Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

The impact of climate change on the distribution of wetland-associated

invasive alien plant species in Western province, Sri Lanka

Prabhathi Kaushalya-Athukorala1; https://orcid.org/0009-0004-9488-9505

Udaya Priyantha Kankanamge-Epa1*; https://orcid.org/0000-0001-9359-9603

Shamen Vidanage2; https://orcid.org/0000-0003-0136-9881

Harsha Kumara-Kadupitiya3; https://orcid.org/0000-0002-9300-0485

1. Department of Zoology and Environmental Management, Faculty of Science, University of Kelaniya, Sri Lanka; athu-

koralaprabhathi@gmail.com, epa@kln.ac.lk (*Correspondence).

2. International Union for Conservation of Nature (IUCN), Sri Lanka; shamenpv@gmail.com

3. Natural Resources Management Centre, Department of Agriculture, Sri Lanka; kadupitiya@gmail.com

Received 16-II-2024. Corrected 21-I-2025. Accepted 24-VI-2025.

ABSTRACT

Introduction: Climate change and invasive alien plant species (IAPS) severely threaten natural ecosystems

globally.

Objective: To identify and assess climate suitability for seven wetland-associated species and predict their future

distribution using shared socio-economic pathways (SSPs) 2 4.5 and 5 8.5 for 2050 and 2070.

Methods: The species selected were Alstonia macrophylla, Annona glabra, Dillenia suffruticosa, Lantana camara,

Leucaena leucocephala, Panicun maximum, and Sphagneticola trilobata. Data on species occurrence were col-

lected by field surveys in the Western province (Colombo, Gampaha and Kalutara districts), and this, together

with climate data, were fed into the Maximum Entropy model (MaxEat model). Climate suitability area maps

were developed for the seven IAPS for the current climate and four future scenarios.

Results: A. glabra, L. camara, and L. leucocephala showed an increase in climate-suitable areas for the years 2050

and 2070 under both climatic scenarios compared to the current distribution. S. trilobata showed a decrease in

its range in the future compared to the current distribution. The climate-suitable area for A. macrophylla will

also not expand under either scenario except for a modest rise in SSP2 4.5 in 2050. The current distribution of D.

suffruticosa and SSP2 4.5 in 2050’s distributions were almost identical, and the other two future scenarios showed

comparatively low distribution. For P. maximum SSP2 4.5 indicated a slight increase in climate-suitable areas for

2070 compared to the current distribution.

Conclusion: A. glabra, L. camara, and L. leucocephala can become highly invasive as their ranges expand in

response to future climate changes. The distribution of S. trilobata will be significantly reduced under future cli-

mate scenarios. As suitable areas for IAPS increase in the Colombo district over time compared to other districts

in the province, its wetland-associated native plant species may face a greater risk of invasion by IAPS in future

climatic scenarios.

Key words: temperature; range expansion; exotic; habitat shift; biodiversity.

https://doi.org/10.15517/rev.biol.trop..v73i1.58832

CONSERVATION

2Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

INTRODUCTION

Invasions due to the positive impact of

global climate change on biological organisms

are regarded as one of the key causes affecting

biodiversity and ecological functioning, caus-

ing life on Earth to relocate globally (Bhagwat

et al., 2012; Çoban et al., 2020; Thuiller et al.,

2008). Further, biological invasions will cause

changes in species distribution, extinctions, and

habitat loss, which will affect natural, agricul-

tural, and croplands (Çoban et al., 2020; Corlett

& Westcott, 2013; Dang et al., 2021; Thuiller et

al., 2008; Walther et al., 2009). Notably, within

the last few decades, invasive alien plant species

(IAPS) increased their distribution, competi-

tion for resources, hybridization with non-

native species, homogeneity in ecosystems due

to the displacement of native biota and altera-

tions in genetic diversity (Abdelaal et al., 2020;

Cao et al., 2021; Corlett & Westcott, 2013; Dang

et al., 2021; Garcia et al., 2014; Walther et al.,

2009). Identifying and predicting such impacts

of invasive species and their distribution before

they invade new environments under vari-

ous climate scenarios is vital to reducing their

future effects (Bhagwat et al., 2012; Garcia et al.,

2014; Marambe & Wijesundara, 2021; Thapa et

al., 2018). According to Essl et al. (2019) and

Walther et al. (2009), as climate change has

accelerated biological invasions, a more com-

prehensive and holistic management plan is

required to restrict their spread and detrimen-

tal consequences.

Species distribution models (SDMs) are

commonly utilized in ecology and conserva-

tion studies (Elith et al., 2010; Jiang et al.,

2023; Thapa et al., 2018). They combine a set

of known species occurrences data with envi-

ronmental variables to forecast species’ present

and future distribution (Abdelaal et al., 2020).

Such distribution models are very effective in

evaluating the spreading of invasive species,

for biodiversity conservation, and to assess the

RESUMEN

Impacto del cambio climático en la distribución de especies de plantas exóticas invasoras

en humedales de la provincia occidental de Sri Lanka

Introducción: El cambio climático y las especies de plantas exóticas invasoras (EPI) amenazan gravemente los

ecosistemas naturales a nivel mundial.

Objetivo: Identificar y evaluar la idoneidad climática de siete especies asociadas a humedales y predecir su distri-

bución futura utilizando vías socioeconómicas compartidas (VSSP) 2 4.5 y 5 8.5 para 2050 y 2070.

