Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

Predicting of HABs by phytoplankton type and abundance

in Northern Bone Bay, South Sulawesi, Indonesia

Rahmadi Tambaru1*; https://orcid.org/0000-0001-9403-0697

Abdul Haris1; https://orcid.org/0000-0001-7535-4514

Andi Iqbal Burhanuddin1; https://orcid.org/0000-0001-6770-7914

Muhammad Anshar Amran1; https://orcid.org/0000-0002-3925-2809

Amir Hamzah Muhiddin1; https://orcid.org/0000-0002-5796-7429

Sahabuddin Sahabuddin2; https://orcid.org/0000-0002-5592-7829

1. Department of Marine Science, Faculty of Marine Science and Fisheries, Hasanuddin University. Perintis Kemerdekaan

KM 10 Tamalanrea, Makassar, South Sulawesi, 90425, Indonesia; aditbr69@unhas.ac.id (*Correspondence), haris_pag-

ala@yahoo.co.id, iqbalburhanuddin@yahoo.com, muhammadansharamran@gmail.com, amirhm@unhas.ac.id

2. Research Center for Fishery, National Research and Innovation Agency, Bogor West Java, Indonesia, 16911; saha006@

brin.go.id

Received 07-XI-2024. Corrected 03-IV-2025. Accepted 12-VIII-2025.

ABSTRACT

Introduction: Harmful Algal Blooms (HAB) are the rapid growth of algae or cyanobacteria in water that can

cause negative impacts on people, animals, or the environment by production of natural toxins. Information

about HABs in the bays in Indonesia is limited.

Objective: To predict HABs based on the type and abundance of phytoplankton in the Northern part of Bone

Bay, South Sulawesi, Indonesia.

Methods: The study was conducted in four locations, namely Tj Ringgit (TR), Passampa (PS), Siwa (SW), and

Barangmamase (BM) between May and July 2024. Various environmental parameters, including nutrients, were

measured. Phytoplankton samples were collected by filtering seawater using a 25 μm plankton net and analyzed

in the laboratory.

Results: The dominant types of phytoplankton were found to be Bacteriastrum, Chaetoceros, Leptocylindrus,

Rhizosolenia, Thalassionema, and Ceratium. All of them are classified as Non-HABs. The identified types of

HABs include Pseudo-nitzschia, Dinophysis, Prorocentrum, Protoperidinium, and Oscillatoria. Orthophosphate

and salinity are two environmental parameters that affect the occurrence of HABs. The proportion of HABs

abundance was lower than that of non-HABs in all locations. An increase in the abundance of HABs was detected

in two locations: SW and BM.

Conclusion: Although the proportion of HABs is lower than that of Non-HABs, the increased abundance of

HABs in some locations, such as SW and BM, indicates the potential for future blooms. Monitoring environmen-

tal parameters, especially orthophosphate and salinity, is critical to mitigating the impact of the development of

HABs, which ultimately affects the ecosystem and human health in Bone Bay. This study emphasizes the impor-

tance of sustainable water management to maintain the balance of the ecosystem in the bay.

Key words: phytoplankton; harmful algal blooms (HABs); Bone Bay; orthophosphate; salinity; mitigation.

https://doi.org/10.15517/rev.biol.trop..v73i1.62573

AQUATIC ECOLOGY

2Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

INTRODUCTION

Phytoplankton are microscopic organ-

isms that are found in the surface layers of

waters, such as in the open sea (Latasa et al.,

2022), lakes (Salmaso & Tolotti, 2021), and bays

(Sarkar et al., 2021). Through photosynthesis,

phytoplankton absorb sunlight and then con-

vert it into chemical energy to produce glucose

as a source of energy and oxygen (Basnayaka et

al., 2024). Therefore, they serve as the core of

the food chain and oxygen production in the

waters. Through the production of energy and

oxygen, phytoplankton plays an important role

in maintaining the balance of aquatic ecosys-

tems (Wong et al., 2023).

As organisms that can absorb carbon diox-

ide (CO₂) from the atmosphere, phytoplankton

play a role in the global carbon cycle (Boyd

et al., 2024). The absorbed carbon is stored

in its body (Naselli-Flores & Padisák, 2023).

When this organism dies, the carbon sinks to

the seafloor (Wang et al., 2024). That process

is known as a “carbon biological pump”, which

helps reduce CO₂ levels in the atmosphere

(Siegel et al., 2023). Through the food chain,

carbon stored in the body of phytoplankton can

be transferred to other organisms, spreading

its benefits throughout marine ecosystems and

reducing the impact of climate change (Kabir

et al., 2023).

The presence of phytoplankton becomes

dangerous when the community overgrows,

producing a toxic phytoplankton bloom in the

waters. Harmful Algal Blooms (HABs) are a

term that is often used to describe the event (Li

et al., 2023). HABs can grow if environmental

conditions favor their growth (Ou et al., 2024).

It can inhibit the growth of other phytoplank-

ton (Chatterjee & More, 2023) and the death

of fish (Feng et al., 2024). As HABs grow and

develop, they also secrete toxic substances that

are released into the waters. These toxins then

affect other type of phytoplankton, which can

stunt growth and cause them to die (Lan et

al., 2024). HABs can also cause fish death

RESUMEN

Predicción de proliferaciones de algas nocivas por tipo y abundancia de fitoplancton

en el norte de Bone Bay, Sulawesi del Sur, Indonesia

Introducción: Las proliferaciones de algas nocivas (PANs) son el crecimiento rápido de algas o Cianobacterias

en el agua que pueden causar impactos negativos en las personas, los animales o el medio ambiente mediante la

producción de toxinas naturales. La información sobre PANs en las bahías de Indonesia es limitada.

Objetivo: Predecir la aparición de PANs en función del tipo y abundancia de fitoplancton en la bahía de Bone,

Sulawesi sur, Indonesia.

Métodos: El estudio se realizó en cuatro localidades: Tj Ringgit (TR), Passampa (PS), Siwa (SW) y Barangmamase

(BM), entre mayo y julio de 2024. Se midieron varios parámetros ambientales, incluidos los nutrientes, y se

recolectaron muestras de fitoplancton mediante filtración de agua marina. Las muestras se analizaron en el

laboratorio.

Resultados: Los tipos dominantes de fitoplancton fueron: Bacteriastrum, Chaetoceros, Leptocylindrus, Rhizosolenia,

Thalassionema y Ceratium, todos clasificados como No-PANs. Los taxa identificados de PANs fueron: Pseudo-

nitzschia, Dinophysis, Prorocentrum, Protoperidinium y Oscillatoria. El ortofosfato y la salinidad fueron los prin-

cipales factores ambientales que afectaron la aparición de PANs. La abundancia de PANs fue menor que la de

No-PANs en todas las localidades, aunque en dos sitios, SW y BM, se observó un incremento en la abundancia

de PANs.

Conclusión: A pesar de que la proporción de PANs fue menor que la de No-PANs, el aumento de PANs en algu-

nos lugares sugiere un posible desarrollo futuro de estas proliferaciones. El monitoreo de ortofosfato y salinidad

resulta esencial para mitigar los impactos de PANs, protegiendo tanto el ecosistema como la salud en la bahía

de Bone. Este estudio enfatiza la importancia de la gestión sostenible del agua para mantener el equilibrio del

ecosistema en la bahía.

Palabras clave: fitoplancton; proliferaciones de algas nocivas (PAN); Bone Bay; ortofosfato; salinidad; mitigación.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

(Parra-Saldivar et al., 2023). When HABs are

consumed by fish or attached to their gills, the

fish’s physiological function will be disrupted,

causing stress and ultimately causing death

(Hallegraeff et al., 2023).

When fish die from HABs, they decom-

pose in the waters. This decomposition process

is carried out by bacteria that need oxygen to

decompose organic matter from phytoplank-

ton and dead fish. In the event of a significant

death, bacteria consume very high amounts of

oxygen, reducing dissolved oxygen levels. This

condition is known as hypoxia, which can cre-

ate dead zones where oxygen levels are too low

to support the life of other aquatic creatures,

such as fish and shrimp, ultimately leading to

ecosystem damage (Zahir et al., 2024).

Some phytoplankton type often associ-

ated with HABs are Karenia (Kuroda et al.,

2024). This type is known to cause poisoning

of fish and marine mammals. Other type, such

as Dinophysis, can produce toxins that affect

human health by consuming contaminated sea-

food (Vieira et al., 2024). Alexandrium is also

an organism that causes seafood to contain

toxins, especially in areas that often experi-

ence HABs (Bui et al., 2024). Given the severe

impact it causes, monitoring and research on

HABs is very important to maintain the health

of aquatic ecosystems and human safety.

In its development, the increase in the

number and abundance of HABs in waters,

including bays, shows a significant increase

(Anderson et al., 2021). The results showed

that nutrient-rich bays, such as those in the

Chesapeake Bay, often experience HABs such

as Karlodinium and Microcystis blooms. Both

have been studied for their harmful impacts on

aquatic ecosystems and the shellfish industry

(Wolny et al., 2020). Similarly, in the Gulf of

Mexico, the explosion of the toxic population

of Karenia type (commonly known as red tides)

has been of particular concern, as it produces

brevetoxins that are harmful to marine life and

humans (Tominack et al., 2020).

