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USING GEOMETRIC MORPHOMETRICS TO TEST FOR FISHING-INDUCED SELECTION IN PHILIPPINE RABBIT FISH Department of Life Sciences, Texas A&M University Corpus Christi Micah Bachner, Abner Bucol, Jason Selwyn, Christopher E. Bird Introduction Populations experience a variable landscape of selective pressures which act on phenotypic variation, resulting in geographic variation in phenotypes. Selective pressures applied by fishing activities accelerate the pace of evolution and can affect geographic variation in morphology. In the Philippines, 91% of locally-caught fishes are consumed locally, and an estimated 56% of protein consumption comes from fishes. In this region, Siganus fuscescens is a staple food item that is eaten fresh, dried, or in the case of juveniles, turned into a delicacy fish paste and whose fishery is showing signs of collapse. To better understand the effects of overfishing on the evolution S. fuscenscens, here we test for differences in body shape among four locations in Negros Oriental, Philippines, each experiencing different fishing regimes. Results Shape differed significantly among locations -PC2 separates sites by size of operculum, position of anal fin (DU-AY vs BA-AM) -PC1 separates BA-AM by body depth 73% of variation in fishing pressure indices explained by PC1 Shape related to PC1 of fishing pressure indices -Most fishermen in BA: deeper body, smaller operculum -Most people in DU: shallower, elongate body Source df SS MS Rsq F Z P Location 3 0.015 5.1E-3 0.14 9.0 9.1 1.0E-04 Resids 165 0.094 5.7E-4 0.86 Total 168 0.11 Table 1. Values from MANOVA test for differences in shape among locations. Figure 2. Example photograph of S. fuscescens used for geometric morphometric analysis with landmarks (red points). Acknowledgements Marhuma Zaman, John Whalen, Dr. Rene Abesames, Dr. Alcala, Dr. Kent Carpenter, SUAKREM Discussion Significant differences in fish shape strongly indicate spatial variation selective pressures. Population size and fisherman inversely related perhaps due to more people = more subsistence; fewer people = more commercial Phenotypes in area of highest commercial fishing pressure may reduce chances of capture via net -deeper body, smaller operculum Figure 1. Map of sampling sites with accentuated municipality boundaries. Inset table contains data on the number of people and fishers per hectare of habitat. Mean fish shape Fish shape for max PC1 AM AY BA DU Methods i. Specimens collected (n=166) from 4 fish markets along the eastern coast of Negros Oriental (Fig. 1) ii. All individuals photographed on left side iii. 24 landmarks identified for each fish and stored in TPS format iv. A PCA of several indices of fishing pressure (pop size, # fishers, available habitat, and distance from pop center was used to isolate PC1 for comparison with shape data v. Geometric morphometrics using geomorph (Adams and Otárola-Castillo 2013) R package: a) Procrustes superimposition, b) MANOVA correction for allometry and sex, c) MANOVA test for effect of location and PCA to visualize, d) multivariate regression test for effect of fishing pressure Figure 4. A 1-D representation of fish shape regressed against fishing pressure index. Regression scores were calculated from the multivariate regression of landmarks against fishing pressure (Table 2, below). Bars represent std. error and the shaded region is the 95% CI of the model. Wireframes show the predicted shapes at the observed extremes of fishing pressure. Here, sites are treated as independent observations, but fish are not. Consequently, this test is conservative relative to that reported in Table 2. Negros Island Ayungon (AY); n=24 Bais (BA); n=87 Amlan (AM); n=31 Dumaguete (DU); n=24 30 km 123°E Source df SS MS F P Fishing Pressure 1 0.011 0.011 18.1 <0.0001 Residuals 167 0.099 5.9E-4 Total 168 0.11 Table 2. Results from the multivariate regression of landmarks against fishing pressure (PC1). Note that fish are treated as independent observations here, in contrast to Figure 4, above. R 2 = 9.7% Figure 3. PC1 and PC2 from principal components analysis of geometric morphometrics after accounting for shape differences due to allometry (centroid size) and sex (M, F, Unk). Colored points depict sites and ellipses delineate 50% confidence intervals. Black wire frames show how shape changes along each PC and grey wire frames show the mean shape (PC1=0, PC2=0). Inset shows the relationship between shape (common regression component from multivariate regression of landmarks), size and sex. Location People/ Habitat Area (#/ha) # Fishers / Habitat Area (#/ha) AY 2164 6.21 BA 1505 15.1 AM 1440 8.96 DU 14172 4.31 10°N 11°N 09°N df = 2 t = 3.8 P=0.06 BA Predicted DU Predicted PC1: 23% of variance PC2: 13% of variance Slopes not significantly different LN Centroid Size Shape (common regression component) P SIZE < 0.0001 P SEX < 0.0001 Confounding Factors Subtracted From Fish Shapes