Métodos: Las especies seleccionadas para el estudio fueron Alstonia macrophylla, Annona glabra, Dillenia suffru-

ticosa. Lantana camara, Leucaena leucocephala, Panicun maximum, y Sphagneticola trilobata. Los datos sobre la

presencia de especies se recopilaron mediante estudios de campo en la provincia occidental (distritos de Colombo,

Gampaha y Kalutara) y estos, junto con datos climáticos, se incorporaron al modelo de máxima entropía (modelo

MaxEnt). Se desarrollaron mapas de áreas de idoneidad climática para las siete EPIs para el clima actual y cuatro

escenarios futuros.

Resultados: A. glabra, L. camara y L. leucocephala mostraron un aumento en las áreas adecuadas para el clima para

2050 y 2070 en ambos escenarios climáticos en comparación con la distribución actual. S. trilobata mostró una

disminución en su rango en el futuro en comparación con la distribución actual. El área adecuada del clima para

A. macrophylla tampoco se expandirá en ninguno de los escenarios, excepto por un aumento modesto en SSP2 4.5

en 2050. La distribución actual de D. suffruticosa y las distribuciones de SSP2 4.5 en 2050 fueron casi idénticas, y

los otros dos escenarios futuros mostraron una distribución comparativamente baja. Para P. maximum, SSP2 4.5

indicó un ligero aumento en las áreas adecuadas del clima para 2070 en comparación con la distribución actual.

Conclusión: A. glabra, L. camara y L. leucocephala pueden volverse altamente invasivas a medida que sus áreas

de distribución se expandan en respuesta a futuros cambios climáticos. La distribución de S. trilobata se reducirá

significativamente en futuros escenarios climáticos. A medida que las áreas adecuadas para EPIs aumenten en el

distrito de Colombo en comparación con otros distritos de la provincia, sus especies de plantas nativas asociadas

a humedales pueden enfrentar un mayor riesgo de invasión por EPIs en futuros escenarios climáticos.

Palabras clave: temperatura; expansión de área de distribución; exóticas; cambio de hábitat; biodiversidad.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

possible impact of climate change on species’

distribution patterns (Thapa et al., 2018). The

maximum entropy model, or MaxEnt model, is

an open-source SDM that uses environmental

grid data and geographic coordinates of species

occurrences to predict the future distribution of

species (Jiang et al., 2023; Nyairo & Machimura,

2020). Since its release in 2004, it has been

widely used for modelling species distributions.

MaxEnt model is a machine learning method to

create species distribution maps from presence-

only data (Franklin, 2010).

Distribution impacts of IAPS are particu-

larly severe on oceanic islands (Essl et al.,

2019; Marambe & Wijesundara, 2021; Wije-

sundara, 2010), where species and ecosystems

are distinct and vulnerable due to island plant

syndrome caused by limited resources, weak

predation, and decreased interspecific and

intraspecific competition (Essl et al.,2019; Kari-

yawasam et al., 2019). The shortage of native

plant species for utilitarian or ornamental uses

on islands led to a significant increase in the

cultivation of alien plants (Essl et al., 2019).

Sri Lanka, a tropical island with one of the

world’s 36 hotspots, has a diverse topography

and different climates, contributing to substan-

tial plant richness, including 3 350 endemic

plant species. The country’s wet zone is home

to 94 % of its endemic plant species (Green

et al., 2009). However, climate change affects

the country’s rainfall distribution, resulting in

a smaller wet zone region (Eeswaran, 2018;

Marambe & Wijesundara, 2021). According

to combined climate suitability maps created

for 14 IAPS in Sri Lanka for the year 2050,

biodiversity-rich zones with higher endemism

are potentially at a higher risk of climate change

(Kariyawasam et al., 2021).

Most invasive alien plants in Sri Lanka

were initially introduced intentionally as orna-

mental or economically beneficial plants (Iqbal

et al., 2014; Marambe & Wijesundara, 2021;

Perera & Epa, 2023; Wijesundara et al., 2010).

Due to their specific adaptations to rapid

spread in new habitats, they eventually spread

into human settlements, forests, agricultural

areas and wetlands, causing a detrimental effect

on all these habitats. Thirty-one plants are

considered nationally important IAPS in Sri

Lanka (Wijesundara et al., 2010), of which 27

are invasive weeds spreading in agroecosystems

(Marambe & Wijesundara, 2021). Identifying

and mapping invasive flora and vulnerable

habitats is critical for successful invasive alien

species (IAS) control, as baseline data on the

distribution and abundance of IAPS in Sri

Lanka are limited. Many studies focus on the

rising vulnerability of biodiversity to IAS in

temperate regions. However, the tropics, where

most biodiversity hotspots are located, have

gotten less attention (Iqbal et al., 2014).

This study was conducted in seven selected

wetlands in the Western province of Sri Lanka

using seven frequently found, Alstonia mac-

rophylla, Annona glabra, Dillenia suffruticosa,

Lantana camara, Leucaena leucocephala, Pani-

cum maximum, and Sphagneticola trilobata.

The objectives of the study were to identify

and assess potential climate suitability for the

Western province wetlands, predict possible

distribution changes in wetlands using Shared

Socio-economic Pathways 2 4.5 and 5 8.5 for

2050 and 2070, and assess the risk posed by the

distribution of native plant species in wetlands

of the Western province. Here, predictions were

made for climate conditions in the years 2050

and 2070 using the current geo-referenced

occurrence data of seven and climate data in

the MaxEnt model.

MATERIALS AND METHODS

Study area: The wetlands selected for the

study (Table 1) were in all three districts of the

Western province, namely, Colombo, Gampa-

ha, and Kalutara (6°49’59.99” N & 80°04’60.00”

E). The Western province covers an area of 3

684 km2, which represents 5.6 % of the coun-

try’s total land area. It is in the country’s South-

west and receives about 2 500 mm of rainfall

yearly, with the Southwest monsoon playing a

significant role. The average temperature varies

slightly from month to month, ranging from 28

to 29 °C.

