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SUPPLEMENTARY MATERIAL
Thermal landscape change as a driver of ectotherm responses to
plant invasions
Raquel A. Garcia1* and Susana Clusella-Trullas1
Proceedings of the Royal Society B, DOI
10.1098/rspb.2019.1020
1 Centre for Invasion Biology, Department of Botany and Zoology,
Stellenbosch University, Private Bag X1, Matieland 7602, South
Africa
* Corresponding author, [email protected]
Supplementary Material for the literature review 2
Supplementary Text S1 | Methods for the literature review 2
Table S1 | Terms used for the literature search 4
Supplementary Text S2 | List of reviewed studies 5
Table S2 | Examples of variables used for quantifying the
thermal effects of alien plants on ectotherms
8
Figure S1 | Cumulative number of studies over time 10
Figure S2 | Native ectotherms covered in the review 11
Figure S3 | Invasive alien plants covered in the review 12
Figure S4 | Geographical coverage of the review 12
Supplementary material for the case study 13
Supplementary Text S3 | Methods for the case study 13
Figure S5 | The three sites studied along a gradient of plant
invasion 14
Figure S6 | Operative environmental temperature across the day
along a gradient of plant invasion
18
Figure S7 | Availability of optimal micro-sites across time
along a gradient of plant invasion
18
Table S3 | Indices of thermal quality along a gradient of plant
invasion 19
Table S4 | Indices of thermoregulation accuracy along a gradient
of plant invasion 20
Additional references 21
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Supplementarymaterialfortheliteraturereview
Supplementary Text 1: Methods for the literature review
We searched the ISI Web of Knowledge on 8 March 2019 for studies
addressing the chain of effects
from the thermal changes in invaded areas to the responses of
ectotherm individuals, populations or
communities. Our search targeted studies assessing the
alteration of micro-site temperatures in
areas of native vegetation invaded by alien plants (hereafter
"invaded areas"), relative to areas of
native vegetation only ("native areas"), and the effects on
reptiles, amphibians, insects or arachnids.
Using a combination of search terms for non-native plants,
thermal effects and native ectotherms
(Table S1), we retrieved articles, reviews and book chapters
from the Web of Science Core Collection
from 1970 to early 2019 and screened relevant studies for
additional references. Studies were
considered relevant when they presented quantitative comparisons
for the thermal landscape stage
of the chain of effects and at least one of the ectotherm
individual, population and community
response stages.
We considered comparisons between invaded and native sites or
between invaded and restored
sites. As invaded sites we included only those that had native
vegetation but had been invaded by
alien plants, thus excluding areas intentionally planted with
alien species, such as gardens,
plantations, cultivated or pasture fields and barrier or
movement corridors, whether actively
managed or very recently abandoned. Both observational and
experimental studies were
considered. We included native organisms with full or partial
terrestrial life-cycles and excluded
benthic macroinvertebrates. We included studies testing
non-thermal mechanisms of response only
if they measured habitat temperature as an alternative
mechanism. Recorded impacts thus often
extended to changes in other abiotic factors such as light, soil
moisture and humidity, as well as
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changes in resource availability and predation risk, but our
focus was on thermal landscape changes
and their effects on native ectothermic organisms, populations
or communities.
When studies performed multiple comparisons, such as for
different native ectotherms, invasive or
native plant species, invasion levels, sites or experimental
venues, we recorded separate entries for
each comparison. Most comparisons reported results for several
variables pertaining to each stage
of the chain of effects addressed (Table S2). For example, a
given comparison could describe the
thermal landscape stage using two variables, mean habitat
temperature and range of habitat
temperatures. When studies presented abundance or species
diversity results at different taxonomic
levels (for example, across a Class as well as separately for
each Order), we reported the lowest level
presented, down to the Family level. For species diversity, we
reported results based on species
diversity estimators, whenever available, rather than raw
numbers of species.
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Table S1 | Terms used for the literature search on the thermal
effects of invasive alien plants on native
ectotherms.
