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10.1371/journal.pone.0310387
PONE-D-24-11523
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Field and DNA-barcode based surveys reveal evidence of rare endemic fishes in the Rufiji River Basin
Field and DNA-barcode based surveys reveal evidence of rare endemic fishes
https://orcid.org/0009-0003-6396-8350
Saiperaki Jackson L. Conceptualization Data curation Investigation Methodology Software Validation Visualization Writing – original draft Writing – review & editing 1 *
Materu Silvia F. Conceptualization Data curation Methodology Supervision Validation Writing – original draft Writing – review & editing 1
Mkenda Prisila A. Data curation Formal analysis Funding acquisition Visualization Writing – original draft 1
Ligate Elly J. Conceptualization Investigation Project administration Writing – original draft Writing – review & editing 1
Rumisha Cyrus Conceptualization Data curation Methodology Resources Software Supervision Writing – original draft Writing – review & editing 2
1 Department of Biosciences, Sokoine University of Agriculture, Morogoro, Tanzania
2 Department of Animal, Aquaculture and Range Sciences, Sokoine University of Agriculture, Morogoro, Tanzania
Zhang Feng Editor
Nanjing Agricultural University, CHINA
Competing Interests: The author have declared that no competing interests exist.

* E-mail: jacksonlendoya89@gmail.com
19 9 2024
2024
19 9 e031038721 3 2024
28 8 2024
© 2024 Saiperaki et al
2024
Saiperaki et al
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Endemic fish species have long supported the livelihoods of local communities in the Rufiji River Basin (RRB). However, destructive fishing practices have led to a concerning decline in endemic fish stocks. To assess these changes, this study employed key informant interviews, focus group discussions (FGDs), and fishery surveys to assess the historical and contemporary distribution of endemic fishes within the RRB. DNA barcoding was also used to verify species identities. Out of 37 reported fish species, 33 species (54.55% endemic and 45.45% exotic to RRB) were confirmed through DNA barcoding and morphological characteristics. About 5 species including, Heterobranchus longifilis, Citharinus congicus, Labeo congoro, Mormyrus longirostris, and Labeobarbus leleupanus were rarely found in the field, despite being classified as Least Concern by IUCN. Additionally, five species that were reported to be present in the RRB by experienced fishers were not captured during sampling. This highlights the need for validation of the existence of such species through eDNA metabarcoding. Moreover, due to the rarity of some species in the area, their IUCN assessment should be revisited.

http://dx.doi.org/10.13039/501100023918 Sokoine University of Agriculture DPRTC/R/126/CoNAS/1/2022 Mkenda Prisila A. This study was funded by Sokoine University of Agriculture Research and Innovation Support (SUARIS) through the CoEF project (Conservation of Endemic Fishes project) under the grant number DPRTC/R/126/CoNAS/1/2022. The funder has no say on the design, data collection and analysis, writing of the manuscript and decision to submit a manuscript for publication consideration. Data AvailabilityThe data that support the finding of this study are available in NCBI databases under the accession number (OQ908874- OQ918545).
Data Availability

The data that support the finding of this study are available in NCBI databases under the accession number (OQ908874- OQ918545).
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pmc1. Introduction

Freshwater fish have traditionally been a significant source of animal protein, income and employment to riparian communities globally [1]. In 2020 freshwater fisheries in Tanzania contributed for over 86% of total fish production and generated around two billion TZS [2]. However, unsustainable fishing practices driven by rapid population growth and high demand for fish protein [3] have resulted in a rapid decline of freshwater fish stocks, particularly in the Rufiji River Basin (RRB).

The decline in fish stocks in the RRB can be attributed to destructive fishing practices, such as poison fishing, dynamite fishing and the use of beach seine nets, as well as poor water quality from unsustainable agriculture and overgrazing [3, 4]. Additionally, the basin continues to shrink and the number of endemic fish species are declining due to land use change [5]. The native tribes of the RRB such as Ndamba and Pogoro have been engaged in fishing since time immemorial, but in the last 1–2 decades there is a great shift to crop farming as alternative source of food and livelihood support. Ndamba and Pogoro have a strong connection with endemic fish species, and thus their disappearance could have severe implications for household animal protein sources [6, 7].