The growth of phytoplankton type,

including HABs (Blooms) in the bay, is due to

anthropogenic processes on land. The activity

increases the concentration of nutrients that

promote the growth of different phytoplankton

type, including HABs (Blooms) (Rajapaksha

et al., 2024). As a result, it affects the health of

the ecosystem and the fisheries and tourism

industries (Álvarez et al., 2024). For this rea-

son, effective monitoring and management of

factors that trigger HABs is essential to protect

public health and the sustainability of aquatic

resources (Carias et al., 2024).

Based on various occurrences of HABs

in several bays worldwide, we have conducted

studies to predict the emergence of HABs based

on the type and abundance of phytoplankton in

the Northern part of Bone Bay, South Sulawesi,

Indonesia. This is a preliminary study because

information about HABs in the region, includ-

ing in other bays in Indonesia, is limited. This

is related to the fertility conditions of the waters

in the Bay. The analysis of available literature

shows limited data related to phytoplankton

type, including data on environmental param-

eters that affect it. However, the potential for

HABs to develop in this bay is very likely,

considering that Bone Bay is classified as fer-

tile due to the input of inorganic and organic

materials from anthropogenic activities, such as

ponds, agriculture, households, ports, and high

fishing activities.

MATERIAL AND METHODS

Time and Location of the study: The

research was conducted from May to July 2020.

The data was collected in NorthernBone Bay,

South Sulawesi, Indonesia. Four research loca-

tions (Fig. 1) are located in the coastal waters

of Palopo City: Tj Ringgit (TR), Passampa (PS)

from Luwu Regency, Siwa (SW), and Barang-

mamase (BM).

Research materials and design: The pri-

mary material used in this study is seawater

samples collected from four locations. Specific

environmental parameters are measured direct-

ly in the field, while others are analyzed in the

laboratory. This research is non-experimental.

The parameters observed without intervention

4Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

from the researchers included the types of phy-

toplankton HABs and non-HABs.

Analysis of phytoplankton HABs and

non-HABs: Seawater filtration was done

directly at the research site to enumerate phyto-

plankton type and abundance. A 50-liter water

sample was filtered using a plankton net with

a mesh size of 25 μm. The results of the sieve

containing phytoplankton in the plankton net

bucket were put into a sample bottle with a

volume of 100 ml, then preserved with five ml

of Lugol one N solution. The sample bottles

were placed in a cool box containing ice cubes

to be analyzed in the laboratory. The sweep-

ing method (census) calculates the type and

abundance of phytoplankton cells (Filatov &

Kirkpatrick, 2024). A total of one milliliter of

the filtered result was inserted into a 50 mm x

20 mm x 1 mm Sedgwick Rafter Cell (SRC) (de

Vries et al., 2024), using a scaled pipette. SRC

was observed using a binocular microscope

(Olympus CX21) at a magnification scale of 10

x 10. Standard references, such as Tomas (1997)

and Castellani & Edwards (2017), were used for

phytoplankton identification.

Measurement of in-situ and ex-situ envi-

ronmental parameters: Environmental param-

eters in situ include temperature, pH, salinity,

and current velocity. Each of these parameters

was measured using a thermometer for tem-

perature (oC), a pH meter for pH, a refrac-

tometer for salinity (ppt), and a drogue that

has been calibrated for current speed (m/s).

Other parameters were measured in the labo-

ratory, such as turbidity (NTU), which was

measured using the nephelometry method,

according to the instructions of Strickland and

Parsons (1972). The nutrient concentration

was measured according to methods devel-

oped by APHA (Rice et al., 2017); the nitrate

by the brucine method, while nitrite by sulfa-

nilamide, ammonium by phenate, orthophos-

phate by stannous chloride, and silicate by

molybdosilicate.

Statistical analysis: The data was analyzed

descriptively using tables and figures. One-way

Fig. 1. Research Location in Bone Bay.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

variance analysis (One-way ANOVA) (Chatzi

& Doody, 2023) was applied to test the abun-

dance of phytoplankton HABs based on loca-

tion differences. If ANOVA shows a significant

difference at a 95 % confidence level (α = 0.05),

the analysis continues with Tukey’s post-hoc

test (Juarros-Basterretxea et al., 2024). Before

conducting further tests, the parameters were

tested first through a normality test using Kol-

mogorov-Smirnov and Levene’s Test of Equality

(Fiandini et al., 2024). Multiple linear regres-

sion analysis (Ismail & El Zokm, 2023) was

applied to evaluate various parameters that sup-

ported the growth of HABs. The entire analysis

was done using SPSS 25 software (IBM Corp.,

2017) and Excel Stat 2017 (Addinsoft, 2017).

RESULTS

Environmental Parameters: Table 1 pres-

ents the results of measuring environmental

parameters, including temperature, salinity, pH,

current speed, turbidity, and nutrients (nitrate,

nitrite, ammonia, orthophosphate, and sili-

cate). Observations of various oceanographic

parameters were carried out to analyze the

suitability of environmental conditions with the

life of HABs in each research location. Based

on the measurement results, most of the values

of each parameter are within the range that

supports phytoplankton growth, including the

type of HABs. Based on environmental param-

eters, particularly nutrients, the water status

ranges from mesotrophic (phosphate: ortho-

phosphate) to eutrophic (total nitrogen: nitrate,

nitrite, ammonia) (Hakanson & Bryhn, 2008).

Phytoplankton Composition of Non-

HABs and HABs: The three classes of

phytoplankton identified in this study are Bacil-

lariophyceae, Dinophyceae, and Cyanophyceae.

Among the three classes, Bacillariophyceae has

the highest number of types, i.e., 19, while

Dinophyceae and Cyanophyceae have only four

and one type, respectively (Table 2 and Fig. 2).

The dominant types of phytoplankton

in this study include Bacteriastrum, Chae-

toceros, Leptocylindrus, Rhizosolenia, and

Table 1

Results of environmental parameter measurement.

Location

Parameter Nutrients (mg/L)

Station Temperature

(°C) Salinity (ppt) pH Current Speed

(m/det)

Turbidity

(NTU) Nitrate Nitrite Ammonia Orthophosphate Silicate

Tj Ringgit (TR) TR1 28.0 ± 0.00 15.3 ± 0.58 7.74 ± 0.02 0.39 ± 0.03 2.96 ± 0.23 0.04 ± 0.01 0.04 ± 0.00 0.60 ± 0.03 0.02 ± 0.00 0.00 ± 0.00

TR2 28.0 ± 0.00 23.3 ± 0.58 7.76 ± 0.01 0.28 ± 0.13 0.80 ± 0.10 0.03 ± 0.00 0.03 ± 0.00 0.70 ± 0.07 0.02 ± 0.00 0.00 ± 0.00

TR3 28.0 ± 0.00 17.7 ± 0.58 7.76 ± 0.02 0.18 ± 0.10 1.01 ± 0.22 0.02 ± 0.00 0.04 ± 0.00 0.80 ± 0.01 0.02 ± 0.00 0.00 ± 0.00

Passampa (PS) PS1 30.1 ± 0.00 28.0 ± 0.00 7.78 ± 0.01 0.16 ± 0.09 0.84 ± 0.50 0.05 ± 0.00 0.08 ± 0.02 0.89 ± 0.00 0.02 ± 0.00 0.01 ± 0.00

PS2 30.1 ± 0.00 28.7 ± 0.58 7.76 ± 0.01 0.21 ± 0.03 0.20 ± 0.14 0.03 ± 0.00 0.08 ± 0.02 0.69 ± 0.00 0.02 ± 0.00 0.01 ± 0.00

PS3 30.1 ± 0.00 28.3 ± 0.58 7.77 ± 0.02 0.10 ± 0.02 1.02 ± 1.43 0.09 ± 0.01 0.08 ± 0.00 0.65 ± 0.00 0.02 ± 0.00 0.02 ± 0.00

Siwa (SW) SW1 29.9 ± 0.06 29.3 ± 0.58 7.79 ± 0.02 0.16 ± 0.09 0.96 ± 0.81 0.04 ± 0.00 0.01 ± 0.01 0.63 ± 0.01 0.02 ± 0.00 0.02 ± 0.00

SW2 30.0 ± 0.06 28.3 ± 0.58 7.78 ± 0.01 0.21 ± 0.03 0.19 ± 0.04 0.03 ± 0.00 0.05 ± 0.01 0.54 ± 0.01 0.02 ± 0.00 0.01 ± 0.00

SW3 30.4 ± 0.61 30.3 ± 0.58 7.78 ± 0.00 0.10 ± 0.02 0.38 ± 0.16 0.03 ± 0.01 0.05 ± 0.01 0.53 ± 0.00 0.02 ± 0.00 0.01 ± 0.00

Barangmamase

(BM)

BM1 29.0 ± 0.00 24.7 ± 0.58 7.81 ± 0.032 0.11 ± 0.037 10.15 ± 0.15 0.05 ± 0.01 0.03 ± 0.02 0.54 ± 0.02 0.02 ± 0.00 0.01 ± 0.00

BM2 31.0 ± 0.00 23.3 ± 0.58 7.79 ± 0.01 0.07 ± 0.04 5.16 ± 0.14 0.05 ± 0.00 0.05 ± 0.03 0.49 ± 0.05 0.02 ± 0.00 0.01 ± 0.00

BM3 30.0 ± 0.06 25.3 ± 0.58 7.79 ± 0.01 0.06 ± 0.00 3.65 ± 0.55 0.08 ± 0.00 0.04 ± 0.01 0.86 ± 0.05 0.02 ± 0.00 0.01 ± 0.58

6Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

Thalassionema from the class Bacillariophyce-

ae, as well as Ceratium from the class Dinophy-

ceae (Table 2). All type identified are classified

as Non-HABs type phytoplankton.