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Species occurrence data: For the study,

seven IAPS that are frequently found and well-

established in Sri Lankan wetlands were select-

ed (Table 2). A. macrophylla is originally found

in Southeast Asia and deliberately introduced

to Sri Lanka from Malaysia (Jayawardhane &

Gunaratne, 2022). This plant is famous as a

pioneer plant that quickly colonizes disturbed

land areas (Ministry of Mahaweli Development

& Environment [MMD&E], 2015). Accord-

ing to (Nanayakkara, 2002), A. glabra was

likely introduced to the country in the 19th

century for unknown reasons. Crude extracts

from A. glabra seed, pulp, or leaves are com-

monly used in traditional medicine in Mexico,

China, and Japan but not in Sri Lanka. In

1882 D. suffruticosa was introduced to Royal

Botanical Gardens of Sri Lanka from Boneo

(Wickramathilake et al., 2014). D. suffruticosa

is a species capable of affecting the nutrient

absorption of native plants growing beneath

it by altering the soil structure and functions

(Wickramathilake et al., 2014). L. camara has

been naturalized in approximately 50 countries

and is regarded as one of the world’s worst

weeds (Qin et al., 2016). L. camara is an orna-

mental plant that was introduced to Sri Lanka

back in 1926 (Fernando et al., 2016). L. camara

can adjust and thrive in harsh environmental

conditions due to its phenotypic plasticity and

allelopathy (Day et al., 2003). L. leucocephala is

among the top five invasive plant species with

a global presence (Sharma et al., 2022). It is

believed that this fast-growing Southeast Asian

legume plant was brought to the island in 1970

as a multipurpose plant due to its nitrogen-

fixing ability. Even though it raises nitrogen in

the soil, it easily outcompetes native plant spe-

cies with its ability to produce a higher number

of seedlings and germination rate (Bambarad-

eniya et al., 2001; Liyanage et al., 1993; Weber,

2004). P. maximum is a very famous weed in

Sri Lanka that was introduced in the 1820s and

now causes significant issues in agriculture and

forestry plantation establishment. This plant

suppresses native flora through pest and dis-

ease transmission, resource domination, and

alteration of ecosystems (Gajaweera et al., 2011;

MMD&E, 2015). S. trilobata, is considered one

of the world’s 100 worst invasive species. This

was introduced to Sri Lanka back in the 1980s

as a cover crop for tea plantations (Prematilake

& Ekanayake, 2004). The S. trilobata creates a

Table 2

The invasive alien plant species (IAPS) recorded during the study.

Family name Species Common name Life form

Apocynaceae Alstonia macrophylla Wall. ex G.Don Hard milkwood Tree

Annonaceae Annona glabra L. Pond apple Small tree

Dilleniaceae Dillenia suffruticosa (Griff ex Hook.f. & Thomson) Martelli Shrubby Dillenia Small tree

Verbenaceae Lantana camara L. Lantana Shrub

Fabaceae Leucaena leucocephala (Lam.) de Wit White leadtree Tree

Poaceae Panicum maximum Jacq. Guinea Grass Grass

Asteraceae Sphagneticola trilobata (L.) Pruski Creeping ox eye Creeper

The GPS Map Camera. (n.d.) was used to get live locations and capture photos.

Table 1

The wetlands selected to assess the future distribution of

invasive alien plant species under different climate change

scenarios in the Western Province, Sri Lanka.

Name of the wetland Area (Km2)District

Muthurajawela marsh-South 5.69 Gampaha

Bellanwila-Attidiya marsh 3.72 Colombo

Parliament road marsh 2.94 Colombo

Bolgoda wetland-East 2.45 Colombo

Thalawathugoda wetland park 0.24 Colombo

Diyata Uyana marsh 0.20 Colombo

Beddagana (Kotte) marsh 0.19 Colombo

Kotte rampart park 0.18 Colombo

Walauwatta Wathurana swamp 0.12 Kaluthara

Talangama tank 0.11 Colombo

The total sampled wetland area was 15.84 km2.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

very thick and crowded cover on the ground

that prevents the germination of other plant

species. So, it can suppress native flora in wet-

lands by creating unnecessary competition for

nutrients, light, and water (MMD&E, 2015).

The Visual Encounter Survey was con-

ducted from January 2023 to July 2023 in the

ten selected wetlands (Fig. 1) to record current

species occurrence data based on the acces-

sibility to the location. Five 100 m length line

transects were marked using lines and poles in

each wetland, and GPS coordinates of sites were

recorded using a handheld GPS (Etrex/Model:

Garmin Summit). For each transect, 1 m2 quad-

rats are arranged evenly with a 10 m distance

along the line. There was a 20 m gap between

each transect (du Toit et al., 2021).

Climate data: The MaxEnt model uses

climate variables as the major predictors

because its primary aspect is regulating the

geographic distributions of species (Zhang

et al., 2021). Nineteen bioclimatic variables

used as environmental parameters in SDMs

were downloaded from the WorldClim data-

base for current and future climate scenarios

(Fick & Hijmans, 2017). Historical data for the

1970-2000 period was considered at a 2.5 arc-

min resolution using the sixth version of the

atmosphere-ocean General Circulation Model

(GCM), Model for Interdisciplinary Research

on Climate (MIROC6). Selecting a suitable

global climate model for species distribution

modelling is difficult because the performance

of the GCM depends on the study area and the

bioclimatic variables used. However, previous

studies suggest that MIROC6 performs well in

South Asia (Kariyawasam et al., 2019). For the

future climate prediction updated scenario of

Representative Concentration Pathways (RCP),

Fig. 1. The selected wetlands in the Western Province, Sri Lanka.

6Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

Shared Socioeconomic Pathways (SSPs) were

considered, which were used for the Intergov-

ernmental Panel on Climate Change (IPCC)

sixth Assessment Report (AR6). Here, SSP2

4.5, a combination of SSP two and RCP 4.5,

and SSP5 8.5, SSP five and RCP 8.5, were used

as greenhouse gas emissions pathways for the

years 2050 and 2070.

To remove highly correlated variables in 19

environmental variables in the MaxEnt model,

Pearson Correlation Coefficients (r) among

variables were calculated. The ‘removeCol-

linearity’ (version 1.5.1) function in R software

(Leroy et al., 2015) was used to calculate the

correlation, and the following six variables were

selected to conduct the study (Table 3).

MaxEnt model settings: MaxEnt version

3.4.4 (Phillips et al., n.d.) was used to get a

random test percentage setting in the model.

This model option divides the uploaded spe-

cies’ occurrence data into two parts. A certain

percentage of data (called test data) will be

used to evaluate the model’s performance. The

remaining percentage of training data will be

used to develop the model. The random test

percentage in the settings folder was changed

to 25 %. This automatically sets presence data

to be used as training (75 %) and test data (25

%) (Ding et al., 2022). Species occurrence data

collected through a field survey included 21

points for A. macrophylla, 40 for A. glabra, 21

for D. suffruticosa, 23 for L. camara, 30 for L.

leucocephala, 26 for P. maximum, and 20 for S.

trilobata. In the basic settings, “replicate run

type” was selected as “subsample” and “regu-

larization multiplier value” as one. In advanced

settings, maximum iterations were increased to

5 000. Replicates were set as 15 so that MaxEnt

would run the model multiple times and cre-

ate averaged suitability maps (Tesfamariam et

al., 2022). Other default settings were kept in

the MaxEnt software (Ding et al., 2022). The

species occurrence data CSV file and ASCII

format of historical environmental layers were

uploaded for species A. macrophylla, and the

program was run. Then, the same species

model was run separately for the ASCII format

of future environmental layers of SSP2 4.5 for

the year 2050, SSP2 4.5 for the year 2070, SSP5

8.5 for the year 2050, and SSP5 8.5 for the year

2070. The same procedure was carried out for

the rest of the six species.

Development of climatic suitability

maps: The ‘reclassify’ tool of ArcMap 10.8 was

used to split the current distribution output

raster layer of one species into three categories:

low suitable area, suitable area, and highly suit-

able area. The areas were classified based on the

number of invasive alien plant species (IAPS)

present: low suitability with 1 IAPS, moderate

suitability with 1.000000001 to 2 IAPS, and

high suitability with 2.000000001 to 3 IAPS.

Then, for the same species raster layer, SSP2 4.5

for the year 2050, SSP2 4.5 for the year 2070,

SSP5 8.5 for the year 2050, and SSP5 8.5 for the

year 2070 were reclassified. This procedure was

applied to the seven selected.

Table 3

The selected environmental variables used for MaxEnt modelling of seven in the wetlands of Western Province, Sri Lanka.

Variable Abbreviation unit

Mean Diurnal Range (Mean of monthly; max temp - min temp) BIO 2 °C

Isothermality (BIO2/BIO7) (×100) BIO 3

Min Temperature of Coldest Month BIO 6 °C

Mean Temperature of Wettest Quarter BIO 8 °C

Mean Temperature of Coldest Quarter BIO 11 °C

Precipitation of Warmest Quarter BIO 18 mm

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

For the quantitative evaluation of the suit-

ability area changes for the years 2050 and 2070,

the class “suitable area” was calculated using the

following formula.

Then, potentially suitable areas change

for each class of seven species under SSP2 4.5

and SSP5 8.5 for the years 2050 and 2070 were

further analyzed as an area reduction or expan-

sion. The following formula was used to cal-

culate the percentage of the proportion of area

increase regarding the original area.

Thus, area expansions were expressed as

negative values, while reductions were defined

as positive (Kariyawasam et al., 2019).

Statistical analysis: The MaxEnt model

supplied statistical tests for the modelling pro-

cess. One was the receiver operating charac-

teristic (ROC) curve or area under the curve

(AUC) value, a default setting. AUC value is

essential to quantitatively evaluate the predic-

tive performances of the model for each model

run (Kariyawasam et al., 2019). AUC value

helps to assess the performance of the model in

each run. This value can range between 0-1. An

AUC value below 0.2 will indicate the model’s

poor performance, and AUC values between

0.5 and 0.7 are moderate. The value above 0.7

shows the model’s high performance (Thapa et

al., 2018).

RESULTS

MaxEnt model prediction accuracy: The

overall accuracy for each run of the model was

quantitatively assessed by area under the curve

(AUC) value. When considering the present

and future periods of seven, AUC values ranged

between 0.87 (lowest) and 0.98 (highest) with

training data and 0.74 (lowest) and 0.98 (high-

est) with test data. The average training value

was 0.96, and the average test value was 0.93.

The highest AUC value of 0.98 was obtained

for S. trilobata for the year 2070 in SSP2 4.5.