Despite the designation of the Kilombero Valley Floodplain (KVFP) as a Ramsar site in 2002 and the establishment of the Nyerere National Park within the RRB [8, 9], the conservation of fish stocks in the RRB remains a critical issue. Unprotected areas within the RRB face significant fishing pressure, raising concerns about the potential disappearance of certain species from local catches [10]. Currently, the available information on the species composition in the region dates back over 20 years, originating from a study that identified 23 fish species in the RRB [11]. However, this study relied solely on morphological identification methods alone, which raise concerns about the potential existence of cryptic species and the possibility of misidentification [12]. Such inaccuracies can skew population assessments and conservation priorities, potentially leading to inadequate protection measures for vulnerable species. This lack of accurate and up-to-date information on species composition hinders conservation efforts, making it challenging to implement targeted interventions to protect vulnerable species and maintain ecosystem balance. Additionally, prevalent illegal fishing activities in the RRB [10] exacerbate these challenges, posing a direct threat to fish populations, especially rare and vulnerable species. Without accurate data on species composition and population dynamics, addressing and mitigating the impacts of illegal fishing activities become even more difficult. Hence, there is an urgent need to implement comprehensive monitoring programs that integrate advanced molecular techniques like DNA barcoding alongside traditional methods. This study integrated DNA barcoding and morphological identification techniques to reveal the composition of endemic fish species in the RRB. These approaches have been previously used in the country to uncover non-targeted tilapias among farmed fish and unveil protected elasmobranchs in Tanzanian fish markets [13, 14]. These approaches will provide more accurate assessments of species composition in the RRB, enabling better-informed conservation strategies and ensuring the long-term sustainability of its fish stocks.

2. Material and methods

2.1 Study site

The present study was conducted in the RRB which consists of the Kilombero River, the Great Ruaha, the Rufiji River and other small rivers [15]. Six landing sites in the RRB including Kidatu, Kivukoni, Mofu, Dinari, Ngalimila and Zombe were selected based on the availability and accessibility of landing sites (Fig 1). The RRB is the largest river basin in East Africa, which is rich in fish biodiversity [16]. It lies between 5.7° to 10.5°S and 33.5° to 39°E, covering an area of about 177,429 km2, which accounts for 20% of the total land area of Tanzania [17]. The RRB includes the KVFP, the largest seasonal freshwater lowland floodplain in East Africa [8]. It contains the Kilombero Valley Ramsar site (KVRS), an internationally recognized site of local and international importance. The Ramsar site covers an area of 796,735ha with the wetland catchment area of 40,000 km2 [8]. The RRB also contains Nyerere National Park, which is the largest National Park in Africa covering an area of over 30,000 km2 [9, 18]. The main economic activities in the RRB are fishing, crop production and livestock keeping [19]. The climatic condition of the RRB varies from tropical humid in the east to temperate in the southern highlands. In the east, the mean daily annual temperature is around 39°C while it is around 23°C in southern highlands [17]. The rainfall ranges from 250 mm in some areas to over 1800 mm on the east of the Udzungwa Mountain [17].

10.1371/journal.pone.0310387.g001 Fig 1 Map showing the sampling sites in the Rufiji River Basin (RRB).

The map was created using ArcGIS software and shapefiles from National Bureau of Statistics (NBS) https://www.nbs.go.tz/index.php/en/census-surveys/gis/385-2012-phc-shapefiles-level-one-and-two. Accessed 10 April 2024.

2.2 Data collection

Fish sampling was conducted during two sampling seasons, between July 2022 (the onset of the dry season) and January 2023 (the onset of the wet season). A total of 46 different species were collected at six landing site of the RRB. Fish were initially identified using the available fish identification keys [20, 21]. Fish species that showed potential differences from those already sampled were specifically collected from each landing sites. For every landing site, where samples were taken (Table 1), coordinate points were recorded using Geographical Positioning System (GPS) device. Fin clip tissues of about 0.05 grams were cut from each fish, stored in 1.5 ml micro centrifuges and preserved using 99.9% ethanol until further analysis. Additionally, three focus group discussions were conducted to gather information about species composition, local fish identification techniques, fishing trends and fish management strategies. In-depth interviews were conducted to 4 groups of key informants including village elders, environmental management officers, fisheries officers and village chairpersons to gather information about the composition of fish in the RRB, local fish identification techniques.

10.1371/journal.pone.0310387.t001 Table 1 Central coordinates and numbers of fins clip sampled within the Rufiji River Basin (RRB).

Site	Coordinates	Number of fin clips sampled	
	Latitudes (° S)	Longitudes (° E)		
Rufiji River				
Zombe	7.80	38.30	2	
Ruaha River				
Kidatu	7.38	37.92	2	
Kilombero River				
Kivukoni	8.19	36.69	34	
Mofu	8.36	36.40	1	
Dinari	8.24	36.58	2	
Ngalimila	8.96	35.87	5	
Total			46	

2.3 Ethical statement

The fish sampled in this study were obtained from landing sites in the study area where they had already been caught by local fishers for human consumption. Therefore, no additional methods of sacrifice, anesthesia, or analgesia were required or administered by the researchers. The sampling process involving collecting fin clips from deceased fish only, ensuring that nor further suffering was inflicted. Authorizations for sampling were obtained from the Sokoine University of Agriculture and the Tanzania Ministry of Regional Administration and Local Government under permit number AB.307/323/01/24.

