IGNOU FST-01 Previous Year Question Papers

  • February 10, 2024

If you are looking for IGNOU  FST-01 previous year question papers  entitled “ Foundation Course in Science and Technology ” for the IGNOU  Bachelor of Arts (Tourism Studies) (BTS) or BDP ,  then you have come to the right place!, here We’ve uploaded the last 10 years’ question papers for your convenience. these FST-1 previous year question papers will help you for your upcoming exams preparation.  These papers are available in both English and Hindi language in the same pdf.

Prepare for your upcoming exams effectively with FST 01 previous year question papers, available in PDF format in English and Hindi. These papers are invaluable resources for your exam preparation.

Click the link below to download these old exam paper pdf for free!

FST-1 Old Paper Details

Programme or BCOM
Course Code
Course Title
Paper LanguageEnglish/Hindi
YearsJune 2018 to December 2022
Doc typePrevious year Question Papers PDF’s (soft copy)

1 thought on “IGNOU FST-01 Previous Year Question Papers”

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IGNOU FST 01 Question Papers

  • 1.1 How to get Ignou FST 1 Solved Question Papers?
  • 1.2 Important detail about Ignou FST 01 previous year question paper
  • 1.3 Download IGNOU FST 01 Question Papers

IGNOU FST 01 Question Papers June 2020, Dec 2019, June 2019, Dec 2018, June 2018, Dec 2017, June 2017, Dec 2016, June 2016, Dec 2015, June 2015, 2014 – Are you pursuing Bachelor Degree Programme (BDP – BA/ B.Com/ B.Sc.) from Indira Gandhi National Open University? If yes, then you have to study a Foundation Course in Science and Technology i.e FST-1.

Related Post: IGNOU Date Sheet Are you also looking for   FST 01 solved assignment ?  For  IGNOU FST 1 help book containing last 10 year solved question papers, Please contact on  WhatsApp at 7428482160 or send us email at [email protected]

To prepare for upcoming June or December term end examination, students may require Ignou FST 01 previous year question papers of last 5 years. These old question papers are provided by university totally free of cost. Students do not need to spend any penny for it. They can easily download FST 01 old question papers of last ten years from the university official website at www.ignou.ac.in.

Related Post:

  • ACC 1 question paper
  • BSHF question paper
  • FEG 1 question paper
  • FEG 2 question paper

The Ignou previous question papers of FST 1 can be easily downloaded in the PDF format. There are two options to download these Ignou FST 01 question papers. Either the students can download it by selecting the program code or they can directly download it by clicking on year/session.

How to get Ignou FST 1 Solved Question Papers?

After downloading FST- 1 previous papers, they should try to solve them. It is something extra which students can do to obtain good marks in their June and December examination. In case, if student faces any difficulty in solving FST 01 question papers, they can take a help of reference books.

Students can buy Ignou FST 01 reference/ help books online.These books contains Ignou previous year questions of last 5 years along with important questions and answers. In case, if you find any difficulty in getting reference books, You can send email at [email protected] . The representative will guide you how to buy it online.

Important detail about Ignou FST 01 previous year question paper

To help out students, we have collected some important points from previous year question papers of FST 01 course.These are mentioned below:

  • Ignou FST 1 question paper carries 70% Weightage of the total marks.The remaining 30% weightage is given to Tutor Marked Assignments which the students have to solve and submit to their concerned study centre.
  • The total marks of FST-01 term end examination question paper is 100.
  • The maximum duration of exam is 3 hours.
  • There are three sections of questions and all these sections are compulsory to answer. However, students will get choice of questions to answer in each section. For more details, please download and check out Ignou FST 01 previous question paper

Download IGNOU FST 01 Question Papers

Sometimes, students find it difficult to search and download the last 10 year question papers from the university official website.So, we have provided below the direct links to download FST-01 question papers in PDF format.These are as follows:



FST 01 question paper not found sir pls reply on gmail- [email protected]

Srijana baraily

Sir i can’t found fst1 question paper how to do my assignment

Priya singh

Sir I can’t found my f.s.t01 qution paper… How to do my assignment


Fst-1 important question paper 2018 not found can u send me the link on my email address please that was your most kindness thanks My email . [email protected]

Saga sali

Sir I can’t get question paper from the web site


Sir I didn’t get my ESO12 study material.Its still under dispatch.My assignment last date is on 30/09/2018.Please help me out.

Subir Banerjee


EMAIL: [email protected] [email protected]





A kumar

Question paper2019-20 of FST-01 in hindi plz uplode sir


Sir I Cannot Found Fst-1 Assignment Question Paper On The Ignou Site. Pls Kindly Send The Assignment Questiuon Paper Of July 2019 And January 2020 Session at my mail id [email protected]


I need BA subject FST-01 last five year solved question paper in Hindi. Can you help me. My email id is [email protected]

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  • IGNOU Assignments

IGNOU FST-01 - Foundation Course in Science and Technology , Latest Solved Assignment (January 2024 - December 2024)

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IGNOU FST-01 January 2024 - December 2024 - Solved Assignment

Are you looking to download a PDF soft copy of the Solved Assignment FST-01 - Foundation Course in Science and Technology ? Then GullyBaba is the right place for you. We have the Assignment available in English and Hindi language.

This particular Assignment references the syllabus chosen for the subject of Science , for the January 2024 - December 2024 session. The code for the assignment is FST-01 and it is often used by students who are enrolled in the BA, B.COM, B.Sc., BSW, BTS Degree.

Once students have paid for the Assignment, they can Instantly Download to their PC, Laptop or Mobile Devices in soft copy as a PDF format. After studying the contents of this Assignment, students will have a better grasp of the subject and will be able to prepare for their upcoming tests.

IGNOU FST-01 (January 2024 - December 2024) Assignment Questions

1. Give an account of the scientific revolution during post renaissance period.

2. List and describe the developments in medicine during the Iron Age.

3.(a) Draw a well labelled diagram of human brain cut along the medial plane. (b) List the major endocrine glands and add a note on their functions.

4. Distinguish between nuclear fusion and nuclear fission and discuss briefly the working of a nuclear reactor.

5. Discuss in detail the evidences of human evolution giving suitable examples.

6. Explain how the recent technological advances have benefitted the modern education system.Give suitable examples.

7.(a) Mention four ways in which our societyhas benefitted from the artificial satellite programme. (b) Explain the impact of the modern information technology on our life style and society.

8. (a) Explain the application of science and technology in small scale industries. (b) Explain the concept of chemical evolution with the help of Miller’s experiment.

9. What is mass communication? Discuss the technological advances in mass communication.

10. Discuss five types of infectious diseases caused by microbes. Add a note on the spread or transmission of these diseases.

IGNOU FST-01 (January 2023 - December 2023) Assignment Questions

1. Write an account on the technical innovations and inventions in Medieval India.

2. List and explain the popular media of mass communication in present times.

3. (a) Make a table showing the food groups and their major nutrients. (b) What goals need to be set for the management of water resources? How water can be managed in a scientific manner?

4. Distinguish between infectious and non-infectious diseases. Discuss briefly how the infectious diseases travel from one person to another.

5. Describe characteristics of planets of solar system.

6. Giving appropriate examples explain how recent technological advances have benefitted the modern education system.

7.(a) Discuss the scientific and technical achievements in Bronze Age. (b) Describe the various theories and experiments regarding the origin of life on Earth.

8. Explain the role of scientific knowledge in agriculture with respect to arid zones, dry lands and hills.

9. ‘How society influences scientific development’ – explain giving suitable examples.

10. Why is it important to pursue the policy of self-reliance for the progress of science and technology and for the development of the nation?

1) पुनर्जागरण काल में वैज्ञानिक क्रांति पर लेख लिखिए ।

2) लौह युग के दौरान चिकित्सा के क्षेत्र में उपलब्धियों को सूचीबद्ध कीजिए और उनका विवरण दीजिए ।

3 क) मध्यवर्ती तल पर काटे गए मानव मस्तिष्क का सुनामांकित चित्र बनाइए । ख) प्रमुख अंतःस्रावी ग्रंथियों की सूची बनाईए और उनके कार्यों पर टिप्पणी लिखिए ।

4) नाभिकीय संलयन और नाभिकीय विखंडन के बीच अंतर कीजिए और नाभिकीय रिएक्टर की कार्यप्रणाली पर संक्षेप में चर्चा कीजिए ।

5) उपयुक्त उदाहरण देते हुए मानव विकास के प्रमाणों पर विस्तार से चर्चा कीजिए।

6) उपयुक्त उदाहरण देते हुए स्पष्ट कीजिए कि हाल की तकनीकी प्रगति ने आधुनिक शिक्षा प्रणाली को कैसे लाभान्वित किया है।

7 क) उन चार तरीकों का उल्लेख कीजिए जिनसे हमारा समाज कृत्रिम उपग्रह कार्यक्रम से लाभान्वित हुआ है। ख) हमारी जीवन शैली और समाज पर आधुनिक सूचना प्रौद्योगिकी के प्रभाव की व्याख्या कीजिए।

8 क) लघु उद्योगों में विज्ञान और प्रौद्योगिकी के अनुप्रयोगों को समझाइए । ख) मिलर के प्रयोग की सहायता से रासायनिक विकास की अवधारणा को समझाइए ।

9) जनसंचार क्या है? जनसंचार में तकनीकी प्रगति पर चर्चा कीजिए ।

10) रोगाणुओं से होने वाले पांच प्रकार के संक्रामक रोगों की चर्चा कीजिए। इन रोगों के फैलने पर एक टिप्पणी लिखिए।

1 मध्यकालीन भारत में तकनीकी नवाचारों और आविष्कारों पर एक लेख लिखिए।

2 वर्तमान समय में जनसंचार के लोकप्रिय माध्यमों की सूची बनाइए और उनकी व्याख्या कीजिए ।

3 क खाद्य समूहों और उनके प्रमुख पोषक तत्वों को दर्शाने वाली एक तालिका बनाइए। ख जल संसाधनों के प्रबंधन के लिए क्या लक्ष्य निर्धारित करने की आवश्यकता है? जल का वैज्ञानिक तरीके से प्रबंधन कैसे किया जा सकता है?

4 संक्रामक और गैर-संक्रामक रोगों के बीच अंतर कीजिये. संक्षेप में चर्चा करें कि संक्रामक रोग एक व्यक्ति से दूसरे व्यक्ति में कैसे जाते हैं।

5 सौरमंडल के ग्रहों की विशेषताओं का वर्णन कीजिए।

6 उपयुक्त उदाहरण देते हुए स्पष्ट करें कि हाल की तकनीकी प्रगति ने आधुनिक शिक्षा प्रणाली को कैसे लाभान्वित किया है।

7 क कांस्य युग में वैज्ञानिक और तकनीकी उपलब्धियों की चर्चा कीजिए। ख पृथ्वी पर जीवन की उत्पत्ति के संबंध में विभिन्न सिद्धांतों और प्रयोगों का वर्णन कीजिए।

8 शुष्क क्षेत्रों, शुष्क भूमि और पहाड़ियों के संदर्भ में कृषि में वैज्ञानिक ज्ञान की भूमिका की व्याख्या कीजिए ।

9 समाज वैज्ञानिक विकास को कैसे प्रभावित करता है- उपयुक्त उदाहरण देते हुए समझाइए ।

10 विज्ञान और प्रौद्योगिकी की प्रगति और राष्ट्र के विकास के लिए आत्मनिर्भरता की नीति को आगे बढ़ाना क्यों आवश्यक है?