The lowest AUC value, 0.87, was obtained for

Dillenia suffruticosa in the year 2050 in SSP2

4.5. Six out of seven had AUC values > 0.9.

Current and future distribution of

wetland-associated invasive alien plant spe-

cies: Under the current climate, larger suit-

able predicted areas were recorded for D.

suffruticosa (1 703.73 km2) and A. macrophylla

(1 172.06 km2). The species L. leucocephala had

the lowest suitable predicted area, 16.24 km2

(Table 4).

Three species, namely A. glabra, L. camara,

and L. leucocephala, showed an overall increase

in climate-suitable areas for years 2050 and

2070 under both climatic scenarios than the

current distribution (Fig. 2). S. trilobata was the

only species that showed a decrease in climate-

suitable areas for the years 2050 and 2070

under both climatic scenarios compared to the

current distribution. For A. macrophylla, SSP2

4.5 for 2050 was the only scenario that showed

a higher climate-suitable area than the current

distribution. The distribution of A. macro-

phylla in SSP5 8.5 will decline by 85.1 % in 2050

(Table 5). Even though the highly suitable area

of A. macrophylla will be reduced in the year

2050 for SSP5 8.5, its highly suitable area will

expand into the Southern part of the province

(Fig. 3A). The climate-suitable areas of A. gla-

bra will significantly increase from 30.76-47.42

% in 2050 and 2070. The highly suitable area

of A. glabra (2 06.33 km2) will also increase by

9.54 % for SSP2 4.5 in 2025 and 0.42 % for SSP5

8.5 by 2070.

D. suffruticosa’s current distribution and

SSP2 4.5 for 2050’s future distribution were

almost identical, and other future scenarios

showed less distribution than these two. The

highly suitable area (285.95 km2) of D. suffruti-

cosa will expand by 16.47 % in SSP2 4.5 in 2050

and 2.6 % in SSP5 8.5 in 2070. Under future

climate circumstances, D. suffruticosa will be

8Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

dispersed from 1 382.68 km2 to 1 708.01 km2,

extending into all three districts. In all future

climate scenarios, the suitable and highly suit-

able areas of L. camara in the western province

will increase. According to the species distribu-

tion maps, this species will mainly be distrib-

uted in the Colombo and Gampaha districts

in future.

Table 4

Projected area of suitability (km2) of the seven IAPS of three classes (low suitable, suitable, and highly suitable) under the

current climate and SSP2 4.5 and SSP5 8.5 for 2050 and 2070.

Species Distribution

class Current 2050 2070

SSP2 4.5 SSP5 8.5 SSP2 4.5 SSP5 8.5

Alstonia macrophylla Low suitable 2 361.25 2 359.54 3 434 2 385.23 2 391.23

Suitable 1 172.06 1 181.48 174.65 1 130.11 1 091.587

Highly suitable 187.5 179.79 112.16 259.41 199.48

Annona glabra Low suitable 3 016.2 2 773.92 2 787.61 2 868.1 2 877.51

Suitable 498.28 720.88 734.57 651.53 636.12

Highly suitable 206.33 226.02 198.63 201.19 207.19

Dillenia suffruticosa Low suitable 1 731.13 1 679.76 2 063.31 2 028.21 1 907.5

Suitable 1 703.73 1 708.01 1 382.68 1 450.31 1 523.94

Highly suitable 285.95 333.04 274.82 242.29 289.38

Lantana camara Low suitable 3 036.75 2 660.9 2 794.46 2 697.72 2 717.41

Suitable 474.31 835.6 657.52 775.67 803.07

Highly suitable 209.76 224.31 268.83 247.43 216.34

Leucaena leucocephala Low suitable 3 398.9 3 065 2 781.62 2 821 2 551.32

Suitable 16.24 504.27 722.59 688.34 942.62

Highly suitable 156.68 155.54 216.61 211.47 226.88

Panicum maximum Low suitable 2 843.26 3 433.15 2 858.67 2 820.15 3 100.11

Suitable 678.07 161.81 673.79 689.2 447.77

Highly suitable 199.48 125.85 188.35 211.47 172.94

Sphagneticola trilobata Low suitable 2 767.07 2 855.25 3 462.26 3 420.31 3 428.87

Suitable 757.69 698.62 142.98 151.54 167.81

Highly suitable 196.06 167.81 115.58 148.97 124.14

Fig. 2. Projected suitable area (km2) of the seven selected IAPS in Western province wetlands in Sri Lanka under current

climate and MIROC6 SSP2 4.5 and SSP5 8.5 for 2050 and 2070.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

For P. maximum SSP2 4.5 for 2070 was the

only scenario that showed a higher climate-

suitable area than current distribution. In the

Colombo district, P. maximum has its highly

suitable areas (199.48 km2), which reduce in

2050 SSP2 4.5, 2050 SSP5 8.5, and 2050 SSP5

8.5 but show an increment for the 2070 SSP2

4.5 by 3.01 %. In current climate conditions, P.

maximum has a suitability area of 678.07 km2,

but this reduces significantly for SSP2 4.5 by

76.14 % in 2050. In the year 2050, SSP5 8.5 and

2070 SSP2 4.5 show suitable area increments,

while 2070 SSP5 8.5 show a reduction. The cur-

rent highly suitable areas (156.68 km2) of L. leu-

cocephala in the Colombo district will reduce

slightly for SSP2 4.5 in 2050 but increase for the

other three scenarios. In current climate condi-

tions, L. leucocephala has a very low suitability

area of 16.24 km2, but this expands significantly

in both scenarios for the years 2050 and 2070.

The currently suitable area is spread out only in

the Colombo district, but in the future, it will

expand to both the Kaluthara and Gampaha

districts. When considering S. trilobata highly

suitable areas (196.06 km2) in the Colombo

district, it is reduced for all future scenarios.