2.4 DNA extraction, COI amplification, and sequencing

Genomic DNA was extracted from each sample using the TIANamp Genomic DNA kit (TIANGEN Biotech, Beijing) according to the manufacturer’s protocol. Then the quality of each DNA extract was evaluated on 1% agarose gel before further analysis [22]. Thereafter, fragments (620 base pairs) of the cytochrome oxidase subunit I gene (COI) were amplified from the DNA extracts of each sample in a T100TM Thermal cycler machine (Bio-Lab Inc, GA, USA) using the Forward primer FishFI (5’-TCAACCAACCACAAAGACATTGGCAC-3’) and the reverse primer FishR1 (5’-TAGACTTCTGGGTGGCCAAAGAATCA-3’) [23]. Amplification reactions were done in a total volume of 35 μL consisting of 2 μL template DNA, 1 x OneTaq 2X Master Mix with Standard Buffer (New England BioLabs Inc., MA, USA), 5 mg bovine serum albumin and 0.3 μM of each primer. Each reaction was initially denatured at 94°C for 5 min, followed by 35 cycles of 94°C for 40 s, 54°C for 45 s and 72°C for 60 s. The final extension of 72°C for 15 min was added to ensure complete elongation. The quality of each PCR product was checked on a 1.5% agarose gels. The successful PCR amplicons were Sanger sequenced by Macrogen Europe Laboratory in the ABI 3730XL automated sequencer (Applied Bio systems, Foster City, USA).

2.5 Data analysis

A total of 46 samples were successfully analysed. The obtained sequences were edited to trim the ends and aligned using ClustalW algorithm as implemented in the program MEGA ver. 11 [24] to obtain sequences with equal length of 600 base pairs. Each sequence was then compared with COI sequences in the GenBank Nucleotide Database using the BLAST (Basic Local Alignment Search Tool) and BOLD (Barcode of Life Data System). The sequences were then submitted to GenBank and accession numbers (OQ908874- OQ918545) were provided. At least 90.91% of the unknown fish were identified to species level and the samples were classified to family, genus and species following the Linnaean taxonomy.

The Bayesian phylogenetic tree was constructed using BEAST ver 2.5 [25] to assess the evolutionary relationships among species. The analysis employed a relaxed uncorrelated log-normal molecular clock and a general time- reversible evolutionary model, running for 10 million generations. The tree was annotated using TreeAnnotator ver 1.10 and visualized using FigTree ver 1.4. The COI sequence of Leopard whip ray Himantura leoparda with the accession number MK422130 was retrieved from GenBank and included in the dataset as outgroup.

3. Results

3.1 Fish diversity

Fishers and the key informants mentioned a total of 37 different fishes found within the RRB. About 5 fish species were not verified during fishery survey suggesting that they are either no longer abundant in the wild or they are present in a very low numbers (Table 2). About 5 species including H. longifilis, C. congicus, L. congoro, M. longirostris, and L. leleupanus were rarely found in the field. Moreover, fishers in the RRB used the local identification techniques such as fish morphology including the size of the fish and number or structure of fins to identify fish. This identification knowledge was obtained from village elders and the experienced fishermen. The provided local names, however, do not reflect the Linnaean taxonomy and the DNA barcoding results. For example, Synodontis multipuctatus was named as ngogo ng’andu and ngogo mwanajeshi while Labeo congoro was named as mtuku and ningu depending on morphological characteristics and stage of development. Additionally, one local name was given to more than one species, particularly those with similar morphologies. For example two different species of tilapia Oreochromis korogwe and Oreochromis urolepis were reported as perege, while Glossogobius giuris and Eleotris klunzingerii were reported as bubu mchanga while Hippopotamyrus spp. and Petrocephalus affinis were reported as ndipi (Table 2). Furthermore, although fishers could distinguish matured bula Schilbe moebiusii and luepe Eutropiellus longifilis, they could not distinguish juveniles of these species due to their similar morphologies.

10.1371/journal.pone.0310387.t002 Table 2 The local names of endemic fishes sampled in the Rufiji River Basin (RRB) and their corresponding Linnaean classification according to DNA barcode results.