FST-01 Assignment Details

  • University IGNOU (Indira Gandhi National Open University)
  • Title Foundation Course in Science and Technology
  • Language(s) English and Hindi
  • Session January 2024 - December 2024
  • Code FST-01
  • Subject Science
  • Degree(s) BA , B.COM , B.Sc. , BSW , BTS
  • Course Foundation Courses (FC)
  • Author Gullybaba.com Panel
  • Publisher Gullybaba Publishing House Pvt. Ltd.

Assignment Submission End Date

The IGNOU open learning format requires students to submit study Assignments. Here is the final end date of the submission of this particular assignment according to the university calendar.

  • 30th April  (if Enrolled in the June Exams)
  • 31st October (if Enrolled in the December Exams).

Download Files & Sessions Details

Here are the PDF files that you can Download for this Assignment. You can pick the language of your choice and see other relevant information such as the Session, File Size and Format.

English Language

  • January 2024 - December 2024 24 Pages (0.00 ), PDF Format SKU: IGNGB-AS-BTS-FST01-EN-422
  • January 2023 - December 2023 16 Pages (0.00 ), PDF Format SKU: IGNGB-AS-BTS-FST01-EN-267

Hindi Language

  • January 2024 - December 2024 30 Pages (0.00 ), PDF Format SKU: IGNGB-AS-BTS-FST01-HI-422
  • January 2023 - December 2023 22 Pages (0.00 ), PDF Format SKU: IGNGB-AS-BTS-FST01-HI-267

What's Included

In this section you can find other relevant information related to the Assignment you are looking at. It will give you an idea of what to expect when downloading a PDF soft copy from GullyBaba.

  • All Solved Answers By IGNOU Experts.
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  • Downloadable Soft Copy in PDF.
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IGNOU Solved Assignments 2022-23

Table of Contents

The students of Indira Gandhi National Open university work very hard to secure good marks in the theory examination but they usually ignore the importance of Ignou assignments. So, after reading this article, they will come to know how important are Ignou solved assignments 2022-23  to appear in upcoming examination. Check guidelines to make a good IGNOU Assignment Front page .

Solved assignments are very important part of Ignou studies. The students need to obtain the minimum passing marks in both term end theory as well as in Tutor Marked Assignments (TMA).

Related Post: Ignou BA assignment submission status Ignou BA solved assignment free

As already mentioned in the Student handbook & prospectus, the learners need to submit one Tutor Marked assignment for each course which required it and also for which they are going to appear for the upcoming examination.

Note: If you need any help in solving assignments, you can send email at   [email protected] or Contact us on WhatsApp at 7428482160

Download IGNOU Assignments 2022-23

The university provides the latest assignment question papers for all the courses in the form of separate booklets on its official website.The 30% weightage is given to the assignments in the final marks.

To appear in the term end examinations, it is compulsory to submit the Ignou solved assignments 2022-23 for the respective courses. The learners who are enrolled in any of the Bachelor or Master degree programme are advised to carefully read all the instructions and guidelines to make good assignments.

These assignments are valid for two latest admission cycles i.e July and January.

The assignments have to be submitted at the concerned Study Centre. The last date to submit the solved assignments for both June or December term-end examinations can be checked in the question booklet.

We have provided the link below to download the Ignou assignment question papers:

  • IGNOU Assignments Download

Importance of IGNOU Solved Assignments

The Indira Gandhi National Open university offers the various programmes such as Master Degree (MBA, MCA, M.Com, MSW, MA, M.Sc, M.Ed., MTM), Bachelor Degree (BAG, BCOMG, BSCG, BA, B.Sc., BSW, BCA, B.Com, B.Ed, BTS, BAVTM), Diploma, Certificate, etc. in both January and July sessions of admission.

To successfully complete these disciplines within the minimum or maximum duration which is allowed by the university, the learners need to get the passing marks in the Term End Theory exams and Ignou solved assignments for all the required number of courses for a particular discipline.

Below we have mentioned a list of very important programmes for which the students need to make the assignments. These are as follows:-

  • IGNOU ACC 1 Solved Assignment
  • IGNOU BHDA 101 Solved Assignment
  • IGNOU BRPA 101 Solved Assignment
  • IGNOU ATR 1 Solved Assignment
  • IGNOU BSW Solved Assignment
  • IGNOU ASP 1 Solved Assignment
  • IGNOU AFW 1 Solved Assignment
  • IGNOU BGSE 1 Solved Assignment
  • IGNOU BCOC 131 Solved Assignment
  • IGNOU BCOC 132 Solved Assignment
  • IGNOU BPCC 131 Solved Assignment
  • IGNOU BSOC 131 Solved Assignment
  • IGNOU BPAC 131 Solved Assignment
  • IGNOU BECC 131 Solved Assignment
  • IGNOU BHDC 131 Solved Assignment
  • IGNOU BANC 131 Solved Assignment
  • IGNOU BPSC 131 Solved Assignment
  • IGNOU BHDLA 135 Solved Assignment
  • IGNOU BEGC 131 Solved Assignment
  • IGNOU BEGLA 135 Solved Assignment
  • IGNOU BEVAE 181 Solved Assignment
  • IGNOU M.Com Solved Assignments
  • IGNOU PGDIBO Solved Assignments
  • IGNOU PGDT Solved Assignment
  • IGNOU PGDEMA Solved Assignment
  • IGNOU BTS Solved Assignment
  • IGNOU CDM Solved Assignment
  • IGNOU DPLAD Solved Assignment
  • IGNOU PGDRD Solved Assignment
  • IGNOU PGDDM Solved Assignment
  • IGNOU PGDCFT Solved Assignment
  • IGNOU MSCCFT Solved Assignment
  • IGNOU MLIS Solved Assignment
  • Master of Arts in Economics (MEC)
  • IGNOU MEG Solved Assignments
  • IGNOU MA History Solved Assignments
  • MA in Public Administration (MPA)
  • IGNOU MSO Solved Assignments
  • MA in Political Science (MPS)
  • MA Rural Development (MARD)
  • MA Education (MES)
  • MA Hindi (MHD)
  • MA Philosophy (MAPY)
  • MA Psychology (MAPC)
  • MA Tourism Management (MTM)
  • Master of Business Administration (MBA)
  • Master of Computer Applications (MCA)
  • Master in Social Work (MSW)
  • Post Graduate Diploma in Rural Development (PGDRD)
  • Bachelor of Arts in Tourism Studies (BTS)
  • BA in Social Work (BSW)
  • BA Sociology (ESO)
  • BA Public Administration (EPA)
  • BA Political Science (EPS)
  • BA History (EHI)
  • BA Hindi (EHD)
  • BA English (EEG / BEGE)
  • Bachelor of Education (B.Ed)
  • Bachelor of Commerce (B.Com)
  • Bachelor of Computer Applications(BCA)

We hope this article will motivate you to make good IGNOU solved assignments 2018-19 to secure good marks.

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The person behind IGNOU student Zone is blogger by passion. Hi qualifications include B.E. Computers, MBA in Marketing, Google Certified in Digital Marketing.

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Sir, The last date of submission of assignment is 15th sept or 30th sept ?

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It is different for different courses. So, just check out assignment booklet for last date of ignou assignment submission.

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I am not getting acc1 assignment solved paper in complete way.. I hv download PDF bt​ questions are not provided on that .

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I need mgps12 assignment could u sent me please

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Sir i want BCA 1st semester SOLVE assignments 2017 july session Becose 15 oct. 2017 is last date of submission assignments And study material also not get

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Sir tell me how to migrate in ignou from one regional center to other

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should i write both on front and back of a page i mean sequence wise ?can anyone please tell me or reply me back?

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IGNOU Assignment Wala


  • Post published: March 3, 2023
  • Post category: Solved Assignments
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क्या आप इग्नू हल असाइनमेंट प्राप्त करना चहेते है ? हम  हल कार्य प्रदान कर रहे हैं। याहा दे गया लिंक से इग्नू बेवे 181 हिंदी हल असाइनमेंट पब्लिश किया गया है .  इग्नू ने असाइनमेंट ignou  fst 01 hindi  हिंदी 2022-23 हल किया. ignou fst 01

Title Name                                                        FST 01  English  Solved Assignment 2022-23

Service Type                                                     Solved Assignment (Soft copy/PDF)

Course                                                               Bachelor’s Degree Programme Under CBCS

Language                                                          HINDI  MEDIUM

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Read the section on Assignments in the Program Guide that IGNOU sent to you after your enrollment. A weightage of 30 per cent, as you are aware, has been prescribed for continuous evaluation, which will consist of tutor-marked assignments for this course. The assignment is in this booklet, and it consists of two parts, Part A and B. The total marks for all the parts is 100, of which 35% is required to pass it.

The important thing candidates should know is that in order to participate in IGNOU FST 01 Term End Examination (TEE), it is necessary to submit IGNOU assignments at the regional center of IGNOU. Without the assignment, candidates will not be allowed to appear in the examination. So, for this students have to first download their assignment, complete them and then submit it to the regional center of IGNOU.

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IGNOU FST-01 Assignment Question Paper Free Download (2023-24)

Valid for july 2023 and january 2024 sessions, if you want to download fst-01: foundation course in science and technology assignment question paper for 2023-24 sessions, you have come to the right place. please click on the image or button below to download the question paper. if you are looking for free solved assignment reference material for this subject, you may download that using the button below as well. this content is donated by gyaniversity publications and is verified by professors. it is plagiarism-free, so you can be assured to learn well and get the highest marks.

FST-01: Foundation Course in Science and Technology

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FST-01 assignment question paper and solved assignment is applicable for 2023-24 sessions in IGNOU. In case you took admission or re-registered in a previous session but did not submit your assignments previously, you must use this latest question paper for submission as the old question papers are no longer valid. If you are looking to pass your exams easily, you can also check out the below guidebook which provides students with the most important questions that are most likely to appear in your final term end exams! Click on the image or button below to learn more about this.

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The top distance university offers bdp (ba / b.sc / b.com) online admission to the learners from all over the country. To get bdp / ba degree, students need to appear in Term End Theory Examination and submit their Ignou Fst 1 Solved Assignment 2024 before last date.

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Every year, the distance university upload fst-01 assignment questions booklet on their official website. The fst-1 assignment will remain valid for July 2023 and January 2024 session.

