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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, rgarcia@sun.ac.za

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

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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

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Figure S7 | Availability of optimal micro-sites across time along a gradient of plant invasion

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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 assemblage structure in a tropical savannah. Biol. Conserv. 191, 75–82. (doi:10.1016/j.biocon.2015.06.016)

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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(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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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)

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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