e n-seeking algo i hm) has al eady been p esen ed in
Ul ich e al. (2018) and is eely a ailable om he
co esponding au ho upon eques . As a measu e o
goodness o i we used he a e age sum o leas squa es:
i ¼1
SPS
1ln piln wj

2,whe e ln p
i
and ln w
j
deno e he
ln- ans o med obse ed and Weibull i ed ela i e abun-
dances, espec i ely. Ul ich e al. (2018) compa ed di e -
en ypes o SAD om small o in e media e sized
Japanese o es ee communi ies (<100 species) and
epo ed i alues <0.05 as being excellen , whe eas i
alues >0.3 we e conside ed poo . Figu e 1con ains six
ypical examples om he p esen da a se o excellen o
FIGURE 1 Six example i s o he Weibull dis ibu ion o g assland communi y species abundance dis ibu ions (SADs), wi h di e en
alues o he goodness-o - i measu e. Goodness o i was calcula ed as he a e age sum o leas squa es: i ¼1
SPS
1ln piln wj

2, whe e ln
p
i
and ln w
j
deno e ln- ans o med obse ed and Weibull i ed ela i e pe cen age co e alues. Le e s (e.g., RO_AP) e e o CPS plo code
(Appendix S1: Table S5) (Ul ich e al., 2021)
ECOLOGY 5o 16

poo i s and demons a es ha i alues <0.3 can s ill be
conside ed e y good. Weibull model i s o he SADs o
each plo , including obse ed and es ima ed co e alues
o each species oge he wi h espec i e SDs o he es i-
ma es, a e con ained in Ul ich e al. (2021).
S a is ical analysis
Fo each o he indi idual plo s and each accumula ion
s ep o he CPSs, we calcula ed he skewness (γ) and he
ku osis (δ) o he SAD. We no e ha a symme ic logno -
mal dis ibu ion has a skewness o γ=0, while a nega i e
skewness indica es an excess o ela i ely a e species
(no e ha his ega ds log-abundance dis ibu ions: dis i-
bu ions o aw abundances wi h an excess o a e species
a e igh skewed) (e.g., Šizling e al., 2009). A s anda d
logno mal dis ibu ion is cha ac e ized by a ku osis o
δ=3. Highe ku osis alues ma k an excess o species
wi h in e media e abundances. Addi ionally, we calcu-
la ed he p opo ional β-di e si y o each cumula i e plo
se ies as β¼1α=γ, whe e αis he a e age local (plo )
and γ he o al species ichness o he CPS.
G aphical compa isons o λ- alues o single plo s
(Figu e 2a)andCPS(Figu e3a) agains o al co e
indica ed he exis ence o ou clea ly sepa a ed g oups
o SADs. We op imized classi ica ion using k-means
clus e ing applied o he quo ien o λ/ln(co e alues)
and i ed o dina y loga i hmic leas -squa es eg es-
sions o each g oup indi idually. Disc iminan analysis
se ed o ela e hese g oups o en i onmen al a i-
ables. Nes ed linea mixed-e ec s modeling (GLM) and
pa ame ic ANOVA wi h pos hoc Tukey es s we e
used o ela e he SAD pa ame e s o communi y spe-
cies ichness, o al ln-abundance, and en i onmen al
a iables. To in e any nonlinea pa e ns wi h ega d
o changes in he a ious SAD momen s and pa ame-
e s (γ,δ,φ,λ) wi h spa ial scale, we included he
squa ed ze o cen e ed ln-co e e m (sepa a ely calcu-
la ed o each o he 40 CPSs in o he analysis). Because
he spa ial ex en o he s udy a ea, ha is, he a ea
encompassed by he plo s wi hin he CPSs, migh in lu-
ence he esul s we also added he a e age pai wise
plo dis ance wi hin each CPS as a co a ia e. We es i-
ma ed he impac s o p edic o a iables om pa ial η2
alues,
FIGURE 2 Plo s o (a, c) Weibull scale pa ame e λand (b, d) shape pa ame e φagains (a, b) o al plan co e alues and (c, d)
species ichness o all 1725 single plo s e u ned ou clea ly de ined g oups o plo s (A, B, C, D) wi h espec o he in e cep alue o λ.
G oups we e less clea ly de ined wi h espec o φ. Communi y membe ship o hese ou g oups is p o ided in Ul ich e al. (2021).
Reg ession lines e e o (a, b) o dina y leas -squa es loga i hmic and (c, d) linea eg essions. B oken lines in (a) indica e bounda ies o
g oup membe ship
6o 16 ULRICH ET AL.
pa ial η2¼SSe ec
SSe ec þSSe o ,
whe e SS deno es he sum o squa es. Calcula ions
we e unde aken using S a is ica 12.0.