The FSt-01 Solved Assignment (TMA) is so important as term-end examination. The fst 1 assignment work consist 30% of the total marks required to complete any course while theory part consists 70% marks (remaining).

Ignou FST-1 assignment is of 100 marks. There are total of 8 questions and students have to answer all the questions. The Fst-1 Assignment is based on all the blocks of this course.

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IGNOU BCom A&F Assignment 2023-2024 (July – January)

IGNOU BCom A&F Assignments 2024 - IGNOU BCom A&F Assignment Question Paper has been uploaded by the university for its current session 2024. The students of the BCom A&F program can now download the Assignment Questions from this page. Candidates have to compulsory download and submit these assignments with the solutions to the university to get permission for attending the Term End Exam of the IGNOU BCom A&F Program.

We also inform all BCom A&F students that the assignment questions for each of the courses of the IGNOU BCom A&F program are available for download from here. You have to prepare each of BCom A&F assignment separately so that IGNOU Evaluators can easily understand and identify the course code of each subject.

  • IGNOU BCom A&F Syllabus
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Name of the Program Bachelor of Commerce with Major in Account & Finance
Session 2024
Applicable For TEE June 2024 & December 2024

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Each of the Assignment questions will have different marks and the same will be printed on each question. Candidates should write the solutions to all questions according to the instructions given in the IGNOU BCom A&F Assignment Question Paper . The BCom A&F students have to submit the Assignments for each course to IGNOU Study Centre in which they get registered. The candidates have to submit it before the due date to appear in Term End Exam conducted by IGNOU.

IGNOU BCom A&F Assignment Submission Last Date for 2024

Here is the Last Date for Submission of the IGNOU BCom A&F Assignment to appear in the Upcoming Term End Exam June 2024 or December 2024 .

For TEE June 2024 15th May 2024 (Extended)
For TEE December 2024 30th September 2024

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If you have completely solved your assignment then you have to submit your IGNOU BCom A&F Assignments to the coordinator of the study centre which is allotted to you at the time of admission. Don’t forget to get a receipt for the submission of BCom A&F Assignments.

After preparing the solution for your BCom A&F Assignment, you have to submit IGNOU Assignments to the coordinator of the study centre which was allotted to you at the time of taking admission. Moreover, Don't forget to get a receipt for the submission of BCom A&F Assignments.

197 thoughts on “IGNOU BCom A&F Assignment 2023-2024 (July – January)”

Can anyone please tell me what assignments to write for bcomaf? The list of assignments. Because only 3 are appearing when I click on bcomaf which is eco12, eco13 and aed01.

Hi, did you get your answer for this ? I had submitted assignments for Business Environment and Export Documentation. Are we supposed to submit assignment for 3 English papers and 1 elective? (My elective is FST 01)

Dear Sir/Madam,

I had submitted the assignments of all the subjects but the marks of BSHF 101 is not reflected in gradesheet

Sir, I have taken admissions for Jan 2020 session, but till now I didn’t attended exam, now I will attend for 2021 December exams, which assignment I need to submit and when is the last date


Hi how many assignments in total for BCOMAF course in website there are only 3 eco 12, eco 13, aed 1 I dont have eco 12 subject in my subjects anyone please help

Hey did you get an answer fr your query

did you got the answe for it?? i have the same querry

Hello sir, Im CA IPC student and i registered for BcomAF in june 2017 from that date no action from me has done like records submission and exam application nothing done. Now i wanna write exams for Dec2021 atleast i dont what to do. I got my enrollment number had my admission details showing valid upto 2023. Kindly pls someone help what to do further.

did you get the answer I had a same query for dec 2024

sir i have question that when i can apply and what is last date for the same

Dear sir/Madam, Please provide me the assignment number in BSHF-101 For the session Dec 2019. Because assignment number were missing.

Sir, I have enrolled in Jan 2019, which assignments which be applicable for me?

I have registered for B Com A&F in July 2019 session. I have to write the assignment of subject FST-01. When I am trying to download FST 1 assignment from here. On the first page of question paper it is showing that it is valid from January 2020 to December 2020. There is a lot of confusion whether to write that assignment or not? whether that assignment was valid for me or not? If not Valid, where is my valid assignment and where can i find it.

Following is the link or the website from where i was trying to download the assignment https://www.ignouhelp.in/ignou-bcom-af-assignments/

Sir I have applied for BCOM (A&F) for June 2020 exams. I have received books but not yet received the ID card. So can you help me in getting ID card and to submit assignments with roll number

One small query Do BHSF -101 & FHS -01 are same? Can you please share question paper for FHS – 01

When I’ve signed up for Bcom A&F, they have said that you shall write 6 assignments only. But when I have went to IGNOU website and searched for assignments then only 3 assignments are showing up. Now in this website, you are showing 7 assignments and ECO-12 is also not present in this website. Can anyone tell me that which assignments should I complete?? I have completed CA Inter and taken up this course.

I m having same doubt, as of Pravin, kindly help

I also have the same doubt. Plz help

Same doubt Anyone get its answer ? Please reply

Where should we write the assignments of ignou? Whether in A4 papers or any booklet will be issued for the purpose of writing? if the assignment is to be written in A4 papers, whether they can be spiral binded and what are the details to be mentioned on the assignment i.e., name etc as such.

Kindly help me regarding the issue.

I have enrolled for Bcom A&F in July 2019 session. Assignment for EEG-04 is not available.

I have enrolled for Bcom A&F in July 2019 Session. Assignment for EEG -04 is not available. And is the subjects IBO-04 and AED-01 same?

Dear Helpdesk,

I have enrolled to Bcom (A&F) in Jan 17 circle, but was unable to write exams due to personal reasons. I want to write now i.e., in Jan 20. My queries are : 1) Is my registration still valid, so that i can appear in Jan 20 2) Which set of assignments i need to write 2018-19 or 2019-20

please help in this issue.

Thanks and regards

i have the same doubt.pls someone help me..ramesh if u know the answer pls let me now

i have enroll in January 2017, but not given exam yet so now i want to appear for exam in December. 2019, so which assignment i have to write for example assignment 2018-19 or assignment 2019-20.

please tell me as early as possible.

i want to change my stream from bcom to bcom ca&f please suggest me

Sir i have my bcom af exam in dec 2019, so which session assignment i have to submit. 2018-19 or july 2019 session??

Sir I am first year student of b.com a&f Jan 2019 . Sir kya muje 2018-19 wali assignment ready karni hai ya 2019-20 wali. Am very confused plz reply me on my mail I’d as soon as possible kyo k muje ye 15sep tak submit karni hai

i need BEGE 101 assignment…plzz help.

dear sir, I have enrolled for b.com there is one assignment which is missing on this column i.e. BECE2. So kindly update that. Thank You.

Sir , i have to appear for dec 19 exams, are the assignments above applicable?

Good Afternoon

I registered for Bcomaf on July 2018 & I am planning to write exam on December 2019. So will a new set of assignments come on September 2019 ?

Dear Sir, on assignment section only three subject are showing, how will i get assignment question for other subject

My exam is on December 2019, can I use these assignments for submission

Sir, what is the last date for submission of B.com A&F assignments. i am confused. is it 15th march,2019 or 31st march,2019

I Have enrolled myself for IGNOU A&F Course Last September (2018) which makes me eligible to appear for TE Examination June 2019. However, till date I havn’t received full study material (Only 2 subjects received) because of which I was not able to complete all of my assignments. Kindly let me know..

1) Last Day for submission of assignments for A&F Course?

2)How & when can I get my study material, in order to complete assignments?

Kindly Reply or revert me at my Email

Your support is essential to us.

Dear sir Am i eligible to appear in june 2019 term end examination If my admission year is jan 2019 in BCOMAF.

Sir, does the last date for submission of assignment of bcom(a&f) has been extended for june 2019 exams?

I have registered for BCOM A&F via online admission. While filling the exam form for it only shows three subjects FEG2, BSHF101 and BEGF101. But I have also registered for AED1,BEGE104 and ECO13. Please let me know why these three courses are not being shown in the form.

Sir I am CA student and doing BCOM AF from ignou. Till date no assignment uploaded on the Site given by ignou for Assignments. So can i consider the above listed assignments as authentic ?(my exams due in June) And if someone knows what all are the procedure i need to undergo for BCOM AF, kindly help since i know nothing about this (like Assignment exams Books material and other stuffs)

u need to write and submit assignments at your study centre by march 15

Hi sir , for BCOMA&F What all are the list of assignments we have to submit to the regional office

Dear Sir I am unable to Download BHDE- 108 Please tell me When it will be Available to Download You can reach me either by mail

Hi BEGF 101 is not reflecting for 2018-19, please tell me when it will be available.

What Is The last date To submit BCOMAF Assignments (For June 2019 TEE Session)

SIr, Please Upload Assignment for BEGF-101.

Sir, I have registered for bcom a&f, BEGF 101 And BSHF 101 are missing in this list. Kindly update it sir

Please kindly upload BSHF 101 2018 -19 assignment

Dear sir , i have enrolled for b.com a&f there are 2 assignments which are missing on this column i.e BEGF-101 & BSHF-101 so kindly update that . Thanking you

From where I will get that

Assignment FHD 2 is missing please upload it soon.

sir BHDE 108 and FHD 2 assignment nhi hai

sir , i have registered for july 2018-2019 session bcom a and f but upto now i have not received the books i contacted ignou but they told they have dispatched but we got only two subject books so kindly consider my issue

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  • Published: 01 July 2024

Genetic and phenotypic diversification in a widespread fish, the Sailfin Molly ( Poecilia latipinna )

  • Ralph Tiedemann   ORCID: orcid.org/0000-0002-2604-6336 1 ,
  • Rüdiger Riesch 2 , 3 , 4 ,
  • Maxi Tomowski   ORCID: orcid.org/0009-0004-9231-3457 1 ,
  • Katja Havenstein 1 ,
  • Jan Schlupp 4 , 6 ,
  • Waldir Miron Berbel-Filho   ORCID: orcid.org/0000-0001-6991-4685 4 , 5 , 7 &
  • Ingo Schlupp   ORCID: orcid.org/0000-0002-2460-5667 1 , 4 , 5  

BMC Ecology and Evolution volume  24 , Article number:  87 ( 2024 ) Cite this article

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Widespread species often experience significant environmental clines over the area they naturally occupy. We investigated a widespread livebearing fish, the Sailfin molly ( Poecilia latipinna ) combining genetic, life-history, and environmental data, asking how structured populations are. Sailfin mollies can be found in coastal freshwater and brackish habitats from roughly Tampico, Veracruz in Mexico to Wilmington, North Carolina, in the USA. In addition, they are found inland on the Florida peninsula. Using microsatellite DNA, we genotyped 168 individuals from 18 populations covering most of the natural range of the Sailfin molly. We further determined standard life-history parameters for both males and females for these populations. Finally, we measured biotic and abiotic parameters in the field. We found six distinct genetic clusters based on microsatellite data, with very strong indication of isolation by distance. However, we also found significant numbers of migrants between adjacent populations. Despite genetic structuring we did not find evidence of cryptic speciation. The genetic clusters and the migration patterns do not match paleodrainages. Life histories vary between populations but not in a way that is easy to interpret. We suggest a role of humans in migration in the sailfin molly, for example in the form of a ship channel that connects southern Texas with Louisiana which might be a conduit for fish migration.