		Linnaean classification			
No	Local name	Family	Genus	Species	
1	Benasongo	Cyprinidae	Enteromius	Enteromius apleurogramma	
2	Bubu mchanga	Gobiidae	Glossogobius	Glossogobius giuris	
3	Bubu mchanga	Eleotridae	Eleotris	Eleotris klunzingerii	
4	Bula	Schilbeidae	Schilbe	Schilbe moebiusii	
5	Gugutuu	Anabantidae	Ctenopoma	Ctenopoma spp	
6	Jwalajwala	Not verified			
7	Kambale	Clariidae	Clarias	Clarias gariepinus	
8	Kibenamdenge	Not verified			
9	Kitoga	Bagridae	Bagrus	Bagrus orientalis	
10	Luepe	Schilbeidae	Eutropielus	Eutropiellus longifilis	
11	Mbala	Citharinidae	Citharinus	Citharinus congicus	
12	Mbewe	Alestidae	Brycinus	Brycinus spp	
13	Mgundu	Alestidae	Alestes	Alestes stuhlmanni	
14	Mjongwa	Clariidae	Heterobranchus	Heterobranchus longifilis	
15	Mkunga	Anguillidae	Anguilla	Anguilla bangelensis	
16	Mkuyu	Cyprinidae	Labeobarbus	Labeobarbus leleupanus	
17	Mtuku	Cyprinidae	Labeo	Labeo congoro	
18	Ndipi	Mormyridae	Petrocephalus	Petrocephalus affinis	
19	Ndipi	Mormyridae	Hippopotamyrus	Hippopotamyrus spp	
20	Ndipi kongwe	Mormyridae	Pollimyrus	Pollimyrus nigrican	
21	Ndipi mdomo mfupi	Mormyridae	Marcusenius	Marcusenius livingstonii	
22	Ndipi mdomo mrefu	Mormyridae	Marcusenius	Marcusenius macrolepidatus	
23	Ndipi miera	Not verified			
24	Ndipi namani	Mormyridae	Hippopotamyrus	Hippopotamyrus grahami	
25	Ndungu	Distichodontidae	Distichodus	Distichodus petersii	
26	Ngogo dongo	Mochokidae	Synodontis	Synodontis multipuctatus	
27	Ngogo mwanajeshi	Mochokidae	Synodontis	Synodontis multipuctatus	
28	Ngogo mweusi	Mochokidae	Synodontis	Synodontis rukwaensis	
29	Ngogo ng’andu	Mochokidae	Synodontis	Synodontis rufigiensis	
30	Ngolya	Not verified			
31	Ngurufi	Cyprinidae	Labeo	Labeo coubie	
32	Ningu	Cyprinidae	Labeo	Labeo congoro	
33	Njege	Alestidae	Hydrocynus	Hydrocynus tanzaniae	
34	Njuju	Alestidae	Brycinus	Brycinus affinis	
35	Njuju mkapa	Alestidae	Brycinus	Brycinus sadleri	
36	Perege 1	Cichlidae	Oreochromis	Oreochromis korogwe	
37	Perege 2	Cichlidae	Oreochromis	Oreochromis urolepis	
38	Sheta	Clariidae	Clarias	Clarias werneri	
39	Sulusulu	Mormyridae	Mormyrus	Mormyrus longirostris	
40	Sulusulu vihondi	Not verified			

3.2 Confirmation of morphologically identified species through DNA barcoding

A total of 46 COI barcode sequences representing 33 different species belonging to 24 different genera, 11 different families and 8 different orders were obtained from the sampled specimens. About 18 (54.55%) out of 33 species were endemic while 15 (45.45%) species were exotic to RRB (Fig 2). These endemic species included; njuju Brycinus affinis, mtuku or ningu Labeo congoro, bula S. moebiusii, ndipi mdomo mrefu Marcusenius macrolepidatus, ndungu D. petersii, njege H. tanzaniae, kitoga B. orientalis, ngogo ng’andu Synodontis rufigiensis, ngogo mweusi Synodontis rukwaensis, mbala Citharinus congicus, tilapia O. urolepis, benasongo Enteromius apleurogramma, mbewe Brycinus spp, luepe E. longifilis, mgundu Alestes stuhlmanni, ndipi P. affinis, ndipi Hippopotamyrus spp and ndipi mdomo mfupi Marcusenius livingstonii. About 13 different fish species were identified using GenBank and BOLD databases. However, higher identities (98.87%-99.84%) failed to confirm ndipi P. affinis and sulusulu Mormyrus longirostris while low identities confirmed mbala C. congicus (93.96%) and ndipi kongwe Pollimyrus nigrican (96.73%) in GenBank database (Table 3). The taxonomic identity of 20 different fish species were not confirmed using DNA barcode alone due to lack of reference barcodes in the GenBank and BOLD databases. Therefore, the integration of DNA barcode results and morphological identification was used to confirm the identity of the 20 fish species. Yet, the identification sheets were poor for ndipi Hippopotamyrus spp, mbewe Brycinus spp and gugutuu Ctenopoma spp.