In current climate conditions, S. trilobata has

a noticeable suitability area (757.69 km2) that

covers Colombo and Kaluthara districts. This

area was slightly reduced for SSP2 4.5 by 7.80 %

in 2050 and significantly reduced for 2050 SSP5

8.5, 2070 SSP2 4.5, and 2070 SSP5 8.5.

Fig. 3 shows the maps of climatic suitability

for selected under the current climate and SSP2

4.5 and 5 8.5 for 2050 and 2070. The projected

maps of all seven species under the current

climate showed a highly suitable region in the

Western part of the Colombo district, including

Bellanwila-Attidiya Marsh, Bolgoda Wetland,

and Colombo Wetland City. In the future, the

Table 5

Percentage area variation (km2) of invasive alien plant species (IAPS) under current climate and SSP2 4.5 and SSP5 8.5 for

2050 and 2070.

Species Distribution class SSP2 4.5 SSP5 8.5

2050 2070 2050 2070

Alstonia macrophylla Low suitable -0.072 1.01 45.43 1.27

Suitable 0.80 -6.87 -85.1 -3.58

Highly suitable -4.11 38.35 -40.2 6.39

Annona glabra Low suitable -8.03 -4.91 -7.58 -4.6

Suitable 44.67 30.76 47.42 27.66

Highly suitable 9.54 -2.49 -3.73 0.42

Dillenia suffruticosa Low suitable -2.97 17.16 19.19 10.19

Suitable 0.25 -14.87 -18.84 -10.55

Highly suitable 16.47 -15.27 -3.89 1.2

Lantana camara Low suitable -12.38 -11.16 -7.98 10.52

Suitable 76.14 63.53 38.63 69.31

Highly suitable 6.94 17.96 28.16 4.49

Leucaena leucocephala Low suitable -9.82 -17.00 -18.16 -24.94

Suitable 3005.12 4138.53 4349.45 5704.31

Highly suitable -0.73 34.97 38.25 44.80

Panicum maximum Low suitable 20.75 -0.81 0.54 9.03

Suitable -76.14 1.64 -0.63 -33.96

Highly suitable -36.91 6.01 -5.58 -13.30

Sphagneticola trilobata Low suitable 3.19 23.60 25.12 23.92

Suitable -7.80 -80 -81.13 -77.85

Highly suitable -14.41 -24.01 -41.05 -36.68

10 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

Fig. 3. Continue in next page.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

Fig. 3. Map showing current and future projected climate suitability for seven IAPS in the Western province of Sri Lanka.

A. Alstonia macrophylla, B. Annona glabra, C. Dillenia suffruticosa, D. Lantana camara, E. Leucaena leucocephal, F. Panicum

maximum, G. Sphagneticola trilobata. a: Current climate, b: MIROC6 SSP2 4.5 for 2050; c: MIROC6 SSP2 4.5 for 2070; d:

MIROC6 SSP5 8.5 for 2050 and e: MIROC6 SSP5 8.5 for 2070.

12 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

native biodiversity in this area could be highly

affected by the range expansion of wetland-

associated IAPS.

DISCUSSION

The seven wetland-associated invasive

plant species evaluated differed significantly in

terms of biological characteristics and belonged

to the following Families: Annonaceae, Apocy-

naceae, Asteraceae, Dilleniaceae, Fabaceae,

Poaceae, and Verbenaceae. The results show

that their responses to different climatic sce-

narios also vary. Recent studies, including those

by Bezeng et al. (2017) and Jiang et al. (2023),

indicate that the impact of climate change on

invasive alien plant species (IAPS) is highly

species-specific. In Sri Lanka’s Western wetland

ecosystems, species like A. glabra, L. camara

and L. leucocephala are predicted to expand

their range under SSP2 4.5 and SSP5 8.5 climate

scenarios, posing threats to native biodiversity.

The distribution models show temperature-

related variables, especially those linked to

cold-season temperatures, as critical drivers of

this expansion. For A. glabra, the mean tem-

perature of the coldest quarter (BIO11) contrib-

uted 73.1 % to the 2050 model under SSP2 4.5,

suggesting potential range expansion as cold

temperatures rise. L. camara’s model showed

a 90.6 % contribution from BIO11, highlight-

ing its sensitivity to cold-season temperatures

and the likelihood of invading new areas. L.

leucocephala, with a 98.1 % contribution from

BIO11 under the SSP2 4.5 scenario for 2070, is

also expected to significantly expand its range

as cold temperatures become less restrictive.

These findings underscore the importance of

cold-season temperatures in shaping the future

distribution of these invasive species.

Two scenarios with two distinct time peri-

ods suggested that A. glabra’s suitability area

increased by more than 27 % (table 5) from

the current distribution. The highly suitable

area for this species fluctuates between 198.63-

226.02 km2 within both scenarios in 2050

and 2070. Under SSP5 8.5 in 2050, A. glabra

suitability area is likely to increase by 47.42 %

compared to the current distribution. Birds

and mammals disperse A. glabra seeds, which

may survive in fresh and saltwater for up to 12

months (Setter et al., 2002), enhancing their

ability to invade new habitats like wetland eco-

systems, particularly in the wet zone because A.

glabra can successfully grow as dense clusters

in both freshwater and brackish water wetlands

(MMD&E, 2015; Nanayakkara, 2002) A. glabra

form dense monocultures spreading in wet-

lands, riparian zones, coastal foreshores, and

other natural and manmade drainages in Aus-

tralia, creating a biodiversity conservation issue

(Setter et al., 2002). Initiating eradication mea-

sures now will better prepare us for future chal-

lenges. If the SSP5-8.5 scenario occurs in 2070,

these early actions will make it more feasible to

manage and potentially eradicate the species

from its established habitats in Sri Lanka.