Peer Review reports


Patterns of biodiversity and speciation continue to intrigue evolutionary biologists and ecologists [ 1 ]. At the nexus of this debate is the question about the mechanisms that lead to differentiation and potentially speciation. Nonetheless, the flipside of this, the lack of differentiation where it may be predicted, is equally important to consider. For example, many organisms are geographically widespread, with multiple populations exhibiting different degrees of reproductive isolation and experiencing various ecological conditions. Yet they appear to exhibit little to no diversification at the species level [ 2 ], which could be due to a host of factors, including a lack of geographic isolation amongst populations, intense gene flow, demography, or short time since population establishment [ 3 , 4 ]. There are examples of genetic differentiation in the absence of phenotypic differentiation, for example in Bororas maculatus from Malaysia [ 5 ] and in Microrasbora rubescens from Myanmar [ 6 ]. This is in stark contrast to the rapid differentiation and even speciation found in some taxa, such as cichlid fishes of the East African rift valley [ 7 ], Laupala crickets in Hawaii [ 8 ], and toads [ 9 ].

Sometimes, cryptic diversity can be detected at the molecular level, but is not reflected in taxonomically relevant morphological traits. Cryptic diversity in bryophytes is a great example of this [ 10 ]. Thus, understanding the patterns of cryptic diversity is crucial for understanding the evolution of biodiversity [ 11 ], and additionally may provide guidance for the conservation of species [ 12 ]. In fact, cryptically diverse taxonomic units may present different responses to Global Change [ 13 ].

One driving factor of cryptic diversity is geographic isolation (i.e., allopatry), which, in freshwater fishes, is usually related to water connectivity [ 14 ]. Indeed, freshwater fishes are models to understand the biogeographical history of a region, given that their natural distribution and dispersal relies on both current and historical connections between river drainages. Two major events are frequently invoked to explain the disjunct distribution of freshwater fishes among isolated rivers: (i) river captures, an inland event that happens when a river system changes its course and connects with another drainage system due to geological activities [ 15 ] and, (ii) paleo-drainage connections, a coastal event that refers to sea level fluctuations caused by climatic changes, occasionally causing basins that previously were isolated to coalesce (sea level decrease), or previously-connected river basins to become isolated (sea level increase) [ 16 ]. Geographical isolation between river systems is expected to restrict gene flow and to enhance population and local differentiation.

In the present paper we explore the biogeographical history as well as the genetic and phenotypic diversity of a widespread species, the Sailfin molly ( Poecilia latipinna ) [ 17 ]. The sailfin molly is a livebearing fish of the family Poeciliidae. They show ovoviviparity and have internal fertilization [ 18 ] (see Supplementary material for additional information). This freshwater fish exhibits an exceptionally large geographical range, compared to some other livebearing fishes. For example, a close relative, P. latipunctata [ 19 , 20 , 21 ] is only known from a small area in Northeastern Mexico [ 22 ]. Poecilia latipinna typically has a narrow coastal distribution that follows the coastline first along the Gulf of Mexico, around the tip of Florida, and then along the Atlantic Coast of the US, covering ca. 4,600 km of coastline. In Florida, it is also widely found inland [ 23 ].

Their overall distribution range predicts that Sailfin mollies should be experiencing several ecological clines, which might provide opportunities for local adaptation and restriction of gene flow, which might in turn lead to genotypic and phenotypic divergence. Yet at least some of the morphological variability associated with geographical distance seems to be due to phenotypic plasticity [ 17 ]. For example, Sailfin mollies experience high temperatures in the summer of over 35ºC in Tampico, Tamaulipas [ 24 ] to winter temperatures below freezing in Wilmington, North Carolina [ 25 ]. Ecological niche modeling has indicated that temperature largely determines the distribution of Sailfin mollies, with the lowest winter temperatures defining the northern limit of the range [ 26 ]. This is particularly relevant because many aspects of fish life histories are temperature-dependent (e.g., in sailfin mollies: [ 17 ]; eastern mosquitofish, Gambusia holbrooki : [ 27 ]; Phalloptychus januarius : [ 28 ]; pumpkinseed, Lepomis gibbosus : [ 29 ]. Such a cline in temperatures may lead to locally adapted populations. On the other hand, Sailfin mollies are also known to be euryhaline occurring in both freshwater and coastal lagoons, and being able to tolerate marine [ 30 , 31 ] and even hypersaline conditions [ 32 ]. This ability may allow them to migrate between river systems, effectively limiting local adaptation and population differentiation via dispersal and gene flow.

Sailfin mollies are considered ecological generalists and feed on detritus, aquatic invertebrates, and food that lands on the water surface [ 33 ]. Furthermore, in their food-web, they are prey for fishes, birds, and reptiles [ 34 ]. In addition to their native range, they have been introduced widely (e.g., in Central Texas [ 35 , 36 ]), either because they were used as bait, or through the aquarium trade, where Sailfin mollies are considered both attractive and hardy pet fish [ 37 ]. Overall, Sailfin mollies have long been a model for research in behavior, ecology, and evolution [ 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ] (for additional background on Sailfin mollies see Supplementary Backgound Information).

Using the Sailfin molly as a model system to address evolutionary questions in widespread species we apply a multifaceted approach to analyze patterns of potential cryptic biodiversity. Based on samples taken along most of the natural range of the Sailfin molly we used microsatellite data to detect cryptic variability and infer population genetic structure. This genetic analysis was then used as a baseline for subsequent analyses of phenotypic traits that should be sensitive to environmental clines, namely life-history traits. Hence, in this study, we were interested in utilizing the power of genetic population delimitation to predict differences in life history.

More precisely we addressed the following questions: (1) Is there cryptic genetic diversity in P. latipinna ? (2) Does the genetic structuring coincide with the biogeographical history of the region? Finally, (3) is variation in life-history traits linked to the observed genetic variability? We hypothesize that based on the wide distribution of the species there might be local adaptation and cryptic diversity. We also hypothesize that, provided that genetic diversity is governed by biogeographical barriers, life histories will differ between the genetic lineages.

Materials and methods

Specimens were collected in the summer of 2008 between June 10 and 20. Starting near Angleton, Texas, for the main field campaign, we (RR, JS, IS) collected samples east and north along the coastline of the Gulf of Mexico to Florida. Northern Florida was crisscrossed to additionally sample inland populations, while Southern Florida was not sampled due to logistical limitations. After sampling Florida, we followed the coastline to North Carolina, where the northernmost native population was sampled in Wilmington, North Carolina. We further added a site from Brownsville, South Texas, on July 1, 2008 (RR, IS). Poecilia latipinna is also found in Mexico to roughly the mouth of the Rio Tuxpan, but this area was not sampled due to logistical constraints. We assume that our study only includes natural populations. We did - for example - ignore populations in Central Texas which had been introduced in the 1950’s, presumably from Florida [ 35 ].

Conditions permitting, we established a sampling site approximately every 50 km. At every sampling site, we measured several habitat variables using a Hydrolab Datasonde 4a Probe with a Surveyor 4 Series Data Display (Hach Company, Loveland, Colorado) (Supplementary Table 1 ) and took representative habitat photos (not shown). Measuring Chlorophyll a was done with a Turner Designs SCUFA Fluorometer [ 47 ].

Fishes were collected with a standard 2 m seine (3.2 mm mesh width) (Memphis Net & Twine, Memphis, Tennessee). We stopped when we had collected at least 20 Sailfin mollies within ca. 30 min of seining or were unable to collect more. Hence, catch per unit effort varied with site. Specimens were sacrificed in the field and immediately stored in 70% ethanol. This way, we sampled a total of 46 sites between Brownsville, TX and Wilmington, NC. We used 18 populations for population genetic analysis and subsequent life-history analysis, with a minimum requirement of five collected specimens per population. Data from the same sampling campaign were previously published in studies on mtDNA [ 48 ] and multiple paternity in Sailfin mollies [ 49 ].

Molecular analyses

We sampled dorsal fin clips from 18 populations ( n  = 168) of Poecilia latipinna along the Gulf of Mexico and the Atlantic coast of Florida, South and North Carolina (Fig.  1 ; see Supplementary Table 2 for location details).

DNA was isolated as in Tiedemann (2005). We genotyped 14 microsatellite loci originally developed for a closely related species ( P. formosa ), namely (primer set I) GT-I41, GA-IV42, GA-I29B, GA-III29B, GA-V18, GA-III49A, GA-II41, GA-I47A, GA-II33, and (primer set II) GA-I13B, GA-I5B, GT-I34, GT-I49, GA-I26 [ 50 ]. About 100ng of genomic DNA were used as template. PCR was performed in a total volume of 25 µl, containing 10mM Tris-HCl, pH 9.0, 50mM KCl, 1.5mM (primer set I) resp. 3mM (primer set II) MgCl 2 , 0.2mM (primer set I) resp. 1mM (primer set II) of each dNTP, 0.136µM (primer set I) resp. 0.16 µM (primer set II) of both forward and reverse primer (one of them 5’-fluorescence-labelled), and 0.5U Taq polymerase (MP Biomedicals; primer set I) resp. 0.6U My Taq polymerase (Bioline; primer set II). Amplifications were performed in a Biometra TGradient thermocycler according to the following reaction profile: Primer set I: one cycle 94 °C 5 min,18,040 cycles 94 °C 30s, the locus-specific annealing temperature (Supplementary Table 1 ) 1 min,18,172 °C 45s; a final extension at 72 °C for 10 min. Primer set II: one cycle 95 °C 1 min, 35 cycles 95 °C 15s, the locus-specific annealing temperature (Supplementary Table 1 ) 15s, 72 °C 10s; a final extension at 72 °C for 10 min. Fragment size was determined on an ABI 3130xl automatic sequencer, using the GENEMAPPER 4.0 software and an internal size standard (GeneScan500(-250)-LIZ, Applied Biosystems). Based on the microsatellite data (Supplementary Table 2 ) population specific genetic diversity parameters, observed and expected heterozygosity (HO, HE) as well as rarefied allelic richness (AR), total allele number and inbreeding coefficient (FIS), were obtained using the Hierfstat package [ 47 ] in R (Version 4.2.2) (Supplementary Table 3 ). Population specific genetic diversity parameters, observed and expected heterozygosity (H O , H E ) as well as rarefied allelic richness (A R ), total allele number and inbreeding coefficient (F IS ), were obtained using the Hierfstat package [ 51 ] in R (Version 4.2.2) (Supplementary Table 4 ). Significant deviation from Hardy-Weinberg-Equilibrium was determined using the hw.test function implemented in the {pegas} package [ 52 ] with 1,000 permutations.