10.1371/journal.pone.0310387.g002 Fig 2 Percentage of endemic and exotic fish sampled between July 2022 and January 2023 in six different landing sites within the Rufiji River Basin (RRB).

10.1371/journal.pone.0310387.t003 Table 3 Fish species identification from GenBank and BOLD databases, conservation status and the number of samples obtained from fish species sampled between July 2022 and January 2023 in the Rufiji River Basin (RRB).

Scientific name	Accession no.	GenBank Species name	Identity (%)	BOLD Species name	Identity (%)	Number of samples	IUCN Red list category	
Brycinus affinis	OQ908874	Alestes spp	92.57	No match	0	1	LC	
Labeo congoro	OQ908912
OQ908894	Labeo lineatus	96.89	Labeo lineatus	97.40	2	LC	
Schilbe moebiusii	OQ908911	Schilbe intemedius	93.98	No match	0	1	LC	
Marcusenius macrolepidatus	OQ908903
OQ908875	Campylomormyrus numenius	93.27	Marcusenius livingstonii	98.34	2	LC	
Oreochromis korogwe	OQ915200
OQ915199	Oreochromis korogwe	99.66	Oreochromis korogwe	99–100	2	LC	
Distichodus petersii	OQ908900	Distichodus petersii	98.04	Distichodus petersii	98.16	1	VU	
Hydrocynus tanzaniae	OQ918545	Hydrocynus vittatus	94.92	No match	0	1	LC	
Clarias gariepinus	OQ908902	Clarias gariepinus	99.84	Clarias gariepinus	99.84	1	LC	
Bagrus orientalis	OQ908901	Bagrus caeruleus	93.13	No match	0	1	LC	
Synodontis rufigiensis	OQ908910
OQ908889	Synodontis spp	94.96	No match	0	2	LC	
Synodontis rukwaensis	OQ908899
OQ908888	Synodontis rukwaensis	99.38	Synodontis rukwaensis	99.67	2	LC	
Citharinus congicus	OQ908898
OQ908881	Citharinus congicus	93.96	No match	0	2	LC	
Anguilla bengalensis	OQ908897
OQ908893
OQ908909	Anguilla bengalensis	100	Anguilla bengalensis	100	3	NT	
Labeo coubie	OQ918544	Labeo forskalii	95.57	No match	0	1	LC	
Hippopotamyrus grahami	OQ915201	Pollimyrus isidori	90.15	No match	0	1	LC	
Hippopotamyrus spp	OQ915198	Ciphomyrus discorhynchus	96.20	No match	0	1	LC	
Mormyrus longirostris	OQ908896
OQ908879	Mormyrus rume	98.87	Mormyrus tapirus	98.71	2	LC	
Oreochromis urolepis	OQ908895	Oreochromis korogwe	97.93	Oreochromis urolepis	98.36	1	LC	
Pollimyrus nigrican	OQ908892	Pollimyrus nigrican	96.73	No match	0	1	LC	
Enteromius apleurogramma	OQ908908
OQ908907	Enteromius apleurogramma	100	Enteromius apleurogramma	100	2	LC	
Brycinus sadleri	OQ908877	Brycinus sp.epulu	97.03	Brycinus lateralis	98.69	1	LC	
Synodontis multipuctatus	OQ908891
OQ908890	Synodontis victoriae	96.08	Synodontis victoriae	97.07	2	LC	
Clarias werneri	OQ908887	Clarias alluaudi	95.94	No match	0	1	LC	
Brycinus spp	OQ908886	Brycinus nurse	91.31	No match	0	1	LC	
Eutropielus longifilis	OQ908906
OQ908885
OQ908884	Schilbe intemedius	91.06	No match	0	3	LC	
Labeobarbus leleupanus	OQ908883	Labeobarbus robertsi	96.27	No match	0	1	VU	
Heterobranchus longifilis	OQ908882	Heterobranchus longifilis	98.72	Heterobranchus spp	98.86	1	LC	
Alestes stuhlmanni	OQ908880	Alestes baremoze	91.58	No match	0	1	LC	
Petrocephalus affinis	OQ908878	Petrocephalus catostoma	99.84	Petrocephalus catostoma	97.18	1	LC	
Ctenopoma spp	OQ908876	Ctenopoma muriei	93.81	No match	0	1	LC	
Glossogobius giuris	OQ918543	Glossogobius giuris	98.35	Glossogobius giuris	98.8	1	LC	
Eleotris klunzingerii	OQ908905	Eleotris klunzingerii	100	Eleotris klunzingerii	100	1	LC	
Marcusenius livingstonii	OQ908904	Ciphomyrus discorhynchus	93.23	No match	0	1	LC	
LC = least concern, VU = vulnerable and NT = n.