Issue Search terms
Invasive plants (((invas* OR alien* OR non$nativ* OR exotic* OR
introduced OR non$indigenous OR naturali?ed) NEAR/3 (plant* OR
vegetat* OR tree* OR shrub* OR grass* OR forest* OR forb* OR herb*
OR vine* OR *weed* OR reed*)) OR (invaded NEAR/1 (habitat* OR site*
OR plot*))) AND
Thermal effect mechanism
(shading OR shade* OR thermal* OR temperature* OR climat* OR
warm* OR cold* OR micro$climate* OR thermo$regulat* OR bask*)
AND
Reptiles ((reptil* OR squamata OR snake* OR python* OR boa OR
boas OR cobra* OR mamba* OR viper* OR adder* OR colubrid* OR
elapid* OR lizard* OR gecko* OR skink* OR chameleon * OR agama* OR
"monitor lizard*" OR lacertid* OR amphisbaenid* OR cordylid* OR
testudine* OR chenolian* OR turtle* OR tortoise* OR terrapin* OR
crocodylia OR crocodil*) OR
Amphibians (amphibian* OR frog* OR anura* OR tadpole*) OR
Insects (insect* OR *flies OR *fly OR mosquito* OR gnat* OR *lice
OR *beetle* OR cricket* or *hopper*
OR cockroach* OR *bug* OR cicada* OR aphid* OR bristletail* OR
flea OR fleas OR moth* OR ant OR ants OR bee OR bees OR wasp* OR
stylopids OR lacewing* OR thrip* OR termite* OR mantid* OR
web$spinner* OR earwig* OR antlion* OR rock$crawler* OR katydid* OR
walkingstick* OR zorapteran* OR silverfish OR locust* OR
bristletail* OR mantis* OR gladiator* OR heelwalker* OR
mantophasmid* OR firebrat* OR Archaeognatha OR Blattodea OR
Coleoptera OR Dermaptera OR Diptera OR Embioptera OR
Grylloblattodea OR Hemiptera OR Hymenoptera OR Lepidoptera OR
Mantodea OR Mantophasmatodea OR Mecoptera OR Megaloptera OR
Neuroptera OR Odonata OR Orthoptera OR Phasmida OR Plecoptera OR
Psocodea OR Raphidioptera OR Siphonaptera OR Strepsiptera OR
Thysanoptera OR Trichoptera OR Zoraptera OR Zygentoma) OR
Arachnids (Arachnida OR Amblypygi OR Araneae OR Astigmata OR
Holothyrida OR Ixodida OR Mesostigmata OR Opilioacarida OR
Opiliones OR Palpigradi OR Prostigmata OR Pseudoscorpiones OR
Ricinulei OR Sarcoptiformes OR Schizomida OR Scorpiones OR
Solifugae OR Trombidiformes OR Uropygi OR *spider* OR *scorpion* OR
mite* OR *tick* OR harvestmen OR harverster* OR solifuge* OR
vinegar$on*))
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Supplementary Text 2: List of reviewed studies
Abom R, Vogler W, Schwarzkopf L. 2015 Mechanisms of the impact
of a weed (grader grass, Themeda quadrivalvis) on reptile
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Block C, Stellatelli OA, García GO, Vega LE, Isacch JP. 2013
Factors affecting the thermal behavior of the sand lizard Liolaemus
wiegmannii in natural and modified grasslands of temperate coastal
dunes from Argentina. J. Therm. Biol. 38, 560–569.
(doi:10.1016/j.jtherbio.2013.09.009)
Bolton RM, Brooks RJ. 2010 Impact of the Seasonal Invasion of
Phragmites australis (Common Reed) on Turtle Reproductive Success.
Chelonian Conserv. Biol. 9, 238–243. (doi:10.2744/CCB-0793.1)
Brown C, Blossey B, Maerz J, Joule S. 2006 Invasive Plant and
Experimental Venue Affect Tadpole Performance. Biol. Invasions 8,
327–338. (doi:10.1007/s10530-004-8244-x)
Carter ET, Eads BC, Ravesi MJ, Kingsbury BA. 2015 Exotic
invasive plants alter thermal regimes: implications for management
using a case study of a native ectotherm. Funct. Ecol. 29, 683–693.
(doi:10.1111/1365-2435.12374)
Carter ET, Ravesi MJ, Eads BC, Kingsbury BA. 2017 Invasive plant
management creates ecological traps for snakes. Biol. Invasions 19,
443–453. (doi:10.1007/s10530-016-1289-9)
Civitello DJ, Flory SL, Clay K. 2008 Exotic Grass Invasion
Reduces Survival of Amblyomma americanum and Dermacentor variabilis
Ticks (Acari: Ixodidae) . J. Med. Entomol. 45, 867–872.
(doi:10.1093/jmedent/45.5.867)
Cohen JS, Maerz JC, Blossey B. 2011 Traits, not origin, explain
impacts of plants on larval amphibians. Ecol. Appl. 22, 218–228.