We further investigated levels of population differentiation by calculating pairwise Fst and G’st distances [ 53 , 54 ] between local populations as well as their respective 95% confidence intervals using 10,000 bootstrap replicates in the {diveRsity} package [ 55 ].

To test for a correlation between pairwise genetic distance and geographical Euclidean distance, a Mantel test for isolation by distance (IBD) was performed in R using the {adegenet} package [ 56 ]. The significance of the correlation was evaluated using the mantel.randtest function with 10,000 permutations. We conducted a further IBD test based on a reduced sample set omitting populations from central and east Florida to exclude a potentially confounding effect of continental barriers on the IBD inference.

Population structure was inferred using the Bayesian clustering analysis implemented in STRUCTURE Version 2.3.4 [ 57 ]. We conducted 10 simulations for each putative genetic cluster value (K) from two to 20 with a 50k burn-in period followed by 200k Markov Chain Monte Carlo (MCMC) repetitions under the admixture model without prior population information. The optimal number of clusters was determined by plotting the likelihood of K for each value of K ( LnPr ⌈ X | K ⌉ ) using the △ K method [ 58 ] in the {Pophelper} package [ 59 ] in R. Clustering results of individual membership probabilities were visualized with the implemented {pophelperShiny} App.

We conducted a hierarchical AMOVA to estimate variance components among genetic clusters revealed by STRUCTURE and among local populations nested within clusters in Arlequin Version 3.5 [ 60 ] using 20,000 permutations.

To identify potential barriers to gene flow, a spatial principal components analysis (sPCA) was performed based on Moran’s I index of spatial autocorrelation in {adegenet}, accounting for differences in allele frequencies between sites depending on geographic distance. We chose the Delaunay triangulation method to weigh network connectivity. Monte Carlo resampling tests with 10,000 iterations were performed to test the statistical significance of global and local spatial structures. The scores of the resulting first eigenvectors of the sPCA were mapped to their corresponding geographic coordinates.

Recent dispersal was assessed by first-generation migrant detection in GENECLASS2 [ 61 ]. We applied the Bayesian criterion of [ 62 ] and the resampling method proposed by [ 63 ] with 10,000 simulations to compute the probability of an individual belonging to its local or an external gene pool using a probability threshold of 0.05.

Palaeodrainage reconstruction

Palaeodrainage configuration during the Last Glacial Maximum (LGM) was reconstructed using topographic and bathymetric data available in the General Bathymetric Chart of the Oceans website ( https://www.gebco.net/ ). A bathymetric 30 arc-second grid layer containing the Gulf of Mexico area and the United States of America East Coast was uploaded and processed into ArcGIS Pro software, with the Hydrological tools add-in used to reconstruct the palaeodrainages, according to the protocol described in [ 64 ]. Briefly, the area exposed during the LGM (-125 m from current sea level) was identified using the tool Contour followed by Mask. The options Fill (to fill the depressions on the surface), followed by Flow Direction (identify the steepness within each cell), Basin (delimit watershed borders), and Stream order (to estimate putative palaeorivers) were used to reconstruct and visualize the palaeodrainages. A detailed protocol for palaeodrainages reconstruction is available at https://github.com/waldirmbf/Paleodrainages .

Life-history measurements and analyses

Life-history traits could be quantified in 14 populations for males (i.e., NET, CAM, LA1, LA2, MIS, WF1, WF5, CF1, CF3, CF4, EF2, EF3, SC1, and LPB) and 11 populations for females (i.e., CAM, LA1, MIS, WF1, WF5, CF1, CF3, CF4, EF3 and LPB) – based on the availability of sexually mature males and gravid females. Preserved specimens (different individuals than the ones used for population genetics) were sexed based on external characteristics and dissected following well-established protocols [ 65 , 66 ]. In short, reproductive tissues (testes for males and ovaries for females) were removed and the fish were weighed and measured for standard length. Developing offspring, if present, were separated, counted, and their stage of development determined [ 67 ]. All tissues were then dried for 24 h at 55ºC and subsequently weighed again. To assess the amount of soluble fats, tissues were then rinsed at least six times for a minimum of 6 h in petroleum ether [ 68 ]. All tissues were reweighed one last time after fat extraction. This protocol provided us with the following four life-history traits for males: SL [mm], lean mass [mg], fat content [%] and gonadosomatic index, GSI [%; male testes mass divided by the sum of male testes dry mass and male somatic dry mass]. For females, we collected the following seven life-history traits: SL [mm], lean mass [mg], fat content [%], fecundity [the number of developing embryos], offspring lean mass [mg], embryo fat content [%] and reproductive allocation, RA [%; total embryo dry mass divided by the sum of total embryo dry mass and female somatic dry mass].

To facilitate meeting model assumptions of most subsequent analyses, life-history data were log 10 -transformed (SL, lean mass, embryo dry and lean mass), square root-transformed (fecundity) or arcsine-transformed (fat content, embryo fat content, GSI, and RA), and then z-transformed (to remove scaling effects). Male size distributions in natural populations of Poeciliids are often bimodal [ 69 , 70 ]. We therefore first evaluated the distribution of male SL in each population by conducting a series of Shapiro-Wilk tests.

We then ran several preliminary analyses to explore population-level variation in male and female life-history traits. First, we ran two sex-specific univariate general linear models (GLMs) on male and female SL with ‘Genetic Cluster’ (based on k identified by STRUCTURE; see above) and ‘Population-nested-within-Genetic Cluster’ [henceforth Population(Genetic Cluster)] as independent variables. This was followed by two sex-specific multivariate GLMs. For males, the dependent variables were lean mass, fat content and GSI, male SL was included as a covariate, and ‘Genetic Cluster’ and ‘Population(Genetic Cluster)’ served as independent variables. For females, the dependent variables were lean mass, fat content, fecundity, embryo lean mass, embryo fat content and RA. As covariates we included female SL and embryonic stage of development and as independent variables, we again used ‘Genetic Cluster’ and ‘Population(Genetic Cluster)’. These preliminary analyses confirmed significant population-level variation (see Supplementary Results), so we proceeded with our planned analyses.

To evaluate if some of the population-specific variation in life-history traits could be explained by local habitat variables, we reduced the variables water temperature, pH, turbidity, Dissolved Oxygen (DO) [%] and salinity via sex-specific Principal Component Analysis – since we had different numbers of populations for analyses of male and female life-history traits. For males, this resulted in two principal components (PCs) being extracted that explained 72.06% of the total variance. PC1 mainly corresponded to water temperature, DO, and salinity, while PC2 mainly corresponded to pH, turbidity and to a lesser extent also DO (Supplementary Table 5 ). For females, we extracted two PCs with a cumulative variance of 74.38%. Here, PC1 mainly loaded highly for water temperature, DO, salinity, and to a lesser extent also pH, while PC2 mainly represented turbidity and to a lesser extent pH and DO (Supplementary Table 6 ).

We then used these PCs as covariates in a set of GLMs on male and female life-history traits of the same structure as described above, but the independent variable ‘Population(Genetic Cluster)’ was now replaced by PC1 and PC2 as covariates. All these life-history analyses were conducted using IBM SPSS (IBM Corporation).

Finally, we wanted to evaluate if phenotypic differentiation was associated with genetic differentiation (measured via pairwise F ST ). To that end, we condensed male and female life-history traits via sex-specific PCA, which resulted in 4 PCs capturing 100% of the total variance for males and 6 PCs capturing 100% of the total variance for females. Using population means for each PC and sex, we then calculated pairwise Euclidian distances in PC-space for each sex and correlated them to pairwise F ST distances via Mantel tests. Mantel tests were computed using the {permute} library (Simpson, 2022) and the {vegan} library [ 71 ] in R version 4.2.1 (R Core Team 2022) with 10,000 permutations.

Raw data is available on Dryad (DOI: https://doi.org/10.5061/dryad.2jm63xsxb ) and as supplementary data attached to this manuscript.

Population genetics

Detected clusters : One microsatellite locus (GA-I26) was monomorphic in all analyzed specimens and hence excluded from further analyses. The remaining 13 loci were all polymorphic with 4 (GT-I13B; GA-I5B) to 42 (GT-I34) alleles (Supplementary Table 3 ). All analyzed populations were in Hardy Weinberg Equilibrium at all analyzed loci (see Supplementary Tables 3 , 4 ).

Applying the hypothesis-free STRUCTURE approach to delimitate clusters of genetically related individuals detected profound population structure and yielded highest support (δ K ) for k = 6 clusters (Fig.  1 , Supplementary Fig.  1 ). These clusters were (1) populations west of Alabama, (2) a population adjacent to Alabama in the east (WF1), (3) populations along the west coast of Florida, (4) populations along the east coast of Florida (including two Florida inland populations), (5) inland populations of northern Florida, and (6) South Carolina. Most individuals were assigned to their respective clusters with high probabilities, only the individuals of EF1 and EF2 were ambiguous in their assignment, being mostly intermediate between the two adjacent clusters (Green and light-Blue). In the westernmost sampled population (LPB), we also observed some ambiguity in the assignment which may indicate an influx from further (unsampled) populations along the coast of Mexico. Comparing STRUCTURE assignment to geographic location (Fig.  1 ) does not only visualize shifts in genetic population structure but indicates some (albeit limited) genetic mixing from (1) WF1 (Red cluster) to adjacent populations to the east and (2) from South Carolina (SC1; Green cluster) to the east coast of Florida. This interpretation is supported by the elevated genetic diversity in these populations (Supplementary Table 4 ). Running STRUCTURE with higher k s (up to 10) tentatively sets apart four further clusters, i.e., LPB, MIS, CF2, and CF1/CF4 (Supplementary Fig.  2 ).

If we assign populations to groups according to their prevalent STRUCTURE assignment (k = 6), an analysis of molecular variance (AMOVA) apportions significant amounts of 16.9% of the variation to divergence among these groups (F CT =0.169; p  < 0.001) and 9.08% to divergence among populations within groups (F SC =0.109; p  < 0.001), while 74.03% of the variation is found within populations (Table  1 ).

figure 1

Genetic structure and its spatial distribution of P. latipinna genetic clusters. ( a ) Membership-coefficient plot with STRUCTURE results with optimal k = 6 inferred by Bayesian analysis. Each bar represents an individual genotype ordered by sampling location. Distinct colors indicate the relative cluster membership probability. ( b ) Sampling area, palaeodrainage reconstruction, and geographical distribution of genetic clusters found in Sailfin mollies. Pie charts colors represent the average membership proportion for all genetic clusters within a sampling site. Colors in the continent (and palaeodrainages) represent river basins reconstructed via palaeodrainage reconstruction (see Methods below). Dark solid line represents current coastline (0 m above sea level); dashed white line denotes sea level at the last glacial maximum (125 m below current sea level.) Orange cluster: west of Alabama; Red cluster: northwest Florida; Green cluster: Florida west coast; Light-blue cluster: Florida east coast; Dark-blue cluster: Florida inland; Yellow cluster: South Carolina

Genetic diversity (both heterozygosity and allelic richness) was generally lower in populations from the Gulf of Mexico (Orange cluster west of Alabama; except for the diverse population in Brownsville, TX (LPB)) and at the Atlantic Coast of South Carolina (Yellow cluster), while diversity was considerably higher around Florida, both at coastal and inland habitats (Fig.  1 ). At several loci, we found shifts in allele sizes between the more western populations (Orange cluster) and the rest. Two loci exhibited a specific allele (GA-I5B) or increased variability (GT-II33) in the populations directly east of Alabama (Red cluster, i.e., WF1 and WF2).