We also applied polynomial o dina y linea segmen ed
leas -squa es eg ession o he SAD pa ame e alues e sus
ln-co e o each o he 40 CPSs, as implemen ed in
SigmaPlo 14. A signi ican b eakpoin indica es a nonlinea
scaling o he espec i e pa ame e s along he o al co e
alue (and he e o e a ea) axis o a gi en CPS. As he spa ial
dis ibu ion o he analyzed G assPlo plo s was clus e ed
and absolu e spa ial dis ances migh be impo an , we used
eigen ec o mapping and added he dominan eigen ec o
(EV1) o he Euclidean plo dis ance ma ix o he GLM
models as a co a ia e.
RESULTS
Goodness o i
The majo i y o he g assland plan SADs we e e y well
i ed by he Weibull dis ibu ion ( i s in Ul ich
e al., 2021, Figu e 1; Appendix S1: Figu e S3). Among
he 1725 indi idual plo s, 400 (23.2%) had i alues <0.1,
indica ing excellen o e y good i s (e.g., Figu e 1a),
1135 plo s (65.8%) had i alues <0.3, indica ing e y
good i s (e.g., Figu es 1b, c), and only 196 (11.4%) we e
compa a i ely weakly i ed by he Weibull dis ibu ion
( i >0.75, e.g., Figu e 1e, ). Goodness o i di e ed sig-
ni ican ly be ween plo s (Appendix S1: Table S1). Species
ichness did no signi ican ly in luence goodness o i
(Appendix S1: Table S1).
Va iabili y in SAD pa ame e s be ween
SAD g oups
Wi h 868 indi idual plo s (50.3%) and 1263 CPS agg e-
ga ion s eps (81.5%), mos i ed SADs we e cha ac e -
ized by φ> 2.0, equi alen o logno mal- ype SADs.
Only 423 indi idual plo s (24.5%) and 47 o he CPS
agg ega ion s eps (3.0%) had φ<1.5, equi alen o a
log-se ies SAD. SAD skewness γdec eased wi h plo
abundance, indica ing an excess o a e species a
FIGURE 3 Plo s o (a, c) Weibull i scale pa ame e λand (b, d) shape pa ame e φagains (a, b) plan cumula i e co e and (c, d)
species ichness o all agg ega ion s eps o cumula i e plo se ies highligh he ou clea ly de ined g oups o plo s (A, B, C, D) wi h espec
o he in e cep alue o λ. G oups we e less clea ly de ined wi h espec o φ. Communi y membe ship o hese ou g oups is p o ided in
Ul ich e al. (2021). Reg ession lines e e o o dina y leas -squa es loga i hmic eg essions. B oken lines in (a) indica e bounda ies o g oup
membe ship
ECOLOGY 7o 16
highe o al co e alues (Appendix S1: Figu e S4c).
Ku osis δwas la gely independen o co e and ich-
ness (Appendix S1: Figu e S4d,h).
Plo s o φand λagains co e alues and species ich-
ness in combina ion wi h k-means clus e analysis
poin ed o ou dis inc g oups o g assland SADs di e -
en ia ed by he scaling o λwi h plan co e (Figu es 2a
and 3a; Appendix S1: Table S2). G oup di e en ia ion
was less ob ious wi h espec o φ(Figu es 2and 3;
Appendix S1: Table S2), al hough k-means clus e ing s ill
con i med >40.0% g oup membe ships (Figu es 2b,d
and 3b,d; Appendix S1: Table S2). The ou g oups did
no signi ican ly di e wi h espec o α-, β-, and
γ-di e si y o o local co e (Figu e 4a). One-way
ANOVA indica ed ha he e was a mode a e e ec o
ege a ion ype on g oup membe ship (pa ial
η2=0.08, p< 0.001). In pa icula , G oup B domina ed in
alpine, xe ic, ocky, and sandy d y g assland communi-
ies, while G oup C domina ed in meso-xe ic, mesic,
and Medi e anean g asslands, as well as in we lands
(Appendix S1: Figu e S3a).
Linea modeling de ec ed signi ican di e ences among
he ou SAD g oups wi h espec o he γand δo he SAD
dis ibu ion and he Weibull pa ame e alues (Table 1,
Figu e 4). G oups A and B SADs we e on a e age cha ac e -
ized by a sligh ly nega i e empi ical γ, indica ing an excess
o a e species (Figu e 4b), while he SADs o G oups C and
D we e signi ican ly igh skewed in acco dance wi h an
excess o abundan species (Figu e 4b). Fo all ou g oups,
δ anged be ween 2 and 3, wi h a dec ease owa d G oup D
(Figu e 4b). Weibull φwas lowes (<2.0) o G oup D com-
muni ies (Figu e 4b).