From Table 2 and Fig. 2, it can be seen

that there was no single dominant type of

HABs during the study. Also, several taxa

type of phytoplankton HABs were detected,

although not in dominant amounts, such as

Pseudo-nitzschia of the class Bacillariophyceae,

Fig. 2. Number of taxa from Non-HABs and HABs.

Table 2

Number and Abundance of HABs and Non-HABs.

Type

Number Class Type Abundance (cell/L)

Tj Ringgit (TR) Passampa (PS) Siwa (SW) Barangmamase (BM)

1Bacillariophyceae Bacteriastrum* 222 1 583 16 18

2  Chaetoceros* 5 555 21 091 525 794

3  Coscinodiscus* 12 20 54 12

4  Cyclotella* 23 23 9 15

5  Dactyliosolen* 1 9 2

6  Ditylum* 5 12 11 10

7  Guinardia* 3 15 4 17

8  Hemiaulus* 2 24

9  Lauderia* 2

10  Leptocylindrus* 111 271 36 1 262

11  Nitzschia* 1 6 8 61

12  Odontella* 1 2

13  Pleurosigma* 1 6 14

14  Pseudo-nitzschia** 29 310 33 272

15  Rhizosolenia* 189 596 49 74

16  Skeletonema* 20 25 22 1 122

17  Synedra* 10 13 9 31

18  Thalassionema* 282 747 402 479

19  Triceratium* 1

Abundance of Type 6 463 24 713 1 197 4 211

Number of Type 14 14 18 18

20 Dinophyceae Ceratium* 125 7 71 29

21  Dinophysis** 31 3 11

22  Prorocentrum** 6 1 10 13

23  Protoperidinium** 33 27 27 33

Abundance of Type 195 38 119 75

Number of Type 4 4 4 3

24 Cyanophyceae Oscillatoria** 3 3 2 36

Abundance of Type 3 3 2 36

Number of Type 1 1 1 1

Total Abundance 6 661 24 755 1 318 4 322

Total Type 19 19 23 22

* Non HABs; ** HABs

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

Dinophysis, Prorocentrum, Protoperidinium of

the class Dinophyceae, and Oscillatoria of the

class Cyanophyceae.

Proportion of HAB abundance: The

results showed that the proportion of HABs

abundance was lower than that of non-HABs

(Fig. 2). In the TR and PS locations, the abun-

dance of HABs only reached 1.53 and 1.39 %,

while the abundance of Non-HABs reached

98.47 and 98.61 %, respectively. In SW and BM

locations, the proportion of HABs increased to

6.25 and 8.18 %, although non-HABs remained

dominant with a proportion of 93.75 and

91.82 % (Table 3 and Fig. 3).

There was no statistically significant dif-

ference (p > 0.05) based on the results of the

analysis of the variance of HABs abundance

between the locations studied (Table 3). These

findings indicate that the abundance of HABs

was considered uniform across sites during

the study.

Detection of Environmental Parameters

Affecting the Emergence of Phytoplankton

HABs: To ascertain the factors that cause the

emergence of phytoplankton HABs in Bone Bay

in the Northern part of South Sulawesi, a mul-

tiple linear regression analysis has been carried

out between the abundance of phytoplankton

HABs and various environmental parameters

such as temperature, salinity, pH, turbidity,

current speed, nitrate, and orthophosphate.

The test results showed that the environmen-

tal parameters had a real relationship (p =

0.14) with HABs (Table 4). Based on verifying

environmental parameters that affect HABs,

orthophosphate and salinity were found with a

determination coefficient (R2) of 61.1 %.

DISCUSSION

The results of the enumeration of phyto-

plankton type showed that the number of type

from the Bacillariophyceae class was more than

that of the Dinophyceae and Cyanophyceae

classes. The abundance of Bacillariophyceae

type is due to their ability to adapt to a variety

of aquatic environments, including freshwater

(Quevedo-Ortiz et al., 2024), marine (Hochfeld

& Hinners, 2024), and estuaria (Solórzano,

2024). This adaptability allows them to colo-

nize diverse habitats and respond to varying

environmental conditions. They can grow well

Table 3

ANOVA results of the abundance of HABs during the study.

AN O VA

The sum of Squares df Mean Square FSig.

Between Groups 198582.917 3 66194.306 3.057 0.092

Within Groups 173214.000 8 21651.750

Total 371796.917 11

Fig. 3. Proportion of abundance of Non-HABs and HABs:

(A) Tj Ringgit (TR); (B) Passampa (PS); (C) Siwa (SW); (D)

Barangmamase (BM).

8Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

in a wide range of nutrients and temperatures

(as in the case of this study), which supports

their rapid growth. In reproducing, they repro-

duce asexually through continuous cell divi-

sion (Krueger-Hadfield, 2024). In unfavorable

environmental conditions, they turn to sexual

reproduction, increasing cell counts and type

diversity (Persson et al., 2024). This is very

important for survival in a changing environ-

ment. The combination of asexual and sexual

reproduction contributes to a type of higher

diversity, which can enhance ecosystem stabil-

ity and resilience.

In contrast, the Dinophyceae and Cya-

nophyceae experience growth restriction that

depends on environmental conditions (Goven-

der & Jury, 2024; Lajnef et al., 2023). The type

of phytoplankton in these two classes are usu-

ally abundant in waters with low concentrations

of nutrients and warmer temperatures (Dory et

al., 2024). Thus, the diversity of the type tends

to be lower. In addition, their reproductive abil-

ity is also slower than Bacillariophyceae (Hara-

guchi et al., 2023).

Research conducted indicates that species

within the Bacillariophyceae class dominate

phytoplankton communities during certain

seasons, demonstrating their ability to adapt

to seasonal changes (Bouma-Gregson et al.,

2024). Selph et al. (2022) also noted that Bac-

illariophyceae exhibit better growth in nutri-

ent-rich conditions, with a rapid reproduction

capability through cell division. In contrast,

Dinophyceae and Cyanophyceae grow more

slowly and depend more on specific environ-

mental conditions. Furthermore, a study found

that Bacillariophyceae dominate phytoplankton

communities in estuaries, with a significantly

higher abundance compared to Dinophyceae

and Cyanophyceae, highlighting their reliance

on more specific environmental conditions

(Essa et al., 2024).

During the study, phytoplankton type

such as Bacteriastrum, Chaetoceros, Leptocylin-

drus, Rhizosolenia, and Thalassionema, which

are members of the class Bacillariophyceae

(diatoms), were predominantly found. This

dominance occurs because these type of phy-

toplankton can adapt to high concentrations

of nutrients (Kim et al., 2023). Under nutrient-

rich environmental conditions, they can bloom

rapidly in coastal waters (Zhu et al., 2024),

Table 4

Summary model and regression analysis of HABs phytoplankton abundance with various environmental parameters.

Model Summary

Model RR Square Adjusted R

Square

Std. Error of the

Estimate

1 0.595a0.354 0.289 0.29644

2 0.782b0.611 0.525 0.24243

a. Predictors: (Constant), Orthophosphate.

b. Predictors: (Constant), Orthophosphate, Salinity.

AN O VAa

Model Sum of Squares df Mean Square FSig.

1Regression 0.482 1 0.482 5.479 0.041b

Residual 0.879 10 0.088

Total 1.360 11

2Regression 0.831 2 0.416 7.073 0.014c

Residual 0.529 9 0.059

Total 1.360 11

a. Dependent Variable: HABs (Log10).

b. Predictors: (Constant), Orthophosphate.

c. Predictors: (Constant), Orthophosphate, Salinity.

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

including bays (Shaika et al., 2023), as in this

study. They can reproduce quickly through cell

division (asexual) and are highly resistant to

temperature fluctuations and salinity to thrive

in various conditions. These multiple factors

make them the most competitive and dominant

type of phytoplankton in coastal and marine

environments (Stewart et al., 2012).

Another ability of the class Bacillari-

ophyceae phytoplankton species is to form

dormant spores, especially Chaetoceros, when

environmental conditions become unfavorable

(for example, when nutrients are depleted or

temperatures change drastically). According to

Ishii et al. (2022), this type can form spores to

survive in poor environmental conditions and

remain on the seafloor or water column until

conditions improve. When nutrients are abun-

dant again, or temperatures return to optimal

conditions, these spores return to active cells

ready to multiply. This adaptation provides a

significant competitive advantage in coastal

waters, including bays (Command et al., 2023),

where environmental changes are frequent, as

it allows Chaetoceros to survive for long periods

and restart growth when conditions improve

(Kazmi et al., 2022).