In pairwise comparisons, most populations were significantly diverged from one another (by means of significant fixation coefficient G’ st and F st , respectively (Fig.  2 )). Particularly high divergence among geographically adjacent populations was found west and east of Alabama (i.e., between MIS and WF1, G’ st =0.628) and between South Carolina (Yellow cluster) and the geographically closest populations of Central Florida (Blue cluster, G’ st =0.623). There was little or no genetic differentiation among most populations west of Alabama (Orange cluster; NET, CAM, LA1, LA2). Furthermore, one Central Florida population (CF3) was not genetically differentiated from proximate populations on both the east and the west coast of Florida.

Comparing geographic and genetic (G’st) distance over all pairs of populations by a Mantel test shows highly significant Isolation-by-Distance ( r  = 0.583; p  < 0.001), accounting for 46.7% of the genetic variation found (Fig.  3 ). A similar IBD-pattern was observed in the reduced sample that excluded populations from central and eastern Florida to account for continental barriers in IBD inference (see methods, r  = 0.581; p  = 0.002). The sPCA revealed a significant global structure, suggesting a correlation between genetic variation and geographic configuration of populations ( p  < 0.001). Accordingly, the mapping of scores of the first principal component illustrates a genetic cline from west to east (Fig.  4 ). However, tests evaluating local spatial structure showed no significance ( p  = 0.999). In general, the isolation-by-distance results suggest a low capacity for long-distance dispersal in P. latipinna .

Geographical distribution of clusters and paleodrainages : Our palaeodrainage reconstruction revealed 13 palaeoriver systems in which our 18 sampling sites with genetic data were located (Fig.  1 b). Plotting the average genetic clusters by sampling site revealed an interesting pattern: most of the genetic clusters followed the topology of multiple palaeoriver systems. For instance, the Orange cluster (west of Alabama) was distributed across four different paleoriver systems. In West Florida, two major genetic clusters (Red and Green) spanned across three different paleoriver systems. In East Florida and parts of Central Florida, the light blue lineage predominated, however, with a substantial level of admixture with the Green cluster from East Florida, being particularly admixed in the more coastal sampling sites. Still in Central Florida, the dark-Blue cluster was dominant and shared among two populations (CF1 and CF4), which belong to two different palaeodrainage systems, suggesting fish movement between sites. Finally, the Yellow cluster is dominant in a single palaeodranaige system in coastal South Carolina. In general, the spatial distribution of genetic lineages seemed to not be limited by the water boundaries of their paleorivers, with multiple instances of genetic clusters spanning several paleodrainages, as well as multiple paleorivers containing more than one genetic cluster.

Migration events : 20 individuals (11.9%) were identified as first-generation migrants using the L home method in GENECLASS2 (Fig.  5 ). While most migration events occurred within the same genetic cluster, the majority of them (16/20, Fig.  5 ) occur between sampling localities within different paleoriver systems. We detected four migration events across cluster borders involving locations of the west- and east coast of Florida (EF3, EF1, WF4). Overall, inferred recent dispersal occurred over medium to longer distances reaching several tens, and in rare cases, a few hundred kilometers.

figure 2

Heatmap and table of pairwise Fst (above diagonal) and G’st (i.e., Fst adjusted for different within populations’ heterozygosity, Hedrick 2005; below diagonal) between P. latipinna sampling points; grey (faint) values indicate non-significant G’st values (α = 0.05)

figure 3

Relationship of (log-transformed) geographic distance and genetic distance. Mantel test statistics are given for both the full data set (black) as well as for a reduced set excluding populations from central and eastern Florida (green)

figure 4

Map showing population scores of the first global and the first local principal component of the spatial principal component analysis (sPCA). Black squares denote negative values, white squares indicate positive values, with size proportional to absolute score

figure 5

Migration analysis Chord diagram showing first-generation migrants of Poecilia latipinna inferred by GENECLASS2 between sampling sites, with scaled sectors showing the sum of immigrants and emigrants detected, the link root/end width proportional to the number of migrants and arrows illustrating the direction of migration. Colors indicate the genetic clusters identified by STRUCTURE analysis

Life-history patterns

Male size was normally distributed in 11 out of 14 populations ( P  ≥ 0.255 in all cases) but deviated from normality in CAM ( W 15  = 0.735, P  < 0.001), CF4 ( W 20  = 0.824, P  = 0.002), and EF2 ( W 20  = 0.854, P  = 0.006). However, we did not detect bimodality in any of these three populations; rather, distributions were right-skewed with a few very large males (Fig.  6 ).

figure 6

Patterns of male standard length (SL) for four different populations ( a - d ). Male size did not deviate from normality in most populations (NET as an example in a) but was not normally distributed in the three sites CAM, CF4, and EF2 ( b - d ). Significant effects of our environmental Principal Components on male life histories ( e - j ). Male standard length (SL, e-f) and male fat content ( i - j ) are corrected for the significant influence of the respective other Principal Component ( e - f ), while lean mass ( g - h ) is corrected for differences in male SL and the respective other Principal Component

The environmental GLM on male SL revealed significant effects of both PCs [PC1: F 1,187 = 19.306, P  < 0.001, η p 2  = 0.094; PC2: F 1,187 = 4.093, P  = 0.044, η p 2  = 0.021] and of Genetic Cluster ( F 5,187 = 10.661, P  < 0.001, η p 2  = 0.222). Along PC1, the relationship was negative, so males were smaller in habitats with higher water temperatures, more dissolved oxygen, and greater salinity, while the relationship with PC2 was positive indicating males were larger in habitats with greater pH and turbidity. Regarding genetic clusters, males from Cluster 4 were the largest, Cluster 3 males were the smallest, and males from the remaining four clusters were intermediate. For female SL the results were similar (PC1: F 1,131 = 9.339, P  = 0.003, η p 2  = 0.067; PC2: F 1,131 = 13.617, P  < 0.001, η p 2  = 0.094; Genetic Cluster: F 4,131 = 3.680, P  = 0.007, η p 2  = 0.101). While Cluster 3 had both the smallest males and females, SL was largest for females from Cluster 5, with the remaining Clusters intermediate. Visual examination revealed negative relationships between female SL and both PCs, so that females got smaller with increasing water temperature, dissolved oxygen, salinity, turbidity, and pH (Fig.  7 , Supplementary Table 7 ).

The multivariate environmental GLM on the remaining male traits returned significant effects of the covariate SL ( F 3,184 = 3167.583, P  < 0.001), both PCs (PC1: F 3,184 = 24.618, P  < 0.001; PC2: F 3,184 = 12.962, P  < 0.001) and Genetic Cluster ( F 15,508 = 6.419, P  < 0.001). However, compared to SL ( η p 2  = 0.981), the effects of PC1 (0.286), PC2 (0.174) and Genetic Cluster (0.148) were much weaker. Post-hoc univariate comparisons (Bonferroni-corrected significance at ⍺ = 0.017) demonstrated that SL significantly affected male lean mass ( F 1,186 = 9427.448, P  < 0.001, η p 2  = 0.981) and GSI ( F 1,186 = 38.029, P  < 0.001, η p 2  = 0.170), but not fat content ( F 1,186 = 2.742, P  = 0.099, η p 2  = 0.015). While male lean mass increased with increasing SL, GSI decreased with increasing SL so that larger males had smaller relative testis mass. Genetic Clusters significantly differed in all three male traits (lean mass: F 5,186 = 3.362, P  = 0.006, η p 2  = 0.083; fat content: F 5,186 = 10.299, P  < 0.001, η p 2  = 0.217; GSI: F 5,186 = 4.680, P  < 0.001, η p 2  = 0.112; Supplementary Table 5 ). Male lean mass was greatest in Clusters 3 and 6 and by far smallest in Cluster 2, while fat content was highest in Cluster 2 and lowest in Cluster 5, and GSI was greatest in Cluster 6 and lowest in Clusters 2, 4 and 5. Both PCs significantly affected lean mass (PC1: F 1,186 = 57.894, P  < 0.001, η p 2  = 0.237; PC2: F 1,186 = 9.051, P  = 0.003, η p 2  = 0.046) and fat content (PC1: F 1,186 = 8.453, P  = 0.004, η p 2  = 0.043; PC2: F 1,186 = 30.947, P  < 0.001, η p 2  = 0.143) but not GSI (PC1: F 1,186 = 1.437, P  = 0.232, η p 2  = 0.008; PC2: F 1,186 = 0.182, P  = 0.670, η p 2  = 0.001). Visual examination revealed that lean mass increased with increasing temperature, oxygen content, and salinity (PC1), but also with increasing turbidity (PC2), while fat content decreased with increasing temperature, oxygen content, and salinity (PC1), but increased with increasing turbidity (PC2; Fig.  6 a-d).

figure 7

Significant effects of our environmental Principal Components on female life histories. Female standard length (SL; a - b ), fat content ( c - d ) fecundity ( e - f ) and embryo lean mass ( g - h ) are corrected for the significant influence of the respective other Principal Component; fecundity ( e - f ), lean mass ( i ) and reproductive allocation (RA; j) are also corrected for differences in female SL, while RA is further corrected for the significant effect of embryonic stage of development ( j )