(doi:10.1890/11-0078.1)
Cook CE, McCluskey AM, Chambers RM. 2018 Impacts of Invasive
Phragmites australis on Diamondback Terrapin Nesting in Chesapeake
Bay. Estuaries and Coasts 41, 966–973.
(doi:10.1007/s12237-017-0325-z)
Cook RW, Talley TS. 2014 The invertebrate communities associated
with a Chrysanthemum coronarium-invaded coastal sage scrub area in
Southern California. Biol. Invasions 16, 365–380.
(doi:10.1007/s10530-013-0526-8)
DeVore JL, Maerz JC. 2014. Grass invasion increases top-down
pressure on an amphibian via structurally mediated effects on an
intraguild predator. Ecology 95, 1724–1730.
(doi:10.1890/13-1715.1)
Downes S, Hoefer A-M. 2007 An experimental study of the effects
of weed invasion on lizard phenotypes. Oecologia 153, 775–785.
(doi:10.1007/s00442-007-0775-2)
Earl JE, Castello PO, Cohagen KE, Semlitsch RD. 2014 Effects of
subsidy quality on reciprocal subsidies: how leaf litter species
changes frog biomass export. Oecologia 175, 209–218.
(doi:10.1007/s00442-013-2870-x)
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Filazzola A, Westphal M, Powers M, Liczner AR, Woollett DA
(Smith), Johnson B, Lortie CJ. 2017 Non-trophic interactions in
deserts: Facilitation, interference, and an endangered lizard
species. Basic Appl. Ecol. 20, 51–61.
(doi:10.1016/j.baae.2017.01.002)
Hacking J, Abom R, Schwarzkopf L. 2014 Why do lizards avoid
weeds? Biol. Invasions 16, 935–947.
(doi:10.1007/s10530-013-0551-7)
Kapust H, McAllister K, Hayes M. 2012 Oregon spotted frog (Rana
pretiosa) response to enhancement of oviposition habitat degraded
by invasive reed canary grass (Phalaris arundinacea). Herpetol.
Conserv. Biol. 7, 358–366.
Leslie AJ, Spotila JR. 2001 Alien plant threatens Nile crocodile
(Crocodylus niloticus) breeding in Lake St. Lucia, South Africa.
Biol. Conserv. 98, 347–355. (doi:10.1016/S0006-3207(00)00177-4)
Magoba RN, Samways MJ. 2010 Recovery of benthic
macroinvertebrate and adult dragonfly assemblages in response to
large scale removal of riparian invasive alien trees. J. Insect
Conserv. 14, 627–636. (doi:10.1007/s10841-010-9291-5)
Nelson SM, Wydoski R. 2008 Riparian Butterfly (Papilionoidea and
Hesperioidea) Assemblages Associated with Tamarix-Dominated, Native
Vegetation–Dominated, and Tamarix Removal Sites along the Arkansas
River, Colorado, U.S.A. Restor. Ecol. 16, 168–179.
(doi:10.1111/j.1526-100X.2007.00358.x)
Nguyen KQ, Cuneo P, Cunningham SA, Krix DW, Leigh A, Murray BR.
2016 Ecological effects of increasing time since invasion by the
exotic African olive (Olea europaea ssp. cuspidata) on leaf-litter
invertebrate assemblages. Biol. Invasions 18, 1689–1699.
(doi:10.1007/s10530-016-1111-8)
Marshall JM, Buckley DS. 2009 Influence of Microstegium vimineum
Presence on Insect Abundance in Hardwood Forests. Southeast. Nat.
8, 515–526. (doi:10.1656/058.008.0312)
Pehle A, Schirmel J. 2015 Moss invasion in a dune ecosystem
influences ground-dwelling arthropod community structure and
reduces soil biological activity. Biol. Invasions 17, 3467–3477.
(doi:10.1007/s10530-015-0971-7)
Racelis AE, Davey RB, Goolsby JA, de León AAP, Varner K, Duhaime
R. 2012 Facilitative Ecological Interactions Between Invasive
Species: Arundo donax Stands as Favorable Habitat for Cattle Ticks
(Acari: Ixodidae) Along the U.S.–Mexico Border. J. Med. Entomol.
49, 410–417. (doi:10.1603/ME11104)
Rogalski MA, Skelly DK. 2012 Positive Effects of Nonnative
Invasive Phragmites australis on Larval Bullfrogs. PLoS One 7, 1–8.
(doi:10.1371/journal.pone.0044420)
Schirmel J, Buchholz S. 2013 Invasive moss alters patterns in
life-history traits and functional diversity of spiders and
carabids. Biol. Invasions 15, 1089–1100.