3.3 Phylogenetic analysis of experimental fish species

The bayesian phylogenetic analysis performed from 46 nucleotide sequences (Fig 3) provided additional confirmation to the identified fish species. Closely related species were clustered under the same node implying that the amplified barcodes correctly identified the species.

10.1371/journal.pone.0310387.g003 Fig 3 Bayesian phylogenetic tree showing clustering patterns of cytochrome oxidase subunit I sequences of endemic and exotic fish species sampled in the Rufiji River Basin (RRB) between July 2022 and January 2023.

3.4 Conservation status

It was revealed that 90.91% (30 different fish species) of the identified species are categorized by IUCN as least concern (LC), 3.03% as near threatened (NT), and 6.06% as vulnerable (VU) (Table 3). Hence, none of the sampled fish species is either endangered or critically endangered. Similarly, none of the sampled fish species is either CITES protected or protected by Tanzanian laws.

4. Discussion

The present study revealed 33 different fish species in the RRB. This number is higher than the number reported in a previous study [11] which showed that there was only 23 different fish species. The variation in results can be attributed to differences in sampling techniques employed, limited sampling sites and shorter duration of sampling. Therefore, a total of 10 fish species identified in this study were not reported in the earlier studies. These newly identified species include, bubu mchanga G. giuris, E. klunzingerii, gugutuu Ctenopoma spp, luepe E. longifilis, mkuyu L. leleupanus, ndipi P. affinis, ndipi kongwe P. nigrican, ngogo mwanajeshi S. multipuctatus, ngogo ng’andu S. rufigiensis and ndipi mdomo mrefu M. macrolepidatus. Eighteen out of 33 species were endemic to RRB while 15 were exotic. The presence of a high number of exotic fish species poses a serious threat to the endemic fish populations. Some of these exotic species can act as competitors, predators, or even hybridize with the endemic species, further exacerbating the risk of extinction [26]. The present study also confirmed the presence of H. longifilis, C. congicus and L. coubie contrary to study conducted by [27] which revealed that the species have disappeared in the RRB. However, the fact that these species were rare in the catch suggests that the current IUCN assessment of them as Least Concern should be revisited. This is particularly critical for H. longifilis because it was found at only one site and was reported by experienced fishers to be among the fishes that were highly abundant in the past but are currently rare.

The local fish identification techniques used was found to be inaccurate, leading to numerous contradictions, especially when distinguishing closely related species. Despite using the Field guide for freshwater fishes of Tanzania [20], there were limitations in the identification sheets, particularly for certain fish species. This is similar to the study conducted in the study area [11] which showed the limitation of the identification sheets in identifying Mbewe Brycinus spp and Sheta C. werneri.

DNA barcoding alone confirmed identities of 13 species. However, low identities were used to confirm some species in the GenBank database while higher identities failed to confirm the identity of ndipi P. affinis and sulusulu M. longirostris, suggesting a high probability of tentative, incorrect or low-quality sequences being submitted to the database [28]. BOLD database confirmed less species than GenBank. However, most of the confirmed species were identified with 99–100% identities. This reveals that BOLD database has greater resolution than GenBank database [29]. The COI sequences of 21 fish species have not been recorded in the GenBank database, and the COI sequences of 17 fish species do not match any sequence in the BOLD database. Thus, this study added COI sequences for 21 fish species to the GenBank database and introduced sequences for 17 fish species that did not previously exist in the BOLD database. Furthermore, fish species identified from this study would help to solve the problem of unidentified species from the previous studies [11, 27]. Some fish species were however, not verified through DNA barcoding alone due to absence of corresponding COI sequences in the GenBank and BOLD Database. The integration of DNA sequencing information with the morphological traits of the fish showed great efficiency.