En i onmen al in luences
The clima ic a iables used he e, in addi ion o ele a-
ion and la i ude, did no signi ican ly in luence he
obse ed SAD shapes (Table 1; Appendix S1:
Figu e S5). φand λinc eased and γdec eased wi h soil
OMC (Appendix S1: Figu e S6e,g,h), while γinc eased
and λdec eased wi h soil C/N a io (Appendix S1:
Figu e S6i,l). Disc iminan analysis also did no de ec
any signi ican in luence o clima ic a iablesonSAD
g oup membe ship (Appendix S1: Table S3). Howe e ,
we ound a s ong indi ec in luence o soil cha ac e is-
ics on SAD g oup membe ship and he e o e on SAD
shape (Figu e 4c;AppendixS1:TableS3).G oupC
communi ies we e ela ed o deepe soils wi h
inc eased C/N a ios, while inc eased OMC was mos
common o G oup A communi ies (Figu e 4c). G oup
A communi ies domina ed a highe , and G oup D
communi ies a lowe , ele a ion (Figu e 4c).
Spa ial scaling o SAD pa ame e s
The Weibull pa ame e s inc eased wi h inc easing cumu-
la i e co e alues (equi alen o inc easing a ea) in a
FIGURE 4 (a) A e age alues o α-, β-, and γ-di e si y, and
a e age local co e alues (C
local
) o cumula i e plo sequences (CPS)
wi hin he ou species abundance dis ibu ion (SAD) g oups
(uppe case le e s) iden i ied in Figu e 2. The e we e no signi ican
di e ences be ween ypes. (b) A e age alues o skewness (γ),
ku osis (δ), shape (φ), and scale (λ) pa ame e s o single g assland
SADs, wi hin he ou g oups. All g oup compa isons signi ican ly
di e ed wi hin each pa ame e . (c) A e age soil dep h, soil o ganic
ma e con en (OMC), soil C/N a ios, and plo ele a ion wi hin he
ou g oups. Fo soil dep h, G oups B and C signi ican ly di e ed
om G oups A and B; o OMC G oup A signi ican ly di e ed
om B, C, and D; o C/N a ios C and D di e ed om A and B; and
o ele a ion A and D di e ed and bo h di e ed om B and C. E o
ba s deno e SEs. Signi icances a he wo-sided 1% e o le el be ween
g oups we e es ed wi h one-way ANOVA and pos hoc Tukey es s
8o 16 ULRICH ET AL.
TABLE 1 Gene al linea modeling de ec ed signi ican di e ences in empi ical species abundance dis ibu ion (SAD) skewness (γ) and
ku osis (δ), and Weibull shape (φ) and scale (λ) pa ame e s, be ween ou g oups o g assland plan communi ies (as de ined in Figu e 2)
and be ween ege a ion ypes
Va iable d
γδφλ
Pa ial η2βPa ial η2βPa ial η2βPa ial η2β
SAD g oup 3 0.29*** …0.04*** …0.36*** …0.94*** …
Vege a ion ype 18 0.03*** …0.05*** …0.02*** …0.04*** …
T
mean
1 0.02*** 0.24 0.01** 0.23 0.03*** 0.32 <0.01 0.01
T
ange
1 <0.01 0.05 0.01** 0.20 0.01** 0.13 0.01** 0.04
P
mean
1 <0.01 0.06 <0.01 0.00 <0.01 0.03 <0.01 0.00
P
seasonali y
1 0.02*** 0.28 0.01** 0.18 0.04*** 0.33 <0.01 0.02
EV1 1 <0.01 0.02 <0.01 0.03 <0.01 0.02 <0.01 0.02
S 1 <0.01 0.01 <0.01 0.02 <0.01 0.04 0.01** 0.02
ln C 1 0.04*** 0.20 <0.01 0.04 0.03*** 0.17 0.34*** 0.20
2
…0.39*** …0.10*** …0.44*** …0.95*** …
No e:T
mean
,P
mean
, annual mean empe a u e and p ecipi a ion; T
ange
, empe a u e ange; P
seasonali y
, p ecipi a ion seasonali y; ln C, ln- ans o med co e
alues; S, species ichness; and he dominan eigen ec o o plo spa ial dis ances (EV1) se ed as me ic co a ia es.
Vege a ion ype en e ed he model as a andom e ec . Pa ial η2- and β- alues a e shown.
Pa ame ic signi icances: **p< 0.01, ***p< 0.001. N=1719 o all ou models.
FIGURE 5 Plo s o he ela ionships be ween species abundance dis ibu ion (SAD) skewness (γ), ku osis (δ), Weibull i shape (φ),
and scale pa ame e s (λ), and ln- ans o med co e alues o ou ep esen a i e cumula i e plo se ies. Red eg ession lines show
signi ican (p< 0.001) and g ay lines nonsigni ican (p> 0.10) piecewise eg essions. The o al in (o) deno es a s ep change in scale alue.
Si e in o ma ion o each o he ou si es can be ound in Ul ich e al. (2021).
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SUPPORTING INFORMATION
Addi ional suppo ing in o ma ion may be ound in he
online e sion o he a icle a he publishe ’s websi e.
How o ci e his a icle: Ul ich, We ne , Thomas
J. Ma hews, Idoia Biu un, Juan An onio Campos,
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16 o 16 ULRICH ET AL.