(doi:10.1007/s10530-012-0352-4)
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Schirmel J, Timler L, Buchholz S. 2011 Impact of the invasive
moss Campylopus introflexus on carabid beetles (Coleoptera:
Carabidae) and spiders (Araneae) in acidic coastal dunes at the
southern Baltic Sea. Biol. Invasions 13, 605–620.
(doi:10.1007/s10530-010-9852-2)
Schmid JL, Addison DS, Donnelly MA, Shirley MA, Wibbels T. 2008
The Effect of Australian Pine (Casuarina equisetifolia) Removal on
Loggerhead Sea Turtle (Caretta caretta) Incubation Temperatures on
Keewaydin Island, Florida. J. Coast. Res. Special Is, 214–220.
(doi:10.2112/SI55-001.1)
Schreuder E, Clusella-Trullas S. 2017 Exotic trees modify the
thermal landscape and food resources for lizard communities.
Oecologia 182, 1213–1225. (doi:10.1007/s00442-016-3726-y)
Somaweera R, Wijayathilaka N, Bowatte G, Meegaskumbura M. 2015
Conservation in a changing landscape: habitat occupancy of the
critically endangered Tennent’s leaf-nosed lizard (Ceratophora
tennentii) in Sri Lanka. J. Nat. Hist. 49, 31–32.
(doi:10.1080/00222933.2015.1006280)
Stellatelli OA, Vega LE, Block C, Cruz FB. 2013 Effects on the
thermoregulatory efficiency of two native lizards as a consequence
of the habitat modification by the introduction of the exotic tree
Acacia longifolia. J. Therm. Biol. 38, 135–142.
(doi:10.1016/j.jtherbio.2012.12.005)
Stellatelli OA, Vega LE, Block C, Cruz FB. 2013 Effects of Tree
Invasion on the Habitat Use of Sand Lizards. Herpetologica 69,
455–465. (doi:10.1655/HERPETOLOGICA-D-12-00033)
Stellatelli OA, Block C, Vega LE, Cruz FB. 2014 Responses of two
sympatric sand lizards to exotic forestations in the coastal dunes
of Argentina: Some implications for conservation. Wildl. Res. 41,
480–489. (doi:10.1071/WR14078)
Trigos-Peral G, Casacci LP, ŚlipiŃski P, GrzeŚ IM, MoroŃ D,
Babik H, Witek M. 2018 Ant communities and Solidago plant invasion:
Environmental properties and food sources. Entomol. Sci. 21,
270–278. (doi:10.1111/ens.12304)
Trimble MJ, van Aarde RJ. 2014 Amphibian and reptile communities
and functional groups over a land-use gradient in a coastal
tropical forest landscape of high richness and endemicity. Anim.
Conserv. 17, 441–453. (doi:10.1111/acv.12111)
Valentine LE, Roberts B, Schwarzkopf L. 2007 Mechanisms driving
avoidance of non-native plants by lizards. J. Appl. Ecol. 44,
228–237. (doi:10.1111/j.1365-2664.2006.01244.x)
Watling JI, Hickman CR, Orrock JL. 2011 Invasive shrub alters
native forest amphibian communities. Biol. Conserv. 144, 2597–2601.
(doi:10.1016/j.biocon.2011.07.005)
Williams SC, Ward JS. 2010 Effects of Japanese Barberry
(Ranunculales: Berberidaceae) Removal and Resulting Microclimatic
Changes on Ixodes scapularis (Acari: Ixodidae) Abundances in
Connecticut, Usa. Environ. Entomol. 39, 1911–1921.
(doi:10.1603/EN10131)
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Table S2 | Examples of variables used for quantifying the
thermal effects of alien plants on native ectotherms.
For each stage along the chain of effects from altered thermal
landscapes to the responses of ectotherms at
the individual, population and community levels, the table
provides examples of suggested variables and
examples of the reviewed studies that used those variables.