The constructed phylogenetic tree provided similar classification concerning taxonomy and morphological traits of the fishes. All closely related species were clustered under the same nodes revealing that the amplified barcodes correctly identified the species. The results of the present study indicate that none of the sampled fish in the RRB are classified as endangered or critically endangered according to the IUCN. However, due to the rarity of some species in the catch, their IUCN assessment should be revisited. This is critical for species such as mjongwa H. longifilis, mbala C. congicus, ningu L. congoro, sulusulu M. longirostris, and mkuyu L. leleupanus because they were particularly rare. These rare species require reassessment and reclassification as their current IUCN criteria does not accurately reflect their actual status on the ground. Additionally, because none of the rare species are listed in either CITES Appendices or the Third Schedule of the Tanzania Fisheries (Amendment) Regulations of 2009. This implies that there are currently no specific legal measures in place to regulate or protect these fish species from overexploitation or illegal trade. This highlights the need to update CITES Appendices and the Third Schedule of the Tanzania Fisheries (Amendment) Regulations of 2009 to include the above-mentioned rare species if they are to be protected from extinction. Furthermore, the absence of some reported species during sampling does not conclusively indicate their complete disappearance in the RRB; instead, it calls for further studies employing environmental DNA (eDNA) to confirm the presence of these species.

5. Conclusion

The present study confirmed 33 different species in the RRB, including species that were reported to have disappeared. However, some species were rarely found in the field despite being classified as Least Concern by the IUCN, suggesting the need for their IUCN Red List status to be reevaluated. Additionally, the presence of rare species suggests the need to protect them in the RRB to prevent further decline in fish populations. This can be achieved through promoting sustainable fishing practices by raising awareness among local fishers about techniques that minimize harm to fish populations and their habitats. Furthermore, the expansion of protected areas within the RRB could provide safe havens for rare species, potentially reversing the observed declining trends. Moreover, the findings of this study should be validated using environmental DNA (eDNA) to confirm the existence of species reported to have disappeared.

We would like to express our gratitude to the local community in the RRB who helped us during fieldwork. We extend our appreciation to the Tanzanian Ministry of Regional Administration and Local Government for issuing the necessary permits. Lastly, we acknowledge the contributions of the reviewers, whose constructive criticism greatly improved this work.

10.1371/journal.pone.0310387.r001
Decision Letter 0
ZHANG Feng Academic Editor
© 2024 Feng ZHANG
2024
Feng ZHANG
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version0
10 May 2024

PONE-D-24-11523Field and DNA-barcode based surveys reveal evidence of rare endemic fishes in the Rufiji River Basin, Tanzania.PLOS ONE

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Reviewer #1: Partly

**********

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Reviewer #1: No

**********

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Reviewer #1: Yes

**********

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Reviewer #1: Yes

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Reviewer #1: The research is well-designed however, there are a few points that need clarification in the text, and the phylogenetic tree needs to be reconstructed using different approaches.

Major Revisions:

- Table 3: Species such as Labeo congoro, Marcusenius macrolepidatus, Mormyrus longirostris, Oreochromis urolepis, Brycinus sadleri, and Petrocephalus affinis showed over 97% coverage with other species during the NCBI or BOLD blast analysis. Do the authors have a plan for these species? Were these species uploaded to BOLD under their scientific names as given by the authors, or according to their coverage from the blast analyses?

- 2.5 Data Analysis: "‘The evolutionary history was inferred by using the maximum likelihood method and Tamura-Nei model. The bootstrap consensus tree inferred from 500 replicates was used to analyse the evolutionary history of the identified species. Branches corresponding to partitions reproduced in less than 75% bootstrap replicates were collapsed. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test 500 replicates was shown next to the branches.’

In the discussion section, it was also noted that all closely related species were clustered under the same nodes, indicating that the amplified barcodes correctly identified the species. However, there were instances where species from different orders and families clustered together, suggesting potential similarities or evolutionary relationships despite their taxonomic differences.

However, if the Himantura leoparda species (an outgroup) is positioned under the same node despite having a completely different background, this suggests that the tree may be unsuitable for this type of data. Therefore, I recommend that the authors use a different approach for reconstructing the tree, such as a Bayesian algorithm.

- Pictures of these species need to be given as supplementary data

- There should be barcoding gap analysis

Minor Revisions:

- 2.3 Ethical Statement: There is inconsistent spacing between lines.

- 3.1 Species Names: The names H. longifilis and C. congicus are not italicized.

- Figures: The resolution of the figures is very low.

**********

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Reviewer #1: Yes: ARZU KARAHAN

**********

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10.1371/journal.pone.0310387.r002
Author response to Decision Letter 0
Submission Version1
11 Jun 2024

EDITOR COMMENTS

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Response: The manuscript was checked and formatted to make sure that it meets PLOS ONE’s style.

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Response: The ethical statement explaining the permission to collect fin clips samples was included in Methods section. See line 102-105.