Several type of phytoplankton in the class

Bacillariophycea have been known to have

endosymbiotic relationships with nitrogen-fix-

ing cyanobacteria, for example, Rhizosolenia

(Mutalipassi et al., 2021). This endosymbiosis

allows Rhizosolenia to take advantage of nitro-

gen from the atmosphere, especially when it

is less available in the water column (Mani-

gandan et al., 2024). This makes it superior in

nitrogen-deficient environments, especially in

more oligotrophic (nutrient-poor) open ocean

waters. Its ability to obtain nitrogen from this

symbiosis allows Rhizosolenia to thrive in envi-

ronments where other phytoplankton may be

limited by nitrogen deficiency (Martínez-Pérez

et al., 2024), making them more competitive

and often dominant.

Ceratium is a type of phytoplankton from

the class Dinophyceae, which was also pre-

dominantly found during the study. These

organisms can assimilate the available nutrients

available in the waters (Jachniak & Jaguś, 2023).

This causes it to develop quickly when an abun-

dant supply of nutrients, such as nitrogen and

phosphate, is often available in coastal waters,

including bays. Although they are not as fast

as diatoms in absorbing nutrients, Ceratium

can survive in nutrient-deficient environments,

which helps it thrive over extended periods,

especially when environmental conditions

change (Albin et al., 2022). These microorgan-

isms are commonly found in marine environ-

ments and can contribute to the occurrence

of algal blooms, which may impact aquatic

ecosystems. Additionally, they serve as pri-

mary producers in the food chain within these

aquatic ecosystems.

As a mixotroph (Yang et al., 2021), Cera-

tium can perform photosynthesis while obtain-

ing nutrients by consuming organic particles or

other microorganisms through phagocytosis.

This flexibility in nutrient acquisition allows it

to survive and even dominate in coastal waters

during nutrient scarcity. Under adverse condi-

tions, the organism can form cysts that enable

it to enter a dormant state and resume growth

when conditions improve (Trottet et al., 2018).

Nevertheless, its abundance is often lower than

diatoms (Vajravelu et al., 2018). Diatoms are

more efficient in utilizing nutrients such as

silica and have a faster reproduction rate in

nutrient-rich waters (Demir & Turkoglu, 2022).

During the study, several types of HABs

were detected, such as Pseudo-nitzschia of the

class Bacillariophyceae, Dinophysis, Prorocen-

trum, Protoperidinium of the class Dinophyce-

ae, and Oscillatoria of the class Cyanophyceae.

These HABs can produce toxins that harm

humans (Sha et al., 2021), disrupt ecosystems,

and degrade water quality (Heil & Muni-Mor-

gan, 2021). Its growth can be rapid because it is

triggered by nutrient-rich environmental con-

ditions caused by human activities, such as agri-

culture and waste disposal. These blooms can

cause significant economic impacts, especially

on fisheries and tourism (Igwaran et al., 2024).

Pseudo-nitzschia is a diatom that can pro-

duce domoic acid, a neurotoxin harmful to

humans and animals. Blooms of Pseudo-nitzschia

10 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

are often associated with the phenomenon of

Amnesic Shellfish Poisoning (ASP) (Twiner et

al., 2008). When shellfish consume this organ-

ism and store ASP toxins in their bodies and

then ingest them by humans, this can cause

health problems (Marques et al., 2010).

Dinophysis is known for its ability to pro-

duce okadaic acid, which causes Diarrhetic

Shellfish Poisoning (DSP) disease (Henigman

et al., 2024), while Prorocentrum is also associ-

ated with the same disease (Camacho-Muñoz

et al., 2021). Some of these two types can

cause seafood poisoning, such as shellfish, thus

threatening human health. Both growths are

often associated with increased nutrient avail-

ability, such as agricultural waste. When blooms

occur (104 cell/L) (Sidabutar et al., 2024), they

can also damage aquatic ecosystems through

decreased water quality and reduced oxygen

levels, potentially affecting the balance of the

ecosystem (Griffith & Gobler, 2020).

Oscillatoria is a cyanobacterium that can

produce toxins, such as microcystins, that harm

human health (Manganelli et al., 2023). Blooms

of Oscillatoria are frequent in nutrient-rich

waters and can result in a decrease in water

quality, as well as affect aquatic ecosystems

(Rattner et al., 2022).

In Indonesia, research on harmful algal

blooms (HAB) in coastal waters has been con-

ducted regularly since 1990. However, many

instances of algal blooms remain unrecorded or

unpublished. This highlights a gap in our under-

standing of this phenomenon and underscores

the need for better documentation to identify

potential patterns and trends. Several studies

have successfully documented the occurrence

of algal blooms and identified the key factors

that trigger these events. One significant find-

ing is that algal species can unexpectedly shift

from non-toxic to toxic, adding complexity

to managing and mitigating HAB impacts in

Indonesian waters (Sidabutar et al., 2024).

The emergence of HABs is important to

observe because they can produce dangerous

toxins and threaten human health and aquatic

ecosystems (Zingone et al., 2021). Its rapid

growth can disrupt the balance of ecosystems,

reduce water quality, and damage the fishing

industry. By understanding the factors that

trigger them to bloom, mitigation strategies can

be designed to minimize their adverse impacts,

protect public health, and maintain aquatic

biodiversity (Pal et al., 2020).

The results showed that the proportion

of HABs abundance in all locations studied

was lower than that of Non-HABs, with the

abundance of HABs in TR and PS locations

only reaching 1.53 and 1.39 %, respectively.

The dominance of non-HABs in these two

locations, which reached 98.47 and 98.61 %,

indicates that environmental conditions are

suspected to be more supportive of the growth

of non-HABs.

In contrast, in SW and BM locations, the

proportion of HABs increased to 6.25 and 8.18

%. However, non-HABs still dominate with

proportions of 93.75 and 91.82 %. Although

there was an increase in the abundance of

HABs in the SW and BM locations, based on

the results of the variance analysis, the abun-

dance of HABs was considered uniform in all

locations during the study.

The increase in the proportion of HABs

in SW and BM locations indicates a change

in environmental conditions that can trigger

their growth. Although the abundance of HABs

was still relatively low, this increase must be

observed as an early sign of more significant

bloom potential. It is important to know that

negative impacts, such as seafood poisoning

and ecosystem damage, can be anticipated

(Organización de las Naciones Unidas para la

Agricultura y la Alimentación, la Comisión

Oceanográfica Intergubernamental & el Organ-

ismo Internacional de Energía Atómica, 2023)

A better understanding of the patterns and

factors influencing the growth of HABs is cru-

cial for the sustainable management of aquatic

resources (Obaid et al., 2024).

The increase in the proportion of HABs in

aquatic waters indicates that various environ-

mental parameters support their growth. In this

context, the regression analysis presented in

Table 3 provides strong evidence of the relation-

ship between environmental conditions and the

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

occurrence of HABs (Pseudo-nitzschia of the

class Bacillariophyceae, Dinophysis, Prorocen-

trum, Protoperidinium of the class Dinophyce-

ae, and Oscillatoria of the class Cyanophyceae).

Two key parameters identified, namely ortho-

phosphate and salinity, play an important role

in facilitating the growth of this harmful algae.

A deep understanding of these relationships is

essential to formulate more effective strategies

for managing aquatic resources.

Orthophosphates, as one of the forms of

phosphorus available to phytoplankton, includ-

ing HABs, serve as the primary nutrients that

support their growth. The availability of ortho-

phosphate often increases due to human activi-

ties (Tambaru et al., 2024), such as intensive

agricultural activities, domestic waste, and

pollution from industry. When phosphorus

accumulates in large quantities in the waters,

conditions become ideal for the growth of

HABs (Glibert et al., 2020). This process can

lead to rapid proliferation, thereby increasing

the risk of blooms (Brown et al., 2020). In many

cases, high orthophosphate concentrations can

contribute to the development of HABs, result-

ing in seafood poisoning and adverse ecosys-

tem impacts (Dammak-Walha et al., 2021),

among other negative consequences.

In addition to orthophosphates, salinity

is an important parameter that can influence

the appearance of HABs. Appropriate salinity

can affect the growth of HABs, allowing them

to adapt and thrive in different environments

(Shi et al., 2024). Some HABs show a high

tolerance to salinity variations to survive and

reproduce under changing conditions (Giesler

et al., 2023).

Each type of phytoplankton, including

HABs, has an optimal salinity range to multiply

efficiently (Jiang et al., 2022). A change in salin-

ity can trigger the proliferation of certain type of

phytoplankton that are more resistant to these

conditions (Röthig et al., 2023). For example,

in waters with low salinity due to river runoff

from land, there is often an increase in nutri-

ents supporting adaptive HAB-type growth,

such as Dinophysis and Prorocentrum. In con-

trast, other type are more resistant to salinity

that may predominate in high-salinity environ-

ments. These factors interact with temperature,

light, and nutrient changes, all of which affect

the dynamics of aquatic ecosystems.