Stage Variables Examples
TERMAL LANDSCAPE
Composition
Temperature distribution statistics such as mean, maximum,
minimum and quantiles or other variables such as degree days
[30,31,88–91,39,40,48,55,60,65,70,87]
Availability of temperatures within optimal range or outside
critical limits for the species; thermal quality index de [79]
[29–31,40]
Landscape ecology metrics (patch matrix model using classes
based on species’ thermal preferences, or gradient model) [92]
Spatial configuration
Spatial autocorrelation measures (e.g. Moran I)
Landscape ecology metrics (patch matrix model using classes
based on species’ thermal preferences, or gradient model) [92]
INDIVIDUAL Micro-habitat use
Level of use of micro-habitats by individuals (time or
occurrence for individuals, eggs or nests, either in absolute terms
or relative to availability)
[39,45,48,62,63,88–90]
Thermoregulation
Thermoregulatory set-point [48]
Body temperature [40,48]
Thermoregulation accuracy or efficiency [e.g. db and E indices;
79] [40]
Time or distance travelled
Activity
Activity budgets, including time performing specific activities
such as basking or hiding in refuges
[28,48]
Body condition and growth
Body size or mass [48,53,58]
Growth or development rate [48,54,56,59]
Reproduction
Age at oviposition, percentage of gravid or egg-laying females
[48,57]
Reproductive output (e.g. metamorph, clutch or offspring weight
or size)
[48,58,59,93]
Reproductive success (e.g. metamorphosis or hatching rate,
offspring survival)
[48,57,93]
Incubation time [60]
Time to metamorphosis [58]
Hatchling sex ratio [61,62]
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Stage Variables Examples
Survival
Adult individual survival or mortality [55]
POPULATION Abundance
Number or density of individuals
[21,30,96,45,63,65,66,70,87,94,95]
COMMUNITY Species diversity
Number or density of species [30,63,66,70,87]
Species diversity estimators (e.g. Chao 1 and 2, Incidence
Coverage Estimator)
[30,66,91,97,98]
Community structure
Community composition [30,66,97,99]
Species turnover (e.g. Whittaker's species turnover)
Functional diversity (e.g. number of species in each functional
group, functional distance between species, functional range
covered by the community, functional dispersion, evenness)
[66,69]
Community thermal indices [e.g. 25,71,100]
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Fig. S1 | Cumulative number of studies over time addressing the
thermal effects of invasive alien plants on
native ectotherms. Studies covering more than one taxonomic
group are counted more than once.
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Fig. S2 | Native ectotherms covered in the review of thermal
effects of invasive alien plants on native
ectotherms. For each taxonomic entity of reptiles, amphibians,
insects and arachnids, the bars show the
numbers of comparisons considered to assess the effect of alien
plants on the given native entity. Taxonomic
entities ranged from Species (e.g. Liolaemus wiegmannii) to
Family (e.g. Formicidae), Order (e.g. Coleoptera)
and Class (e.g. Reptilia). Six studies sampled “invertebrates”,
but the majority of these fell in the Insecta and
Arachnida classes; they were thus included and classified as
“Insecta and Arachnida”.
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Fig. S3 | Invasive alien plants covered in the review of thermal
effects of invasive alien plants on native
ectotherms. For each alien plant species, the bars show the
numbers of comparisons considered to assess the
effects of the given alien plant on native ectotherms. The term
"Multiple" refers to comparisons where the
invaded sites in the comparison had more than one dominant
invasive alien species.
Fig. S4 | Geographical coverage of the review of thermal effects
of invasive alien plants on native ectotherms.
The barplot shows the numbers of studies on reptiles,
amphibians, insects and arachnids undertaken in each
continent.
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Supplementarymaterialforthecasestudy
Supplementary Text 3: Methods for the case study
Temperature data collection
Our study took place in the Joostenbergkloof reserve in the
Western Cape Province of South Africa (-
33°45'45'', 18°46'11''), an area of native renosterveld habitat
with patches invaded by Acacia saligna
that was recently set aside for conservation. We used simplified
physical models of the Cape skink
(Trachylepis capensis; Scincidae), fitted with temperature
sensors inside to sample operative
environmental temperatures in our study area. The models were
made of hollow copper pipes, 100
mm long to match the snout-vent length of T. capensis [maximum
SVL of 117 mm; 101], and painted
with a grey colour with a reflectance of 17% falling within the
range of skin reflectances of diurnal
lizard families in the region [5.3–17.2%; 30,102]. An iButton
(DS1921G-F5#/MAXIM Thermochron, -
40°C to + 85°C, accuracy of 1°C) was secured inside the
air-filled cylinder with mesh, and the cylinder
was sealed with corks on both ends.