The multivariate environmental GLM on the remaining female life-history traits indicated significant effects of the covariates SL ( F 6,124 = 375.528, P  < 0.001) and Embryonic Stage of Development ( F 6,124 = 9.585, P  < 0.001), both PCs (PC1: F 6,124 = 47.889, P  < 0.001; PC2: F 6,124 = 12.941, P  < 0.001) and Genetic Cluster ( F 24,434 = 8.904, P  < 0.001). The strongest effects were due to SL ( η p 2  = 0.948) and PC1 (0.699), while the effects of Embryonic Stage of Development (0.317), PC2 (0.385) and Genetic Cluster (0.295) were much weaker. Post-hoc univariate comparisons (Bonferroni-corrected significance at ⍺ = 0.008) demonstrated that SL significantly affected female lean mass ( F 1,129 = 1676.468, P  < 0.001, η p 2  = 0.929), fecundity ( F 1,129 = 172.164, P  < 0.001, η p 2  = 0.572), and RA ( F 1,129 = 11.007, P  = 0.001, η p 2  = 0.079; P  > 0.104 for all other traits), with all three increasing with increasing female SL (Supplementary Fig.  3 , a and b). Embryonic Stage of Development, on the other hand, significantly affected embryo fat content ( F 1,129 = 39.057, P  < 0.001, η p 2  = 0.232) and RA ( F 1,129 = 17.212, P  < 0.001, η p 2  = 0.118; P  > 0.032 for all other traits), with both traits decreasing with increasing developmental stage (Supplementary Fig.  3 , c and d). Genetic Cluster significantly affected all traits (female lean mass: F 4,129 = 4.716, P  = 0.001, η p 2  = 0.128; female fat content: F 4,129 = 19.521, P  < 0.001, η p 2  = 0.377; fecundity: F 4,129 = 9.300, P  < 0.001, η p 2  = 0.224; embryo fat content: F 4,129 = 3.758, P  = 0.006, η p 2  = 0.104; embryo lean mass: F 4,129 = 8.976, P  < 0.001, η p 2  = 0.218; RA: F 4,129 = 4.982, P  < 0.001, η p 2  = 0.133). Female lean mass was greatest in Genetic Clusters 1 and 5, intermediate in Cluster 4 and smallest in Clusters 2 and 3, while female fat content was highest in Genetic Cluster 2 and lowest in Genetic Cluster 5 (Supplementary Table 6 ). Fecundity was greatest in Cluster 1 and by far the lowest in Cluster 5, and the opposite pattern was discovered for embryo lean mass, which was by far the greatest in Cluster 5 and lowest in Cluster 1. Embryo fat content was greatest in Clusters 3 and 5 and lowest in Cluster 1, and RA was by far lowest in Cluster 5 and greatest in Clusters 2 and 3 (Supplementary Table 6 ). PC1 significantly affected all traits but embryo fat content (female lean mass: F 1,129 = 78.952, P  < 0.001, η p 2  = 0.380; female fat content: F 1,129 = 12.311, P  < 0.001, η p 2  = 0.087; fecundity: F 1,129 = 7.629, P  = 0.007, η p 2  = 0.056; embryo lean mass: F 1,129 = 63.764, P  < 0.001, η p 2  = 0.331; RA: F 1,129 = 9.664, P  = 0.002, η p 2  = 0.070; embryo fat content: F 1,129 = 0.585, P  = 0.446, η p 2  = 0.005) and PC2 significantly affected female fat content ( F 1,129 = 43.108, P  < 0.001, η p 2  = 0.250), fecundity ( F 1,129 = 9.009, P  = 0.003, η p 2  = 0.065) and embryo lean mass ( F 1,129 = 14.934, P  < 0.001, η p 2  = 0.104; P  > 0.084 for all other traits). Visual examination revealed positive relationships between PC1 and both female lean mass and fecundity, while the relationships between PC1 on one side and female fat content, embryo lean mass and RA on the other side were negative (Fig.  6 f-i). Similarly, female fat content and fecundity had a positive relationship with PC2 while PC2 and embryo lean mass had a negative relationship (Fig.  7 f-i). This means that female lean mass and fecundity increased with increasing water temperature, DO and salinity, but that female fat content, embryo mass and RA decreased along the same axis. Moreover, female fat content and fecundity increased with increasing turbidity, while embryo lean mass decreased. Based on our Mantel tests, neither male life-history distance ( r  = 0.024, P  = 0.442) nor female life-history distance ( r = -0.234, P  = 0.875) were correlated with genetic distance between population pairs.

We studied biogeography as well as population-genetic and life-history differentiation in a widespread fish species, the Sailfin molly ( P. latipinna ), and found very clear genetic structuring that is in general agreement with isolation by distance (IBD). Abiotic factors measured as a snapshot of the conditions we encountered during the collections did not appear to correlate with the distribution of the detected genetic clusters. In addition, life-history trait differentiation showed some congruence with patterns of genetic differentiation, but large proportions of the variation likely respond more strongly to local (i.e., site-specific), rather than cluster-specific, ecological factors.

Genetic differentiation and biogeography

Below we are evaluating the evidence we provide relative to three important concepts: isolation by distance (IBD), dispersal within paleodrainages and potential human-assisted dispersal. Overall, we have strong support for IBD, indicating reduced genetic connectivity among populations separated by longer distances due to limited dispersal. That seems to be the most “natural” scenario for a species like P. latipinna . Although they can tolerate marine conditions, they do not seem to be able to actively swim long distances. However, in some cases as indicated by our migration analyses, sampling localities separated by distinct paleorivers, and considerable distances had or have recent gene flow. Those connections do not align with the expected alternative explanation of dispersal via paleorivers. Altogether, our genetic findings suggest constrained long-distance dispersal in P. latipinna and connections between distant populations may not have been facilitated by past river connections but rather by relatively recent dispersal events. The fact that first generation migrants were frequently detected between paleoriver systems suggests that human-assisted dispersal, potentially combined with rare natural events with less predictable outcomes, such as hurricanes, tornadoes, and zoochory, may have shaped the genetic structure of P. latipinna .

In trying to dissect potential mechanisms for the pattern we detected, we noted that the genetic composition of populations west of Alabama (including the Mississippi) within the Orange cluster is remarkably homogeneous. The only exception was the population from Brownsville, Texas (LPB). This homogeneous pattern might be a consequence of unhindered migration by individuals via the “Intracoastal Waterway”, a ship channel that connects Brownsville in South Texas with New Orleans and the Mississippi delta. The channel continues to Carrabelle, Florida, but the eastern part is separated by the Harvey Lock in New Orleans, which may be impassible to Sailfin mollies. The Intracoastal Waterway, recognized as migration conduit for various fish species (including two species of Fundulus and the Least Killifish, Heterandria formosa ), has also been suggested to have played a role in the northward expansion of the Amazon molly ( P. formosa ), a congener of the Sailfin molly [ 72 ]. Sailfin mollies are likely capable of moving from river to river via the ocean due to their tolerance of high salinity [ 73 ], but the ship channel might allow them to move between areas without having to enter marine environments. In the ocean, near-shore currents are expected to drift any Sailfin mollies downcoast [ 74 ] in a western and southern direction but these near-shore currents exhibit considerable variability [ 75 ]. Movement of livebearing fishes across the ocean has been suggested in scenarios of colonization of islands in the Caribbean (e.g [ 76 ]). . , , and, due to sperm storage (allowing a female to have multiple broods without mating again), a single inseminated female could be capable of establishing a new population. This has been demonstrated in a close relative, the guppy ( Poecilia reticulata ) [ 77 ].

Why the Brownsville, Texas (LPB) population is different from the other populations west of Alabama (the Orange cluster) is unclear, but the admixture in this population may be influenced by genotypes occurring to the south, in Mexico, which we could not sample for this study. This, too, might be caused by a near-shore current that would transport Sailfin mollies northward up to the mouth of the Nueces River, where this current collides with a southward flowing current from Louisiana [ 30 , 78 ]. Such dynamic river networks may be a plausible conduit for stepping-stone dispersal.

More generally, while the homogeneous population structure west of Alabama is surprising, albeit potentially explained by the Intracoastal Waterway, the situation east of Alabama is much more complex. Here, as well, patterns are not easily explained by river drainages. In fact, palaeodrainages do not line up with the detected population structuring. The complex situation in Florida thus requires considering several alternative mechanisms of dispersal. Generally, the coastal populations starting in the Florida panhandle (red), continuing down the coast (green) and along the Atlantic coast (light blue) seem to reflect movement of genotypes along the coast in agreement with the predominant marine current systems in the area [ 79 ]. On the west coast, currents would mostly transport any Sailfin mollies southward after leaving the river mouths [ 80 , 81 ]. This is in agreement with the slow fading of Red genotypes as we look at the four populations from West Florida WF1–4). Notably, WF4 and WF5 are in different drainage systems, yet quite similar in genotype composition. On the east coast, currents would take Sailfin mollies northward, potentially explaining the dominance of the light blue genotype along that coast. However, there is also a strong presence of the dark green genotype, which is predominantly associated with the west coast. It is not clear how we can easily account for this, but several mechanisms seem plausible, including currents that flow from the Gulf of Mexico around the southern tip of Florida into the Atlantic [ 79 ]. Furthermore, river capture, a geological process, could connect previously separated streams facilitating the movement of aquatic organisms from drainage to drainage during flooding events (e.g., heavy rains, typically caused by hurricanes [ 43 ]. The very flat topography of Florida makes such flooding a plausible avenue for fish movement. Several studies have provided evidence that changing water levels in Florida (such as during flooding or drought) are a major driver of fish movement and dispersal, including movement of sailfin mollies and other poeciliid fishes [ 82 ,  83 ]. In fact, Florida is frequently hit by hurricanes [ 43 ], both on the Atlantic and the Gulf coasts. Dispersal aided by hurricanes has been suggested specifically for Sailfin mollies based on populations sampled before and after a hurricane [ 43 ]. However, it is difficult to attribute dispersal directly to individual events. Our samples were collected in 2008. During the hurricane season the year before, 2007, Tropical Storm ‘Barry’ passed over Florida - a potential influence on the fish migration [ 84 ]. Even if hurricanes may not move fishes directly, tornados, which originate over land, are capable of this and may contribute to the dispersal patterns we detected.

Of course, direct natural movement from populations in Florida, cannot be ruled out although it seems unlikely given the distances and the established pattern of isolation by distance. As seen in our migration analysis, transport of fishes by humans is likely to have played a role in the distribution of P. latipinna lineages. Sailfin mollies are popular as bait fishes and historically Sailfin mollies have been introduced from Florida or Louisiana by human activity to Central Texas in the San Marcos area, where populations have persisted since the 1950’s [ 35 ]. Our finding that Sailfin mollies may have moved along the ship channel reinforces the idea that the current genetic structuring in P. latipinna is not organized along river drainages or their past connections, but by a combination of natural and human-facilitated dispersal events. Examples of humans aiding the spread of small fishes as bait or for mosquito control are well established for Sailfin mollies and other species, including guppies ( Poecilia reticulata ) [ 77 , 85 ] and mosquitofish (genus Gambusia ) [ 86 , 87 , 88 ] and we suggest that this is more widespread than currently appreciated.

The situation in Central Florida is also quite interesting: two inland populations (CF1 and CF4) are very homogenous and represent their own cluster (dark-Blue). Notably, though, they are from two different river drainages. The southern of the two populations is in the same drainage as EF1 from the east coast, but there is no significant sharing of genotypes. The two populations south of them (CF2 and CF3) are mainly composed of the light-Blue genotype, linking them to populations from the East Coast. Together this seems to indicate limited movements in inland populations of P. latipinna , while the coastal populations are more connected.