HABs have a wider salinity tolerance and

can take advantage of more extreme environ-

mental conditions than non-HABs (Hernando

et al., 2020). Some HAB type can survive and

reproduce in less-than-ideal conditions, such

as high or low salinity and fluctuations in

temperature and nutrients. In contrast, non-

HABs grow in more stable waters with a more

consistent salinity range (Xu et al., 2024). These

differences make HABs type more flexible in

responding to environmental changes, often

causing blooms that damage ecosystems and

human health. Salinity values recorded in the

study area ranged from 15.3 to 30.3 ppt.

The combination of the high availabil-

ity of orthophosphate and extreme changes in

salinity creates a very conducive environment

for the growth of HABs (Bouma-Gregson et

al., 2024). Therefore, monitoring these two

parameters is crucial to understanding the

dynamics of HABs and formulating appropriate

mitigation measures. By monitoring changes in

orthophosphate concentrations and salinity, we

can identify the potential for early blooms. This

allows authorities and stakeholders to manage

water quality and protect ecosystems proac-

tively. Given the negative impacts that HABs

can have, such as seafood poisoning and habi-

tat destruction, a better understanding of the

factors influencing their growth is key to the

sustainable management of aquatic resources.

Thus, more effective prevention and manage-

ment measures can be implemented to reduce

the negative impact of this phenomenon.

Comprehensive mitigation measures are

needed to maintain the ecosystem’s sustain-

ability in Bone Bay. Reducing nutrient sources

from agricultural, fishery, and industrial waste

is essential. Regular monitoring of water qual-

ity, education, and community engagement

are also crucial to addressing the negative

impacts of HABs. With collaborative efforts,

we can restore and protect coastal aquatic eco-

systems to remain productive and healthy for

12 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

the sake of marine survival and human welfare

in the future.

In conclusion, this study shows that the

phytoplankton that caused Harmful Algal

Blooms (HABs) identified included Pseudo-

nitzschia (Bacillariophyceae), Dinophysis, Pro-

rocentrum, Protoperidinium (Dinophyceae),

and Oscillatoria (Cyanophyceae). Although the

proportion of HABs abundance was lower than

that of non-HABs phytoplankton across sites,

the increased abundance of HABs in some

areas, such as SW and BM, indicated the poten-

tial for future blooms. Therefore, monitoring

environmental parameters, especially ortho-

phosphate concentration and salinity as the

two main factors influencing the occurrence of

HABs, is very important. Through this moni-

toring, mitigation measures can be formulated,

such as reducing nutrient sources from agricul-

tural, fishery, and industrial wasteand imple-

menting regular water quality monitoring. This

step aims to protect the aquatic ecosystem

while maintaining public health. This research

provides important insights into the need for

sustainable management of marine resources

in Bone Bay.

Activities in Bone Bay that can increase the

nutrient load discharged into the waters include

aquaculture, agriculture, and household activi-

ties. Agricultural runoff, such as fertilizers and

pesticides, can flow into the waters, increasing

nutrient levels such as nitrogen and phospho-

rus. Agricultural areas near Bone Bay, especially

those using chemical fertilizers, can potentially

contribute nutrient waste to the waters. Waste

from household activities and ports also con-

tributes to the increased nutrient load. Data on

nutrient levels in runoff from agricultural land

and domestic waste are crucial for understand-

ing the risks of Harmful Algal Blooms (HAB)

in Bone Bay, as increased nutrients can trig-

ger the growth of harmful phytoplankton that

negatively impacts ecosystem and food health.

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

followed all pertinent ethical and legal proce-

dures and requirements. All financial sources

are fully and clearly stated in the acknowledg-

ments section. A signed document has been

filed in the journal archives.

ACKNOWLEDGMENTS

We want to thank the Rector of Hasa-

nuddin University, Makassar, Indonesia, for

his permission to provide research grants

through the Institute for Research and Com-

munity Service (LP2M) of Hasanuddin Univer-

sity under the 2024 Collaborative Fundamental

Research scheme.

REFERENCES

Addinsoft. (2017). XLSTAT (Version 2017) [Computer

software]. https://www.xlstat.com

Albin, K. J., Jyothibabu, R., Alok, K. T., Santhikrishnan,

S., Sarath, S., Sudheesh, V., Sherin, C. K., Balachan-

dran, K. K., Asha Devi, C. R., & Gupta, G. V. M.

(2022). Distinctive phytoplankton size responses to

the nutrient enrichment of coastal upwelling and win-

ter convection in the eastern Arabian Sea. Progress in

Oceanography, 203, 102779. https://doi.org/10.1016/J.

POCEAN.2022.102779

Álvarez, S., Brown, C. E., García Diaz, M., O’Leary, H., &

Solís, D. (2024). Non-linear impacts of harmful algae

blooms on the coastal tourism economy. Journal of

Environmental Management, 351, 119811. https://doi.

org/10.1016/J.JENVMAN.2023.119811

Anderson, D. M., Fensin, E., Gobler, C. J., Hoeglund, A. E.,

Hubbard, K. A., Kulis, D. M., Landsberg, J. H., Lefe-

bvre, K. A., Provoost, P., Richlen, M. L., Smith, J. L.,

Solow, A. R., & Trainer, V. L. (2021). Marine harmful

algal blooms (HABs) in the United States: History,

current status and future trends. Harmful Algae, 102,

101975. https://doi.org/10.1016/J.HAL.2021.101975

Basnayaka, C., Somasiri, M., Ahsan, A., Nazeer, Z., Thilini,

N., Bandara, S., & Fernando, E. Y. (2024). Marine pho-

tosynthetic microbial fuel cell for circular renewable

power production. Bioenergy Research, 17(4), 2299–

2310. https://doi.org/10.1007/s12155-024-10768-x

Bouma-Gregson, K., Bosworth, D., Flynn, T. M., Magui-

re, A., Rinde, J., & Hartman, R. (2024). Delta

blue(green)s: The effect of drought and drought-

management actions on microcystis in the Sacra-

mento–San Joaquin Delta. San Francisco Estuary and

Watershed Science, 22(1). https://doi.org/10.15447/

SFEWS.2024V22ISS1ART2

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

Boyd, P. W., Arrigo, K. R., Ardyna, M., Halfter, S., Huck-

stadt, L., Kuhn, A. M., Lannuzel, D., Neukermans,

G., Novaglio, C., Shadwick, E. H., Swart, S., & Tho-

malla, S. J. (2024). The role of biota in the Southern

Ocean carbon cycle. Nature Reviews Earth & Envi-

ronment, 5(5), 390–408. https://doi.org/10.1038/

s43017-024-00531-3

Brown, A. R., Lilley, M., Shutler, J., Lowe, C., Artioli,

Y., Torres, R., Berdalet, E., & Tyler, C. R. (2020).

Assessing risks and mitigating impacts of harmful

algal blooms on mariculture and marine fisheries.

Reviews in Aquaculture, 12(3), 1663–1688. https://doi.

org/10.1111/RAQ.12403

Bui, Q. T. N., Pradhan, B., Kim, H. S., & Ki, J. S. (2024).

Environmental factors modulate saxitoxins (stxs) pro-

duction in toxic dinoflagellate alexandrium: an upda-

ted review of stxs and synthesis gene aspects. Toxins,

16(5), 210. https://doi.org/10.3390/TOXINS16050210

Camacho-Muñoz, D., Praptiwi, R. A., Lawton, L. A.,

& Edwards, C. (2021). High value phycotoxins

from the dinoflagellate prorocentrum. Frontiers in

Marine Science, 8, 638739. https://doi.org/10.3389/

fmars.2021.638739

Carias, J., Vásquez-Lavín, F., Barrientos, M., Ponce Oliva, R.

D., & Gelcich, S. (2024). Economic valuation of Har-

mful Algal Blooms (HAB): Methodological challen-

ges, policy implications, and an empirical application.

Journal of Environmental Management, 365, 121566.

https://doi.org/10.1016/J.JENVMAN.2024.121566

Castellani, C., & Edwards, M. (2017). Marine Plankton: A

practical guide to ecology, methodology, and taxonomy.

Oxford University Press. https://doi.org/10.1093/

oso/9780199233267.001.0001

Chatterjee, S., & More, M. (2023). Cyanobacterial harmful

algal bloom toxin microcystin and increased vibrio

occurrence as climate-change-induced biological co-

stressors: exposure and disease outcomes via their

interaction with gut–liver–brain axis. Toxins, 15(4),

289. https://doi.org/10.3390/TOXINS15040289

Chatzi, A., & Doody, O. (2023). The one-way ANOVA test

explained. Nurse Researcher, 31(3), 8–14. https://doi.

org/10.7748/NR.2023.E1885

Command, R. J., De Leo, F. C., McKenzie, C. H., & Robert,

K. (2023). A first look at megabenthic commu-

nity responses to seasonal change using the new

Holyrood Subsea Observatory in Conception Bay,

NL. Progress in Oceanography, 216, 103071. https://

doi.org/10.1016/J.POCEAN.2023.103071

Dammak-Walha, L., Hamza, A., Abdmouleh Keskes, F.,

Cibic, T., Mechi, A., Mahfoudi, M., & Sammari, C.