We selected a native area of renosterveld bush ('native area')
and two areas invaded by A. saligna
along a gradient of invasion level, differing in the age and
density of alien trees: an area sparsely
invaded by young acacias ('mildly invaded' area) and an area
densely invaded by older acacias
('highly invaded' area). In each area we placed 36 models in a
matrix of 3 x 12, spaced 20cm from
each other. The iButtons were programmed to log temperatures
every two minutes for two days
and 20 hours, from 23 April 2017 at 12:00. The aim was to
capture small-scale spatial thermal
heterogeneity relevant to the organism's body size and home
range, and the thermal fluctuations
experienced throughout the animal's daily active period. Given
the large number of temperature
loggers needed for the simultaneous measurement of three
landscapes at fine spatial and temporal
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resolution, the areas sampled were relatively small. To obtain
larger areas, in a post-sampling data
processing step, we thus replicated sub-sections of each sampled
area and combined them in space
to obtain a larger squared area of three metre side. To do so,
for each type of landscape (native,
mildly invaded and highly invaded) we replicated the 12 x 3
matrix three times. We divided each of
the replicates into four sections of 3 x 3 and combined the
sections in different arrangements to
create a new 12 x 3 matrix. We then merged the three new
matrices with the original matrix,
yielding a new landscape of 12 x 12 models (approximately 3 x 3
metres). We are thus assuming that
the micro-site variability within the initial matrix is
representative of the larger landscape. This is an
acceptable assumption given the similarity in levels of thermal
heterogeneity that have been
reported across the micro-, local and landscape levels [77]. The
initial matrix is also considered
representative of the lizard's home range given the species'
small size. We also measured ambient
temperature with an iButton inside an open, perforated white
container that was suspended one
metre above the ground.
(a)
(b)
(c)
Fig. S5 | The three sites studied along a gradient of invasion.
(a) native vegetation ('native landscape'), (b)
sparse invasion by young acacias ('mildly invaded landscape'),
and (d) dense invasion by older acacias ('highly
invaded landscape').
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Temperature data analysis
For the temperature data analysis, we considered the operative
temperature data for two full days
from 00:00 on 24 April 2017 to 23:59 on 25 April 2017. We
computed a suite of variables to describe
the composition and spatial configuration of the thermal
landscapes in the native, mildly invaded
and highly invaded areas. First, as summary statistics we
computed the quantiles of the operative
temperature distribution for the entire activity period of the
lizard (7:00 to 19:00) or for three
periods of the day: morning (7:00–11:00), midday (11:00–15:00),
and afternoon (15:00–19:00). For
comparison, we computed the same variables for air
temperature.
Second, we computed thermal composition variables relative to
the Trachylepis capensis' optimum
temperature [Tpref of 34.5°C; 80] and critical thermal maximum
[CTmax of 44.9°C; 80]. These
variables included the time during which there was at least one
micro-site available with operative
temperature within the organism's Tpref range [34–35°C; 80] or
above CTmax, and the percentage
of micro-sites with optimal temperature or temperatures above
the organism's maximum limit at a
given time. We also computed the average of the absolute
deviations of operative temperatures
from Tpref, known as the index of habitat thermal quality [de;
79].
Third, we characterised the spatial configuration of the thermal
landscapes by computing, for each
time period, metrics from landscape ecology. Our aim was to
assess the extent to which optimal
temperatures were aggregated or dispersed in space. We thus
classified the available Te into classes
according to the organism's thermal preferences and limits, and
then calculated the indices of
percentage of like adjacencies, aggregation and patch cohesion
[92] for the class of operative
temperatures falling within the Tpref range.
Individual-based modelling
We used a spatially-explicit individual-based model to simulate
the thermoregulatory behaviour of
Trachylepis capensis individuals in two-dimensional landscapes
across time, based on the methods
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developed by Sears and colleagues [42,103]. We wrote the model
using the R language [104] and
applied it to the three landscapes we created with the operative
temperature measurements in
native, mildly invaded and highly invaded areas (see above).
At the start time (ti), an individual with body temperature
corresponding to the mean Tpref of the
organism was placed in a random initial position on the grid.
Every two minutes (the resolution of
our operative temperature data), the individual sampled the
landscape with the aim of selecting the
cell with operative temperature that would result in body
temperature closest to Tpref after a
period of two minutes. If the body temperature in the current
location was already within the Tpref
range, the animal remained in the same location with a
probability of 0.9. Otherwise, the animal
moved with a probability of 0.9. When moving, the animal
assessed a set of new locations, randomly
chosen within a buffer of three grid cells around the current
cell (60 cm, equivalent to a fourth of the
maximum distance possible). The number of cells sampled every
two minutes was set to 20% of the
number of available cells within the buffer. In each new
location, body temperature at time ti+1 was
given by:
where t is the time the animal is exposed to operative
temperature Tei (2 minutes) and τ is the
thermal time constant of the lizard. In the absence of
information on the study species' heating and
cooling rate, we used published values for Trachylepis
quinquetaeniata [105], a congeneric species
of similar body size [101]. The heating and cooling rates were
323 and 358 seconds, respectively
[106]. The lizard chose the location that resulted in the body
temperature closest to Tpref. If more
than one location offered optimal temperatures, the lizard chose
the nearest location. Once the new
location was chosen, the same process was repeated in time ti+1
using the operative temperature of
the new location at time ti+1 and the body temperature of the
lizard at time ti. For each landscape,
we ran 100 simulations, varying the initial random location,
across the entire operative temperature
time series (two days and 20 hours).