3. Thank you for stating the following financial disclosure:

"This study was funded by Sokoine University of Agriculture Research and Innovation Support (SUARIS) through the CoEF project (Conservation of Endemic Fishes project) under the grant number DPRTC/R/126/CoNAS/1/2022. The funder has no say on the design, data collection and analysis, writing of the manuscript and decision to submit a manuscript for publication consideration. "Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

Response: The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

4. We note that [Figure 1] in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

Response: The figure is replaced with the new one to avoid submitting the copyrighted images. The new map was created using ArcGIS software and shapefiles from National Bureau of Statistics (NBS) https://www.nbs.go.tz/index.php/en/census-surveys/gis/385-2012-phc-shapefiles-level-one-and-two. Accessed 10 April 2024.

REVIEWERS COMMENTS

Major Revisions

Reviewer #1: The research is well-designed however, there are a few points that need clarification in the text, and the phylogenetic tree needs to be reconstructed using different approaches.

Response: The phylogenetic tree was constructed using BEAST version 2.5, followed by annotation using TreeAnnotator version 1.10 and visualization using FigTree version 1.4. Notably, the tree exhibited a clustering pattern wherein closely related species were grouped together, indicating the accuracy of species identification through the amplified barcode. Consequently, additional clarifications were incorporated into the text, as outlined from line 193 to 209, to elucidate this observation.

Table 3: Species such as Labeo congoro, Marcusenius macrolepidatus, Mormyrus longirostris, Oreochromis urolepis, Brycinus sadleri, and Petrocephalus affinis showed over 97% coverage with other species during the NCBI or BOLD blast analysis. Do the authors have a plan for these species? Were these species uploaded to BOLD under their scientific names as given by the authors, or according to their coverage from the blast analyses?

Response: The highest similarities observed between these species with other species in NCBI or BOLD databases provide an alarm that there is high possibility of incorrect or low quality sequences that have been submitted to these databases. This suspicion is further underscored by the disparity between the morphological traits of the species documented in the database and those observed during our field surveys. Compounding the issue, the sequences of these species, identified by their scientific names, had not been previously uploaded to either BOLD or NCBI databases. In response, we uploaded these sequences in NCBI database for reference under the accession number OQ908874- OQ918545. However, we remain open to explore much on these species if funds were provided.

Data Analysis: "‘The evolutionary history was inferred by using the maximum likelihood method and Tamura-Nei model. The bootstrap consensus tree inferred from 500 replicates was used to analyse the evolutionary history of the identified species. Branches corresponding to partitions reproduced in less than 75% bootstrap replicates were collapsed. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test 500 replicates was shown next to the branches.’

In the discussion section, it was also noted that all closely related species were clustered under the same nodes, indicating that the amplified barcodes correctly identified the species. However, there were instances where species from different orders and families clustered together, suggesting potential similarities or evolutionary relationships despite their taxonomic differences.

However, if the Himantura leoparda species (an outgroup) is positioned under the same node despite having a completely different background, this suggests that the tree may be unsuitable for this type of data. Therefore, I recommend that the authors use a different approach for reconstructing the tree, such as a Bayesian algorithm.

Response: The bayesian phylogenetic analysis was performed as suggested by the reviewer. The tree clearly separated outgroup (Himantura leoparda) from other species and grouped closely related species under the same cluster. This clustering confirms that the amplified barcodes effectively identified the species.

Minor Revisions:

- 2.3 Ethical Statement: There is inconsistent spacing between lines.

Response: The ethical statement was checked as suggested by the reviewer to remove unnecessary spaces between lines

- 3.1 Species Names: The names H. longifilis and C. congicus are not italicized.

Response: The names were italicized see line 153

- Figures: The resolution of the figures is very low.

Response: The resolution of the figures was improved to 300dpi

Attachment Submitted filename: Response to reviewers.docx

10.1371/journal.pone.0310387.r003
Decision Letter 1
ZHANG Feng Academic Editor
© 2024 Feng ZHANG
2024
Feng ZHANG
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version1
29 Aug 2024

Field and DNA-barcode based surveys reveal evidence of rare endemic fishes in the Rufiji River Basin, Tanzania.

PONE-D-24-11523R1

Dear Dr. Saiperaki,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Academic Editor

PLOS ONE

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Comments to the Author

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Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: please do the below corrections;

1) Line 206: The title '3.3 Phylogenetic analysis of experimental fish species' should be simplified as '3.3 Phylogenetic analysis.'

2) The font size of the scale in Figure 3 needs to be increased.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Arzu Karahan

**********

10.1371/journal.pone.0310387.r004
Acceptance letter
ZHANG Feng Academic Editor
© 2024 Feng ZHANG
2024
Feng ZHANG
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
10 Sep 2024

PONE-D-24-11523R1

PLOS ONE

Dear Dr. Saiperaki,

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9 Kijazi A. Tanzania National Parks. 2020. 58 p.
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