(2021). Heavy metals accumulation in environmental

matrices and their influence on potentially harmful

dinoflagellates development in the Gulf of Gabes

(Tunisia). Estuarine, Coastal and Shelf Science, 254,

107317. https://doi.org/10.1016/J.ECSS.2021.107317

de Vries, J., Monteiro, F., Langer, G., Brownlee, C., & Whe-

eler, G. (2024). A critical trade-off between nitrogen

quota and growth allows Coccolithus braarudii life

cycle phases to exploit varying environment. Biogeos-

ciences, 21(7), 1707–1727. https://doi.org/10.5194/

BG-21-1707-2024

Demir, E. İ., & Turkoglu, M. (2022). Temporal variations

of phytoplankton community and their correlation

with environmental factors in the coastal waters of

the Çanakkale Strait in 2018. Oceanologia, 64(1), 176–

197. https://doi.org/10.1016/J.OCEANO.2021.10.003

Dory, F., Nava, V., Spreafico, M., Orlandi, V., Soler, V., &

Leoni, B. (2024). Interaction between temperature

and nutrients: How does the phytoplankton commu-

nity cope with climate change? Science of the Total

Environment, 906, 167566. https://doi.org/10.1016/J.

SCITOTENV.2023.167566

Selph, K. E., Swalethorp, R., Stukel, M. R., Kelly, T. B.,

Knapp, A. N., Fleming, K., Hernandez, T., & Landry,

M. R. (2022). Phytoplankton Community Composi-

tion and Biomass in the Oligotrophic Gulf of Mexico.

Journal of Plankton Research, 44(5), 618–37. https://

doi.org/10.1093/plankt/fbab006

Essa, D. I., Elshobary, M. E., Attiah, A. M., Salem, Z.

E., Keshta, A. E., & Edokpayi, J. N. (2024). Asses-

sing phytoplankton populations and their

relation to water parameters as early alerts and bio-

logical indicators of the aquatic pollution. Ecologi-

cal Indicators, 159, 111721. https://doi.org/10.1016/J.

ECOLIND.2024.111721

Feng, L., Wang, Y., Hou, X., Qin, B., Kuster, T., Qu, F., Chen,

N., Paerl, H. W., & Zheng, C. (2024). Harmful algal

blooms in inland waters. Nature Reviews Earth &

Environment, 5(9), 631–644. https://doi.org/10.1038/

s43017-024-00578-2

Fiandini, M., Nandiyanto, A. B. D., Al Husaeni, D. F., Al

Husaeni, D. N., & Mushiban, M. (2024). How to

calculate statistics for significant difference test using

SPSS: Understanding students comprehension on

the concept of steam engines as power plant. Indone-

sian Journal of Science and Technology, 9(1), 45–108.

https://doi.org/10.17509/ijost.v9i1.64035

Filatov, D. A., & Kirkpatrick, M. (2024). How does evolution

work in superabundant microbes? Trends in Micro-

biology, 32(9), 836–846. https://doi.org/10.1016/J.

TIM.2024.01.009

Giesler, J. K., Lemley, D. A., Adams, J. B., & Moorthi, S.

D. (2023). Interactive effects of salinity, temperature

and food web configuration on performance and har-

mfulness of the raphidophyte Heterosigma akashiwo.

Frontiers in Marine Science, 10, 1244639. https://doi.

org/10.3389/fmars.2023.1244639

Glibert, P. M., Maranger, R., Sobota, D. J., & Bouwman,

L. (2020). Further evidence of the Haber-Bosch-

Harmful Algal Bloom (HB-HAB) link and the risk

14 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

of suggesting HAB control through phosphorus

reductions only. Just Enough Nitrogen: Perspectives

on How to Get There for Regions with Too Much

and Too Little Nitrogen (pp. 255–282). https://doi.

org/10.1007/978-3-030-58065-0_17

Govender, Y., & Jury, M. R. (2024). Environmental controls

on bioluminescent dinoflagellate density in Laguna

Grande, Fajardo, Puerto Rico. Revista de Biología

Tropical, 72(1), e56729. https://doi.org/10.15517/rev.

biol.trop.v72i1.56729

Griffith, A. W., & Gobler, C. J. (2020). Harmful algal

blooms: a climate change co-stressor in marine and

freshwater ecosystems. Harmful Algae, 91, 101590.

https://doi.org/10.1016/j.hal.2019.03.008

Håkanson, L., & Bryhn, A. C. (2008). Eutrophication in the

Baltic Sea: Present situation, nutrient transport proces-

ses, remedial strategies. Springer-Verlag.

Hallegraeff, G. M., Anderson, D. M., Davidson, K., Giane-

lla, F., Hansen, P. J., Hegaret, H., Iwataki, M., Larsen,

T. O., Mardones, J., MacKenzie, L., & Rensel, J. E.

(2023). Fish-killing marine algal blooms: Causative

organisms, ichthyotoxic mechanisms, impacts and miti-

gation [Technical report]. UNESCO - IOC/SCOR.

https://doi.org/10.25607/OBP-1964

Haraguchi, L., Kraft, K., Ylöstalo, P., Kielosto, S., Hällfors,

H., Tamminen, T., & Seppälä, J. (2023). Trait Respon-

se of Three Baltic Sea Spring Dinoflagellates to Tem-

perature, Salinity, and Light Gradients. Frontiers in

Marine Science, 10, 1156487. https://doi.org/10.3389/

fmars.2023.1156487

Heil, C. A., & Muni-Morgan, A. L. (2021). Florida’s har-

mful algal bloom (HAB) problem: escalating risks

to human, environmental and economic health with

climate change. Frontiers in Ecology and Evolution,

9, 646080. https://doi.org/10.3389/fevo.2021.646080

Henigman, U., Mozetič, P., Francé, J., Knific, T., Vadnjal, S.,

Dolenc, J., Kirbiš, A., & Biasizzo, M. (2024). Okadaic

acid as a major problem for the seafood safety (Myti-

lus galloprovincialis) and the dynamics of toxic phyto-

plankton in the Slovenian coastal sea (Gulf of Trieste,

Adriatic Sea). Harmful Algae, 135, 102632. https://doi.

org/10.1016/j.hal.2024.102632

Hernando, M., Varela, D. E., Malanga, G., Almandoz, G.

O., & Schloss, I. R. (2020). Effects of climate-induced

changes in temperature and salinity on phytoplankton

physiology and stress responses in coastal Antarc-

tica. Journal of Experimental Marine Biology and

Ecology, 530–531, 151400. https://doi.org/10.1016/J.

JEMBE.2020.151400

Hochfeld, I., & Hinners, J. (2024). Evolutionary adaptation

to steady or changing environments affects compe-

titive outcomes in marine phytoplankton. Limnology

and Oceanography, 69(5), 1172–1186. https://doi.

org/10.1002/LNO.12559

IBM Corp. (2017). IBM SPSS Statistics for Windows

(Version 25.0) [Computer software]. Armonk,

NY: IBM Corp. https://www.ibm.com/analytics/

spss-statistics-software

Igwaran, A., Kayode, A. J., Moloantoa, K. M., Khetsha, Z.

P., & Unuofin, J. O. (2024). Cyanobacteria harmful

algae blooms: causes, impacts, and risk management.

Water, Air, and Soil Pollution, 235(1), 1–26. https://

doi.org/10.1007/s11270-023-06782-y

Ishii, K. I., Matsuoka, K., Imai, I., & Ishikawa, A. (2022).

Life Cycle Strategies of the Centric Diatoms in a

Shallow Embayment Revealed by the Plankton Emer-

gence Trap/Chamber (PET Chamber) Experiments.

Frontiers in Marine Science, 9, 889633. https://doi.

org/10.3389/fmars.2022.889633

Ismail, M. M., & El Zokm, G. M. (2023). Evaluation of the

response of phytoplankton communities to heavy

metal stresses using multi-statistical approaches,

Alexandria coast, Egypt. International Journal of Envi-

ronmental Science and Technology, 20(12), 13595–

13608. https://doi.org/10.1007/s13762-023-04914-9

Jachniak, E., & Jaguś, A. (2023). Assessment of the trophic

state of the Soła River dam cascade, Polish Car-

pathians: a comparison of the methodology. Scien-

tific Reports, 13(1), 1–17. https://doi.org/10.1038/

s41598-023-33040-2

Jiang, T., Wu, G., Niu, P., Cui, Z., Bian, X., Xie, Y., Shi,

H., Xu, X., & Qu, K. (2022). Short-term changes in

algal blooms and phytoplankton community after

the passage of Super Typhoon Lekima in a temperate

and inner sea (Bohai Sea) in China. Ecotoxicology

and Environmental Safety, 232, 113223. https://doi.

org/10.1016/J.ECOENV.2022.113223

Juarros-Basterretxea, J., Aonso-Diego, G., Postigo, Á., Mon-

tes-Álvarez, P., Menéndez-Aller, Á., & García-Cueto,

E. (2024). Post-hoc tests in one-way ANOVA: the case

for normal distribution. Methodology, 20(2), 84–99.

https://doi.org/10.5964/METH.11721

Kabir, M., Habiba, U. E., Khan, W., Shah, A., Rahim, S., De

los Ríos-Escalante, P. R., Farooqi, Z.-U.-R., Ali, L., &

Shafiq, M. (2023).Climate change due to increasing

concentration of carbon dioxide and its impacts on

environment in the 21st century: a mini review. Jour-

nal of King Saud University – Science, 35(5), 102693.

https://doi.org/10.1016/j.jksus.2023.102693

Kazmi, S. S. U. H., Yapa, N., Karunarathna, S. C., & Suwan-

narach, N. (2022). Perceived intensification in har-

mful algal blooms is a wave of cumulative threat to the

aquatic ecosystems. Biology, 2022, 11(6), 852. https://

doi.org/10.3390/BIOLOGY11060852

Kim, J. H., Ajani, P. A., Murray, S. A., Kang, S. M., Kim, S.