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For comparison with a null model, we also performed 100
simulations for a thermoconforming
lizard. We followed a similar approach as above, with the
exception that new locations were chosen
randomly within the buffer area irrespective of the body
temperature offered. For both
thermoregulating and thermoconforming lizards, we computed the
thermal quality and
thermoregulation accuracy indices [79], as well as the total
distance moved by the lizard and the
time during which the individual's body temperature was within
the Tpref range.
To assess the effect of lizard motility on the individual's
response to plant invasions, we performed
two additional sets of simulations: one set for a less motile
lizard, moving within a buffer of one grid
cell only, to represent a sit-and wait foraging strategy; and
another set for a more motile lizard,
moving within the entire area, to represent a wide-foraging
strategy.
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18
(a)
(b)
(c)
Fig. S6 | Operative environmental temperature across the day
along a gradient of plant invasion. For native
(a), mildly invaded (b) and highly invaded (c) landscapes, the
bloxplots show the distribution of operative
temperature measurements across the landscape at each hour of
the day over the study period, in relation to
Trachylepis capensis’ preferred body temperature (Tpref) and
critical thermal maximum (CTmax). The medians
(solid circles), interquartile ranges (solid vertical lines),
and whiskers extending 1.5 times the interquartile
range from the nearer quartile (dotted lines) are shown. The
horizontal white lines delimit the activity period
for the species.
(a)
(b)
(c)
Fig. S7 | Availability of optimal micro-sites across time along
a gradient of plant invasion. For native (a), mildly
invaded (b) and highly invaded (c) landscapes, the bloxplots
show the distribution of the percentage of sites
across the landscape with operative temperature measurements
within the Trachylepis capensis' preferred
body temperature range. For each time period, the median (solid
circles), 25th and 75th quantiles (solid lines)
and whiskers extending 1.5 times the interquartile range from
the nearer quartile (dotted lines) are shown.
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19
Table S3 | Indices of thermal quality along a gradient of plant
invasion. Indices are shown separately for the morning (7h–11h),
midday (11h–15h) and afternoon periods
(15h–19h). Thermal landscape composition metrics are: the
median, 25% and 75% quantiles of air temperature (Ta) and operative
environmental temperature (Te); the
percentage of sites with Te within the Tpref range or above
CTmax of T. capensis; the length of time when at least one
micro-site has Te within the Tpref range or above
CTmax; and the habitat thermal quality index (de), with high
values indicating poor match between Te and Tpref [79]. Thermal
landscape spatial configuration metrics are
three patch-matrix metrics where higher values correspond to
landscapes that are more clumped in space. We provide the median
for each index, with the numbers in
brackets indicating the interquartile range.