It produces allelopathic compounds and

frequently creates dense monospecies stands by

interrupting the regeneration process of indige-

nous plant species (Kato-Noguchi & Kurniadie,

2021). The immediate introduction of control

measures is highly recommended for L. camara

as in all future climatic scenarios in 2050

and 2070; this species showed more expansion

than the currently suitable area in Sri Lanka.

The highest suitability to spread was shown

under SSP2 4.5 in the year 2050, which could

increase the suitability area by 76.14 %. The

lowest future suitability is shown under SSP5

8.5 in the year 2050, in which the suitability

area can increase only by 38.63 %. As a result,

unless a proper plan is implemented to prevent

this species’ continuing range expansion, it

will benefit from climate change scenarios and

establish itself in new places, posing conserva-

tion challenges. According to Qin et al. (2016),

MaxEnt model predictions through 2050 indi-

cated an overall global expansion of L. camara

despite future suitability varying considerably

among continents.

It is widely used in agroforestry, livestock,

and restoration operations, leading to its inva-

sion of natural ecosystems in Asia. Out of

seven plants studied, L. leucocephala had the

lowest current distribution in the wetland

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

environments in Sri Lanka. The plant primar-

ily invades wastelands, roadsides, riverbanks,

agricultural lands, and forest edges, inhibiting

the growth of other woody and herbaceous

species (Sharma et al., 2022). The highly moist

soil in a wetland environment and the current

climate may not be very positive for the dis-

tribution of L. leucocephala. However, future

climate scenarios are highly advantageous for

the range expansion of these species. Accord-

ing to MaxEnt model prediction, L. leuco-

cephala will have a suitability area increase of

more than 3 005 % for all four future climatic

scenarios. Although L. leucocephala has limited

natural dissemination by mechanical means,

its persistent seed bank likely assures dispersal

through the soil, which is common around

disturbed sites (Nghiem et al., 2015). The high-

est suitability is presented under SSP5 8.5 in

2070 when the suitability area can increase by

5 704.31 % and the highly suitable area by 44.8

%. The warmer future climate in the wet zone

in Sri Lanka (Kariyawasam et al., 2021) may be

favorable for the growth and dispersal of L. leu-

cocephala. So, this species’ alarming, expected

rate of rapid range expansion must be stopped

before it further affects the local biodiversity.

The current period will be the most suitable

time to eradicate L. leucocephala if selected as a

management option.

A. macrophylla is widely distributed in sev-

eral Asian countries, including Sri Lanka, India,

Thailand, Cambodia, Indonesia and Vietnam.

It is a drought-resistant, wind-dispersed tree

that thrives even on poor soil. According to the

results, SSP5 8.5 in 2050 was the most unfa-

vorable climate for A. macrophylla because its

suitability area will be reduced by 85.1 %. In

SSP5 8.5 in 2070, the suitability area will also

be reduced by 3.58 % compared to the current

suitability area. So, future climate conditions

in the western province can be unfavorable for

A. macrophylla. A. macrophylla is expected to

experience climatic unsuitability by 2050 under

the SSP5 8.5 scenario, presenting an opportuni-

ty to control its spread in vulnerable ecosystems

in the Western province. Nonetheless, eradica-

tion and containment plans should be prepared

in advance, even if future conditions may facili-

tate these efforts. A. macrophylla has been natu-

ralized on Sentosa Island in Singapore since

1879 but has yet to spread beyond its original

location (Nghiem et al., 2015), which shows its

slow range expansion in invaded habitats.

D. suffruticosa, a native of East Asia, has

the highest distribution in the current climate

and four future scenarios compared to the

other six studied. The presence of this species is

considered a sign of forest degradation (Heng

et al., 2014). According to Wijesundara (2010),

the population size of D. suffruticosa has rap-

idly increased in Sri Lanka owing to optimum

environmental conditions. However, only SSP2

4.5 in 2050 showed a slight increase in the suit-

ability area (0.25 %) for D. suffruticosa. All the

other three scenarios showed a decrease in the

suitable area of over 10 % compared to the cur-

rent suitability area. Even though the suitability

area is predicted to be low in the future, the area

it occupies will be considerably higher than the

other six invasive species. Therefore, managing

the spreading of D. suffruticosa in the future

needs’ special attention. It has spread to several

areas of the country, including natural ecosys-

tems, abandoned or degraded lands, and forest

plantations. When considering the predictions

of P. maximum, only 2070 SSP2 4.5 could

increase the area by 1.64 %. All the other three

scenarios showed a decline in the suitability

area. The SSP2 4.5 in 2050 will have the highest

drop in the area, 76.14 %. So, the future climate

is not more advantageous for P. maximum than

the current climate. According to Jiang et al.

(2023), climate change may negatively affect the

global distribution pattern of another Guinea

grass species, P. milliaceum.