Overall, the notable mismatch between palaeodranainages and the main genetic clusters in P. latipinna is in stark contrast to some recent findings on coastal fish biogeography, where paleorivers largely explained the distribution of the main patterns of genetic structure [ 64 , 89 , 90 ]. However, these previous studies were conducted on strictly freshwater species. Sailfin mollies differ from those species in several regards, which could help explain the different patterns we found in our study. First, given its euryhaline nature [ 31 ], P. latipinna may be and have been able to disperse between river mouth areas, connecting populations that are now shared among currently isolated rivers. Alternatively, human-induced fish movement may have also contributed to the sharing of genetic clusters among paleoriver systems. After all, P. latipinna is widely used in the aquarium trade, as bait fish, and for mosquito control [ 37 ]. Finally, river capture and/or flooding events may have connected some inland populations (such as CF1 and CF4 in Central Florida).

Life-history differentiation and geography

While there was considerable genetic structuring, only weak structuring was detected in our life-history analyses, and we did not find any correlation between pairwise-population genetic distances (via F ST ) and pairwise-population life-history distance in either sex (via Euclidean distances). Nonetheless, there were many differences in specific traits between genetic clusters. Most of these differences were idiosyncratic (i.e., not following clear patterns suggesting overarching clines between clusters) so that for different traits (both per sex but also across both sexes) it was usually different sets of genetic clusters that differed most from one another. Further, complex life-history traits are likely polygenic and subject to environmental influence (phenotypic plasticity). Nonetheless, these life-history differences between genetic clusters could indicate that at least some of the neutral genetic differentiation we uncovered might be mirrored by functional genetic differentiation reflecting local adaptation.

The only tangible signal we uncovered was for embryo lean mass, for which values were smallest for populations originating from the Western Gulf of Mexico Region (Cluster 1), intermediate for West and East Coast populations of Florida (Clusters 2, 3, 4), and greatest for populations from Central Florida (Clusters 4 and 5). Offspring size is known to respond to resource availability, competition, and predation, with offspring size usually being lower in high-resource, low-competition or high-predation environments [ 91 , 92 ], but these selective pressures can interact in complex ways (e.g [ 92 , 93 ]). This suggests the presence of large geographic gradients in predation, population density, and/or resource availability between each of these clusters and localities. For example, together with the fact that male size was also largest in sites from Central Florida, this could suggest that the inland populations in Florida might experience less predation than the coastal populations of Florida and the western Gulf region. Nonetheless, we currently lack the data to fully interpret this and call on future studies to investigate this further.

However, if we explore life-history patterns by themselves and in relation to local environmental variables, we detect several interesting patterns. First, in natural populations, male size of many Poeciliids is bimodally distributed with many small and large males but relatively few intermediate-sized ones [ 69 , 70 , 94 ], and it has been shown for swordtails (genus Xiphophorus ) that this bimodality is genetically controlled via the P -locus [ 69 ]. For sailfin mollies, previous results had been mixed with evidence of bimodality from some populations but not from others [ 17 ]. In our data, we did not find a single population with male size following a bimodal distribution, a pattern mirrored in some other mollies (e.g., Poecilia mexicana : [ 95 ], and Limia perugiae [ 96 ]). This might suggest that male size is not under the kind of genetic control described for other Poeciliids but could also simply be the result of environmental effects overriding potential genetic determination [ 94 ] or of populations being fixed for one allele at the P -locus.

It was no surprise that male and female lean mass, but also female fecundity, increased with fish SL (longer fish are heavier; larger females also ought to have more body cavity space to accommodate more developing offspring). However, GSI decreased with increasing male SL, likely due to the sailfin molly mating system. Smaller males usually invest less into male secondary characteristics (i.e., bold body and fin coloration and elaborate dorsal fins) and follow a sneaker tactic that relies on approaching females from behind and attempting to force copulations via gonopodial thrusting [ 97 , 98 , 99 ]. Large males, on the other hand, are usually very colorful, have elaborate dorsal fins, and rely on male courtship displays to attract female attention [ 98 , 100 ], with females generally preferring large over small males [ 46 , 99 ]. Smaller males investing more into relative testis size than larger males to facilitate their mating behavior of forced copulations makes intuitively sense and has been found before [ 101 ].

We found RA and embryo fat content to decrease with increasing developmental stage. Both of these patterns have been well documented in poeciliid fishes [ 102 , 103 ]. Sailfin mollies are predominantly lecithotrophic species (i.e., almost all resources needed for embryo development are usually stored in the yolk prior to fertilization), although they can supplement embryos with additional nutrients under some environmental conditions [ 102 , 104 ]. This means that embryos will lose roughly 40% of their mass during embryo development, which will result in a lower RA towards the end of pregnancy compared to RA closer to fertilization [ 102 ]. Similarly, embryonic fat content usually also declines with increasing embryonic stage [ 67 , 103 ], probably because fat reserves in the yolk get metabolized by the embryo during development.

With respect to environmental variables, male and female lean mass as well as fecundity increased with increasing water temperature, oxygen content, and salinity, while male and female fat content, embryo lean mass, and RA decreased along the same gradients. Male lean mass and fat content also increased with increasing turbidity and pH, while female fat content and fecundity increased with increasing turbidity, but embryo lean mass decreased along the same gradient. Greater lean mass as a function of increasing salinity has been found in sailfin mollies and other Poeciliids before (sailfin mollies: [ 17 ]; Gambusia spp.: [ 91 ]; Phalloptychus januarius : [ 28 ] and could be a reflection of increased ionoregulatory advantages of a larger body mass [ 105 , 106 ] and other physiological effects of salinity. Similarly, the effects of temperature on fish size (SL and/or mass) have been reported for other poeciliid fishes before ( Gambusia affinis : [ 107 ]; Gambusia puncticulata : [ 108 ], and an experimental positive link between increased temperature and fish growth has also been documented [ 107 ] even though, on a global scale, responses to temperature in fish can go in either direction [ 109 ].

The effects of DO and turbidity on some of the traits are more difficult to explain. Nonetheless, given that DO co-varied with temperature and salinity, the effect of DO could be due to that covariation rather than an indication of direct responses to DO. Increasing turbidity in aquatic habitats is usually accompanied by reduced primary productivity [ 110 , 111 ], so we would therefore expect fish in more turbid waters to be smaller and have less fat reserves; yet we found the opposite pattern. Behaviorally, turbidity increases the time needed for mate choice in Sailfin mollies [ 112 ]. However, turbidity may correlate with other environmental variables we did not capture, and the responses we observed could be influenced by these other variables, rather than turbidity itself. For example, it is possible that some measured turbidity was due to high algal biomass rather than suspended inorganic particles [ 113 ]. If so, greater turbidity would correlate with habitat productivity, resulting in the observed patterns. Overall, environmental patterns may be influenced by seasonality, however, to control for this we conducted the collections during a few weeks in the summer, when conditions are relatively stable.

It appears that migration and exchange of genotypes made possible by dispersal from river mouth to river mouth (as suggested by our mismatches between genetic clusters and palaeoriver systems) and possible human-mediated dispersal provide the glue that holds this species together. This interpretation is also in agreement with the relatively large number of recent migrants between sites in different river (and paleoriver) systems.

Overall, we found that genetic differentiation in Sailfin mollies revealed distinct genetic clusters and a general isolation-by-distance population structure, with some expected admixture supported by the several mismatches between paleodrainages and geographical distribution of the genetic clusters. Neither life-history patterns nor the abiotic factors we recorded provided strong explanations for the observed genetic structuring. Instead, despite the large distribution range and apparently limited dispersal capabilities, there might be sufficient gene flow to hinder cryptic speciation in this widespread species.

Animal ethics declaration

This project was approved by University of Oklahoma IACUC #R05-001. Collecting permits were granted by various state agencies. Texas Scientific Permit Number SPR-0305-045; Louisiana Scientific Collecting Permit S-81-2008; South Carolina Scientific Collecting Permit F-08-30; Georgia Scientific Collecting Permit 29-WBH-08-148; Florida License 580-957-322; Alabama Permit 4607. Collections in Mississippi were conducted under a permit issued to Jake Schaefer (University of Southern Mississippi) and IS and the collection in North Carolina was done in collaboration with the NC DNR office in Wilmington.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. The paleodrainage analysis is avalailable here: https://github.com/waldirmbf/Paleodrainages. Raw data is available on Dryad (DOI: 10.5061/dryad.2jm63xsxb) and as supplementary data attached to this manuscript.

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We are grateful to the many individuals that helped with collections in the field, identifying potential field sites, or obtaining permits. We thank Jake Schaefer and Joel Trexler for helpful comments, and R.E. Turner for assistance with interpreting marine currents.

Open Access funding enabled and organized by Projekt DEAL. Financial support came from the University of Oklahoma and the University of Potsdam.

Open Access funding enabled and organized by Projekt DEAL.

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Unit of Evolutionary Biology/Systematic Zoology Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany

Ralph Tiedemann, Maxi Tomowski, Katja Havenstein & Ingo Schlupp

Department of Biological Sciences, Royal Holloway University of London, Egham, TW20 0EX, UK

Rüdiger Riesch

CEFE, CNRS, Univ Montpellier, EPHE, IRD, Montpellier, France

School of Biological Sciences, University of Oklahoma, 730 Van Vleet Oval, Norman, OK, 73019, USA

Rüdiger Riesch, Jan Schlupp, Waldir Miron Berbel-Filho & Ingo Schlupp

International Stock Center for Livebearing Fishes, University of Oklahoma, Norman, OK, 73019, USA

Waldir Miron Berbel-Filho & Ingo Schlupp

Amazon, amazon.com, Arlington, VA, 22202, USA

Jan Schlupp

Department of Biology, University of West Florida, Pensacola, FL, 32514, USA

Waldir Miron Berbel-Filho

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R.R. and I.S. conceived the study. I.S., R. R., W.M.B.F., M.T. designed the study. I.S., J.S. and R.R. collected the specimens and the field data. K.H. and R.T. produced the molecular data, and R.R. collected the life-history data. W.M.B.F. analyzed the paleodrainage data. All authors contributed to data analysis, interpretation, and wrote the main manuscript text. All authors reviewed the manuscript.

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Correspondence to Ralph Tiedemann or Ingo Schlupp .

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The authors declare no competing interests.

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Tiedemann, R., Riesch, R., Tomowski, M. et al. Genetic and phenotypic diversification in a widespread fish, the Sailfin Molly ( Poecilia latipinna ). BMC Ecol Evo 24 , 87 (2024). https://doi.org/10.1186/s12862-024-02270-x

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Published : 01 July 2024

DOI : https://doi.org/10.1186/s12862-024-02270-x

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  • Genetic structure
  • Palaeodrainages
  • Life history
  • Poeciliidae

BMC Ecology and Evolution

ISSN: 2730-7182

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