Index Morning Midday Afternoon Native Mildly invaded Highly
invaded Native Mildly invaded Highly invaded Native Mildly invaded
Highly invaded
Thermal landscape change: Te composition Median Ta 23.00 22.50
23.50 35.50 38.50 39.00 30.50 30.00 35.00
25% quantile Ta 18.50 18.00 18.00 33.00 36.50 36.50 26.50 25.00
25.50 75% quantile Ta 30.00 31.00 32.50 37.00 39.50 41.00 33.00
34.00 38.00
Median Te 19.37 18.93 19.43 41 46.35 42.71 30.87 34.33 29.96 25%
quantile Te 17.5 17 17.5 31.00 35.50 34.00 27.50 30 28.50 75%
quantile Te 26.25 20.5 21.25 54.00 58.5 50.50 36.50 40.00 31.50
% sites Tpref 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 2.78 (2.78)
0.00 (0.00) 0.00 (0.00) 0.00 (2.78) 0.00 (2.78) 0.00 (0.00) % sites
CTmax 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 30.56 (13.89) 58.33
(27.08) 27.78 (25) 0.00 (0.00) 0.00 (36.11) 0.00 (0.00) % time
Tpref 15.47 21.22 17.63 59.09 18.79 20.91 45.28 33.06 22.22
% time CTmax 3.24 10.79 1.44 99.39 100.00 98.79 24.17 39.72
11.94 de 14.63 (14.92) 15.07 (0.74) 14.57 (5.36) 6.85 (0.38) 11.42
(0.29) 7.81 (12.37) 5.10 (5.33) 7.99 (0.73) 5.59 (8.82)
Thermal landscape change: Te spatial configuration % like
adjacencies 0.00 (0.00) 0.04 (0.09) 0.07 (0.16) 0.07 (0.06) 0.09
(0.80) 0.80 (0.80) 0.08 (0.17) 0.12 (0.66) 0.49 (0.55) Aggregation
index 0.00 (0.00) 10.26 (21.67) 15.79 (32.43) 17.39 (14.64) 21.05
(97.27) 97.27 (97.27) 18.89 (36.84) 30.43 (78.38) 72.75 (56.13)
Path cohesion index 4.13 (1.16) 4.07 (1.72) 5.15 (1.23) 3.73
(1.69) 8.39 (3.62) 8.39 (0.00) 4.68 (1.65) 6.38 (3.97) 8.28
(1.92)
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20
Table S4 | Indices of thermoregulation accuracy along a gradient
of plant invasion. Indices are shown separately for the morning
(7h–11h), midday (11h–15h) and
afternoon periods (15h–19h), for both thermoregulating and
thermoconforming lizards. We show the mean body temperature (Tb)
for T. capensis; percentage of time
when Tb was within the Tpref range; the thermoregulation
accuracy index (db), with high values indicating poor match between
Tb and Tpref [79]; the thermoregulation
efficiency index E which approaches zero when animals do not
thermoregulate [79]; and the total distance in metres moved by the
individual. For each index in a given
time period, we show the median across iterations, with the
interquartile range in brackets.
Index Morning Midday Afternoon Native Mildly invaded Highly
invaded Native Mildly invaded Highly invaded Native Mildly invaded
Highly invaded
Mechanism (individual response): Thermoregulating lizard's Tb
Median Tb 22.13 (16.14) 19.93 (16.56) 20.05 (15.51) 34.72 (1.00)
37.57 (3.64) 36.97 (3.61) 33.68 (5.69) 33.94 (8.10) 32.95
(9.64)
% time Tpref 11.15 (5.49) 12.59 (6.21) 10.97 (3.60) 54.09
(11.59) 14.7 (7.27) 17.58 (8.56) 34.44 (7.02) 21.25 (5.97) 19.58
(4.31) db 11.87 (14.92) 14.07 (15.81) 13.95 (15.23) 0.00 (0.38)
2.57 (3.62) 1.97 (3.46) 0.41 (5.33) 1.67 (6.52) 2.41 (8.89) E 0.19
(0.71) 0.07 (0.74) 0.08 (0.51) 1.00 (0.06) 0.77 (0.29) 0.73 (0.39)
0.89 (0.67) 0.76 (0.73) 0.49 (0.76)
Distance moved 74.51 (4.62) 63.07 (5.91) 72.52 (5.36) 28.01
(9.87) 77.41 (11.27) 86.18 (12.37) 55.81 (8.99) 79.6 (8.97) 79.46
(8.82) Mechanism (individual response): Thermoconforming lizard's
Tb
Median Tb 18.87 (9.56) 18.48 (11.72) 18.87 (11.71) 40.88 (5.06)
45.69 (5.22) 42.71 (3.35) 31.24 (9.85) 35.01 (16.6) 30.72 (13.02) %
time Tpref 1.80 (1.08) 2.52 (1.44) 2.52 (1.53) 2.42 (1.21) 0.30
(0.61) 0.30 (0.61) 4.44 (1.53) 2.50 (1.12) 3.33 (1.39)
db 15.13 (9.56) 15.52 (11.66) 15.13 (11.71) 5.88 (5.05) 10.69
(5.22) 7.71 (3.35) 4.61 (6.17) 7.65 (6.40) 5.57 (7.48) E 0.00
(0.09) -0.01 (0.07) -0.01 (0.06) 0.16 (0.62) 0.03 (0.34) 0.03
(0.30) 0.10 (0.40) 0.06 (0.22) 0.05 (0.16)
Distance moved 117.07 (5.88) 117.15 (4.58) 116.49 (4.63) 138.77
(3.71) 138.98 (5.56) 138.63 (6.17) 150.89 (5.58) 151.93 (4.98)
151.25 (4.96)
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21
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