The present climate is the most suitable

condition for S. trilobata because it has the

highest distribution compared to most future

climate scenarios. For SSP2 4.5 in 2050, the

suitability area of the species reduced slightly by

7.08 %. For all the other future scenarios of the

species, it shows a suitable area decline of more

than 77 % compared to the current suitability

area. The SSP5 8.5 in 2050 will be the species’

most unfavorable scenario, showing 81.13 %

14 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

suitable area reduction. Also, it will be the best

phase to manage the abundance of this species

with the help of adverse environmental condi-

tions of nature. S. trilobata thrives in moist

areas like marshes and riverbanks, frequently

impacted by human activity (Kato-Noguchi

& Kurniadie, 2021; Perera et al., 2023). The

expected lesser distribution of this plant under

future climatic scenarios could be ascribed to

the rising temperature in the environment. To

leverage potential future climate unfavourabil-

ity, appropriate eradication measures should be

implemented now. Also, it will be the best phase

to manage the abundance of this species with

the help of adverse environmental conditions

of nature. S. trilobata thrives in moist areas like

marshes and riverbanks, frequently impacted

by human activity (Kato-Noguchi & Kurniadie,

2021; Perera et al., 2023). S. trilobata currently

thrives in stable, moist environments, with

isothermality (BIO3) contributing 66.5 % to

its distribution model, highlighting its reliance

on consistent temperature patterns. However,

as the climate warms, the species’ distribution

is expected to shift. By 2070, under the SSP2

4.5 scenario, the mean temperature of the cold-

est quarter (BIO11) becomes overwhelmingly

dominant, contributing 99.3 %, indicating a

growing dependence on cold-season tempera-

tures. Similarly, under the SSP5 8.5 scenario for

2070, BIO11 and BIO6 (Min Temperature of

Coldest Month) together account for over 33 %

of the model, reflecting the species’ increasing

sensitivity to warming trends. As cooler, stable

conditions become less common, S. trilobata

may struggle to maintain its current distribu-

tion, potentially limiting its spread in the West-

ern Province of Sri Lanka.

It is well known that invasive plants fre-

quently inhabit human-modified ecosystems,

which are different from their native habitats

(Bhagwat et al., 2012; Çoban et al., 2020; Corlett

& Westcott, 2013; Dang et al., 2021; Thuiller et

al., 2008; Walther et al., 2009). Western Prov-

ince is Sri Lanka’s most populous province,

so anthropogenic activities have significantly

impacted the natural ecosystems. Disrupted

habitats in the Western province include barren

land, garbage dumping sites, agricultural lands,

human settlements, industrial and construc-

tion sites and manmade wetlands. Due to these

disturbances and future climate suitability, the

wetlands in this environment can be highly

susceptible to IAPS invasions. Meteorological

data analysis in Sri Lanka indicates consider-

able changes in climate parameters, supporting

future climate change (Iqbal et al., 2014). Since

most native plants cannot evolve and change

their distribution area quickly or spread fast like,

it is necessary to take precautionary measures

to manage the range expansion of in Sri Lanka.

Island biogeography, small size, and expanding

anthropogenic disturbances may significantly

impact the spread of across the country. The

projected maps of all seven species under the

current climate showed a highly suitable region

for IAPS in the Western part of the Colombo

district, including Bellanwila-Attidiya Marsh,

Bolgoda Wetland, and Colombo Wetland City.

In the future, the native biodiversity in this area

could be highly affected by the range expansion

of wetland-associated IAPS.

The findings of this study provide scientific

information emphasizing areas that should be

managed more carefully. Because unfavorable

environmental conditions limit the establish-

ment and distribution of (Walther et al., 2009),

most management measures used to control

or remove invasive species are effective when

plant distribution is minimal (Bhagwat et al.,

2012). However, the ability of plants to invade

depends not only on environmental factors but

also on the species invasive potential and prop-

agule pressure (Kariyawasam et al., 2019) which

should also be considered in selecting strategies

to control the future distribution of. Invasive

plants provide significant environmental and

socio-economic challenges. Sri Lanka, a signa-

tory to the Nations Framework Convention on

Climate Change (United Nations, 1992) and the

Paris Agreement (United Nations Framework

Convention on Climate Change, 2016), identi-

fies with the urgency of solving climate-related

challenges (Marambe & Wijesundara, 2021).

This work is the first to predict wetland-associ-

ated dispersal under future climatic conditions

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e58832, enero-diciembre 2025 (Publicado Jul. 30, 2025)

in Sri Lanka, potentially assisting decision-

makers in optimal planning and management.

The MaxEnt model was used to estimate

the distribution of suitable climatic conditions

associated with wetlands in Sri Lanka’s Western

province under shared socio-economic path-

ways SSP2 4.5 and 5 8.5 for 2050 and 2070.

The results provide qualitative and quantitative

evidence along with temporal and spatial loca-

tions where they are possibly distributed or that

can be distributed in the future. A. glabra, L.

camara, and L. leucocephala can become highly

invasive as their ranges expand in response to

SSP2 4.5 and 5 8.5 for both years. S. trilobata is

vulnerable to climate change as its distribution

will significantly reduce under future climate

scenarios. SSP5 8.5 in 2050 will be the species’

most adverse scenario, with an 81.13 % reduc-

tion in suitable territory. A. macrophylla, D.

suffruticosa, and P. maximum will respond dif-

ferently to future climatic scenarios, increasing

and decreasing their distribution in response

to climate fluctuations. Comparatively, native

plant species and ecosystems in Colombo are at

higher risk than in the Gampaha and Kaluthara

districts. The findings can be utilized to design

future conservation efforts for native plant

biodiversity, reducing economic and environ-

mental costs.

Ethical statement: The authors declare

that they all agree with this publication and

made significant contributions; that there is no

conflict of interest of any kind; and that we fol-

lowed all pertinent ethical and legal procedures

and requirements. All financial sources are fully

and clearly stated in the acknowledgments sec-

tion. A signed document has been filed in the

journal archives.

ACKNOWLEDGMENTS

The University of Kelaniya is acknowl-

edged for its financial support to carry out the

study. Comments from anonymous reviewers

to improve the quality of the manuscript are

deeply appreciated.

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