H., Lim, H. C., Teng, S. T., Lim, P. T., & Park, B. S.

(2023). Abiotic and biotic factors controlling sexual

reproduction in populations of Pseudo-nitzschia

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

pungens (Bacillariophyceae). Harmful Algae, 123,

102392. https://doi.org/10.1016/J.HAL.2023.102392

Krueger-Hadfield, S. A. (2024). Let’s talk about sex: Why

reproductive systems matter for understanding algae.

Journal of Phycology, 60(3), 581–597. https://doi.

org/10.1111/JPY.13462

Kuroda, H., Takagi, S., Azumaya, T., & Hasegawa, N.

(2024). Spatiotemporal Variability of Satellite-Derived

Abundance of Karenia Spp. during 2021 in Shelf

Waters along the Pacific Coast of Hokkaido, Japan.

Frontiers in Marine Science, 11, 1452762. https://doi.

org/10.3389/fmars.2024.1452762

Lajnef, R., Quéméneur, M., Abdennadher, M., Dammak

Walha, L., Hamza, A., Belhassen, M., & Bellaaj Zoua-

ri, A. (2023). Prokaryotic diversity and dynamics

during dinoflagellate bloom decays in coastal tunisian

waters. Diversity, 15(2), 273. https://doi.org/10.3390/

d15020273

Lan, J., Liu, P., Hu, X., & Zhu, S. (2024). Harmful algal

blooms in eutrophic marine environments: causes,

monitoring, and treatment. Water, 16(17), 2525.

https://doi.org/10.3390/W16172525

Latasa, M., Scharek, R., Morán, X. A. G., Gutiérrez-

Rodríguez, A., Emelianov, M., Salat, J., Vidal, M.,

& Estrada, M. (2022). Dynamics of phytoplank-

ton groups in three contrasting situations of the

open NW Mediterranean Sea revealed by pigment,

microscopy, and flow cytometry analyses. Progress in

Oceanography, 201, 102737. https://doi.org/10.1016/J.

POCEAN.2021.102737

Li, X. Y., Yu, R. C., Richardson, A. J., Sun, C., Eriksen,

R., Kong, F. Z., Zhou, Z. X., Geng, H. X., Zhang,

Q. C., & Zhou, M. J. (2023). Marked shifts of har-

mful algal blooms in the Bohai Sea linked with

combined impacts of environmental changes. Har-

mful Algae, 121, 102370. https://doi.org/10.1016/J.

HAL.2022.102370

Manganelli, M., Testai, E., Tazart, Z., Scardala, S., &

Codd, G. A. (2023). Co-occurrence of taste and

odor compounds and cyanotoxins in cyanobac-

terial blooms: emerging risks to human health?

Microorganisms, 11(4), 872. https://doi.org/10.3390/

MICROORGANISMS11040872

Manigandan, V., Muthukumar, C., Shah, C., Logesh, N.,

Sivadas, S. K., Ramu, K., & Ramana Murthy, M. V.

(2024). Phylogenetic affiliation of Pedinomonas nocti-

lucae and green Noctiluca scintillans nutritional dyna-

mics in the Gulf of Mannar, Southeastern Arabian

Sea. Protist, 175(2), 126019. https://doi.org/10.1016/J.

PROTIS.2024.126019

Marques, A., Nunes, M. L., Moore, S. K., & Ström, M.

S. (2010). Climate change and seafood safety:

Human health implications. Food Research Interna-

tional, 43(7), 1766–1779. https://doi.org/10.1016/j.

foodres.2010.02.010

Martínez-Pérez, C., Zweifel, S. T., Pioli, R., & Stocker, R.

(2024). Space, the final frontier: The spatial compo-

nent of phytoplankton-bacterial interactions. Mole-

cular Microbiology, 122(3). https://doi.org/10.1111/

mmi.15293

Mutalipassi, M., Riccio, G., Mazzella, V., Galasso, C.,

Somma, E., Chiarore, A., de Pascale, D., & Zupo, V.

(2021). Symbioses of cyanobacteria in marine envi-

ronments: ecological insights and biotechnological

perspectives. Marine Drugs, 19(4), 227. https://doi.

org/10.3390/marine-drugs19040227

Naselli-Flores, L., & Padisák, J. (2023). Ecosystem services

provided by marine and freshwater phytoplankton.

Hydrobiologia, 850(12–13), 2691–2706. https://doi.

org/10.1007/s10750-022-04795-y

Obaid, A. A., Adam, E. M., Ali, K. A., & Abiye, T. A. (2024).

Time-series analysis of water-quality factors enhan-

cing harmful algal blooms (HABs): a study integrating

in-situ and satellite data, Vaal Dam, South Africa.

Water, 16(5), 764. https://doi.org/10.3390/w16050764

Organización de las Naciones Unidas para la Agricultura

y la Alimentación, Comisión Oceanográfica Intergu-

bernamental, & Organismo Internacional de Ener-

gía Atómica. (2023). Joint FAO-IOC-IAEA technical

guidance for the implementation of early warning

systems for harmful algal blooms [Fisheries and

Aquaculture Technical Paper No. 690]. FAO. https://

doi.org/10.4060/cc4794en

Ou, L. J., Wang, Z., Ding, G. M., Han, F. X., Cen, J. Y.,

Dai, X. F., Li, K. Q., & Lu, S. H. (2024). Organic

nutrient availability and extracellular enzyme activi-

ties influence harmful algal bloom proliferation in a

coastal aquaculture area. Aquaculture, 582, 740530.

https://doi.org/10.1016/j.aquaculture.2023.740530

Pal, M., Yesankar, P. J., Dwivedi, A., & Qureshi, A. (2020).

Biotic control of harmful algal blooms (HABs):

A brief review. Journal of Environmental Mana-

gement, 268, 110687. https://doi.org/10.1016/J.

JENVMAN.2020.110687

Parra-Saldivar, R., Melchor-Martínez, E. M., Oh, J.-W.,

Shiv, S., Pushparaj, C., Muthu, M., & Gopal, J. (2023).

Review of harmful algal blooms (HABs) causing mari-

ne fish kills: toxicity and mitigation. Plants, 12(23),

3936. https://doi.org/10.3390/PLANTS12233936

Persson, A., Smith, B. C., Alix, J. H., & Wikfors, G. H.

(2024). Properties and behavior of sexual life stages

underlying dinoflagellate hab events of cyst-produ-

cing species that disrupt fisheries and aquaculture.

Reviews in Fisheries Science & Aquaculture, 32(2),

171–188. https://doi.org/10.1080/23308249.2023.226

8715

Quevedo-Ortiz, G., Fernández-Calero, J. M., Cañedo-

Argüelles, M., von Schiller, D., Fortuño, P., Bonada,

N., & Gomà, J. (2024). An experimental study to

assess resistance and resilience strategies of freshwater

16 Revista de Biología Tropical, ISSN: 2215-2075 Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

diatoms to cope with drying in Mediterranean tem-

porary rivers. Hydrobiologia, 851(17), 4293–4306.

https://doi.org/10.1007/s10750-024-05585-4

Rajapaksha, R. P., Wu, M. L., Wang, Y. T., Bandara, G.,

Atapaththu, K. S. S., & Wang, Y. S. (2024). Long-term

alterations of nutrient dynamics and phytoplank-

ton communities in Daya Bay, South China Sea.

Marine Pollution Bulletin, 208, 116955. https://doi.

org/10.1016/J.MARPOLBUL.2024.116955

Rattner, B. A., Wazniak, C. E., Lankton, J. S., McGowan, P.

C., Drovetski, S. V., & Egerton, T. A. (2022). Review

of harmful algal bloom effects on birds with implica-

tions for avian wildlife in the Chesapeake Bay region.

Harmful Algae, 120, 102319. https://doi.org/10.1016/J.

HAL.2022.102319

Röthig, T., Trevathan-Tackett, S. M., Voolstra, C. R., Ross,

C., Chaffron, S., Durack, P. J., Warmuth, L. M., &

Sweet, M. (2023). Human-induced Salinity Changes

Impact Marine Organisms and Ecosystems. Glo-

bal Change Biology, 29(17), 4731–49. https://doi.

org/10.1111/gcb.16859

Salmaso, N., & Tolotti, M. (2021). Phytoplankton and

anthropogenic changes in pelagic environments.

Hydrobiologia, 848(1), 251–284. https://doi.

org/10.1007/s10750-020-04323-w

Sarkar, S. D., Sarkar, U. K., Naskar, M., Roy, K., Bose, A. K.,

Nag, S. K., Karnatak, G., & Das, B. K. (2021). Effect of

Climato-Environmental Parameters on Chlorophyll

a Concentration in the Lower Ganga Basin, India.

Revista de Biología Tropical, 69(1), 60–76. https://doi.

org/10.15517/rbt.v69i1.42731

Sha, J., Xiong, H., Li, C., Lu, Z., Zhang, J., Zhong, H.,

Zhang, W., & Yan, B. (2021). Harmful algal blooms

and their eco-environmental indication. Chemos-

phere, 274, 129912. https://doi.org/10.1016/j.

chemosphere.2021.129912

Shaika, N. A., Alhomaidi, E., Sarker, M. M., An Nur, A.,

Sadat, M. A., Awal, S., Mostafa, G., Hasan, S. J.,

Mahmud, Y., & Khan, S. (2023). Winter bloom of

marine cyanobacterium, trichodesmium erythraeum

and its relation to environmental factors. Sustainabi-

lity, 15(2), 1311. https://doi.org/10.3390/SU15021311

Shi, X., Zou, Y., Zhang, Y., Ding, G., Xiao, Y., Lin, S., &

Chen, J. (2024). Salinity decline promotes growth

and harmful blooms of a toxic alga by diverting car-

bon flow. Global Change Biology, 30(6). https://doi.

org/10.1111/GCB.17348

Sidabutar, T., Srimariana, E. S., Cappenberg, H., & Wouthu-

yzen, S. (2024). Comprehensive analysis of harmful

algal blooms in indonesia: from occurrence to

impact. BIO Web of Conferences, 87, 02003. https://

doi.org/10.1051/BIOCONF/20248702003

Siegel, D. A., Devries, T., Cetinić, I., & Bisson, K. M.

(2023). Quantifying the ocean’s biological pump and

its carbon cycle impacts on global scales. Annual

Review of Marine Science, 15, 329–356. https://doi.

org/10.1146/annurev-marine-040722-115226

Strickland, J. D. H., & Parsons, T. R. (1972). A Practical

Handbook of Seawater Analysis. Bulletin of the Fishe-

ries Research Board of Canada, 167, 1–310.

Solórzano, G. G., Fernández, J. M. G., & Zuno, S. A. F.

(2024). Phytoplankton from a brackish lagoon in

the central region of Veracruz, Mexico. Revista de

Biología Tropical, 72(1), e51160–e51160. https://doi.

org/10.15517/REV.BIOL.TROP..V72I1.51160

Rice, E. W., Baird, R. B., Eaton, A. D., & Clesceri, L. S.

(2017). Standard Methods for the Examination of

Water and Wastewater. Standard Methods. https://

www.standardmethods.org/

Stewart, J., Miller, M., Audo, C., & Stewart, G. (2012).

Using cluster analysis to identify patterns in students’

responses to contextually different conceptual pro-

blems. Physical Review Special Topics - Physics Educa-

tion Research, 8(2), 020112. https://doi.org/10.1103/

PhysRevSTPER.8.020112

Tambaru, R., Burhanuddin, A. I., Haris, A., Amran, M. A.,

Massinai, A., Muhiddin, A. H., Yaqin, K., Firman, &

Yuliana. (2024). Diversity and abundance of phyto-

plankton in Bone Bay, South Sulawesi, Indonesia and

its relationship with environmental variables. Biodi-

versitas Journal of Biological Diversity, 25(2), 624–631.

https://doi.org/10.13057/BIODIV/D250221

Tomas, C. R. (1997). Identifying marine phytoplankton

(1st ed.). Elsevier. https://doi.org/10.1016/B978-0-12-

693018-4.X5000-0

Tominack, S. A., Coffey, K. Z., Yoskowitz, D., Sutton, G.,

& Wetz, M. S. (2020). An assessment of trends in the

frequency and duration of Karenia brevis red tide

blooms on the South Texas coast (western Gulf of

Mexico). PloS One, 15(9). https://doi.org/10.1371/

JOURNAL.PONE.0239309

Trottet, A., Wilson, B., Sew Wei Xin, G., George, C., Casten,

L., Schmoker, C., Rawi, N. S. B. M., Chew Siew, M.,

Larsen, O., Eikaas, H. S., Tun, K., & Drillet, G. (2018).

Resting stage of plankton diversity from Singapore

coastal water: Implications for harmful algae blooms

and coastal management. Environmental Manage-

ment, 61(2), 275–290. https://doi.org/10.1007/

s00267-017-0966-5

Twiner, M. J., Rehmann, N., Hess, P., & Doucette, G. J.

(2008). Azaspiracid shellfish poisoning: a review

on the chemistry, ecology, and toxicology with an

emphasis on human health impacts. Marine Drugs,

6(2), 39. https://doi.org/10.3390/MD20080004

Vajravelu, M., Martin, Y., Ayyappan, S., & Mayakrishnan,

M. (2018). Seasonal influence of physico-chemical

parameters on phytoplankton diversity, community

structure and abundance at Parangipettai coastal

Revista de Biología Tropical, ISSN: 2215-2075, Vol. 73: e62573, enero-diciembre 2025 (Publicado Ago. 29, 2025)

waters, Bay of Bengal, south east coast of India. Ocea-

nologia, 60(2), 114–127. https://doi.org/10.1016/j.

oceano.2017.08.003

Vieira, V. M. N. de C. da S., Rosa, T. L., Sobrinho-Gonçal-

ves, L., Mateus, M. D., & Mota, B. (2024). A demogra-

phic model to forecast Dinophysis acuminata harmful

algal blooms. Frontiers in Marine Science, 11, 1355706.

https://doi.org/10.3389/fmars.2024.1355706

Wang, Y. Y., Zhai, W. D., Wu, C., Yang, S., & Gong, X.

Z. (2024). Exploring contribution of phytoplankton

cell death to settleable particulate organic carbon

in the East China Sea in spring. Marine Pollution

Bulletin, 201, 116197. https://doi.org/10.1016/j.

marpolbul.2024.116197

Wolny, J. L., Tomlinson, M. C., Schollaert Uz, S., Egerton, T.

A., McKay, J. R., Meredith, A., Reece, K. S., Scott, G.

P., & Stumpf, R. P. (2020). Current and future remote

sensing of harmful algal blooms in the Chesapeake

Bay to support the shellfish industry. Frontiers in

Marine Science, 7, 518373. https://doi.org/10.3389/

fmars.2020.00337

Wong, J. C. Y., Raven, J. A., Aldunate, M., Silva, S., Gaitán-

Espitia, J. D., Vargas, C. A., Ulloa, O., & von Dassow,

P. (2023). Do phytoplankton require oxygen to survi-

ve? A hypothesis and model synthesis from oxygen

minimum zones. Limnology and Oceanography, 68(7),

1417–1437. https://doi.org/10.1002/lno.12367

Xu, Y., Chen, J., Yang, Q., Jiang, X., Fu, Y., & Pan, D.

(2024). Trend of harmful algal bloom dynamics

from GOCI observed diurnal variation of chloro-

phyll a off Southeast coast of China. Frontiers in

Marine Science, 11, 1357669. https://doi.org/10.3389/

fmars.2024.1357669

Yang, J., Löder, M. G. J., Wiltshire, K. H., & Montagnes, D.

J. S. (2021). Comparing the trophic impact of micro-

zooplankton during the spring and autumn blooms

in temperate waters. Estuaries and Coasts, 44(1), 189–

198. https://doi.org/10.1007/s12237-020-00775-4

Zahir, M., Su, Y., Shahzad, M. I., Ayub, G., Rahman, S.

U., & Ijaz, J. (2024). A review on monitoring, fore-

casting, and early warning of harmful algal bloom.

Aquaculture, 593, 741351. https://doi.org/10.1016/J.

AQUACULTURE.2024.741351

Zhu, Y., Mulholland, M. R., Bernhardt, P. W., Neeley, A. R.,

Widner, B., Tapia, A. M., & Echevarria, M. A. (2024).

Nitrogen uptake rates and phytoplankton composi-

tion across contrasting North Atlantic Ocean coastal

regimes north and south of Cape Hatteras. Frontiers

in Microbiology, 15, 1380179. https://doi.org/10.3389/

fmicb.2024.1380179

Zingone, A., Escalera, L., Aligizaki, K., Fernández-Tejedor,

M., Ismael, A., Montresor, M., Mozetič, P., Taş, S., &

Totti, C. (2021). Toxic marine microalgae and noxious

blooms in the Mediterranean Sea: A contribution to

the Global HAB Status Report. Harmful Algae, 102,

101843. https://doi.org/10.1016/J.HAL.2020.101843