USING GEOMETRIC MORPHOMETRICS TO TEST FOR FISHING …mcnair.tamucc.edu/m.-bachner.pdf · 2021. 1. 30. · FOR FISHING-INDUCED SELECTION IN PHILIPPINE RABBIT FISH Department of Life

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  • USING GEOMETRIC MORPHOMETRICS TO TEST

    FOR FISHING-INDUCED SELECTION IN PHILIPPINE

    RABBIT FISHDepartment of Life Sciences, Texas A&M University – Corpus Christi

    Micah Bachner, Abner Bucol, Jason Selwyn, Christopher E. Bird

    IntroductionPopulations experience a variable landscape of

    selective pressures which act on phenotypic variation,

    resulting in geographic variation in phenotypes.

    Selective pressures applied by fishing activities

    accelerate the pace of evolution and can affect

    geographic variation in morphology. In the Philippines,

    91% of locally-caught fishes are consumed locally, and

    an estimated 56% of protein consumption comes from

    fishes. In this region, Siganus fuscescens is a staple

    food item that is eaten fresh, dried, or in the case of

    juveniles, turned into a delicacy fish paste and whose

    fishery is showing signs of collapse. To better

    understand the effects of overfishing on the evolution

    S. fuscenscens, here we test for differences in body

    shape among four locations in Negros Oriental,

    Philippines, each experiencing different fishing

    regimes.

    Results• Shape differed significantly among locations

    -PC2 separates sites by size of operculum,

    position of anal fin (DU-AY vs BA-AM)

    -PC1 separates BA-AM by body depth

    • 73% of variation in fishing pressure indices

    explained by PC1

    • Shape related to PC1 of fishing pressure indices

    -Most fishermen in BA: deeper body, smaller

    operculum

    -Most people in DU: shallower, elongate body

    Source df SS MS Rsq F Z P

    Location 3 0.015 5.1E-3 0.14 9.0 9.1 1.0E-04

    Resids 165 0.094 5.7E-4 0.86

    Total 168 0.11

    Table 1. Values from MANOVA test for differences in shape among locations.

    Figure 2. Example photograph of S. fuscescens used for geometric morphometric analysis with landmarks (red points).

    AcknowledgementsMarhuma Zaman, John Whalen, Dr. Rene

    Abesames, Dr. Alcala, Dr. Kent Carpenter,

    SUAKREM

    Discussion• Significant differences in fish shape strongly

    indicate spatial variation selective pressures.

    • Population size and fisherman inversely related

    perhaps due to more people = more subsistence;

    fewer people = more commercial

    • Phenotypes in area of highest commercial fishing

    pressure may reduce chances of capture via net

    -deeper body, smaller operculum

    Figure 1. Map of sampling sites with accentuated municipality boundaries.

    Inset table contains data on the number of people and fishers per hectare of

    habitat.

    Mean fish shape

    Fish shape for max PC1

    AMAYBADU

    Methodsi. Specimens collected (n=166) from 4 fish markets

    along the eastern coast of Negros Oriental (Fig. 1)

    ii. All individuals photographed on left side

    iii. 24 landmarks identified for each fish and stored in

    TPS format

    iv. A PCA of several indices of fishing pressure (pop

    size, # fishers, available habitat, and distance from

    pop center was used to isolate PC1 for comparison

    with shape data

    v. Geometric morphometrics using geomorph (Adams

    and Otárola-Castillo 2013) R package: a) Procrustes

    superimposition, b) MANOVA correction for allometry

    and sex, c) MANOVA test for effect of location and

    PCA to visualize, d) multivariate regression test for

    effect of fishing pressure

    Figure 4. A 1-D representation of fish shape regressed against fishing

    pressure index. Regression scores were calculated from the multivariate

    regression of landmarks against fishing pressure (Table 2, below). Bars

    represent std. error and the shaded region is the 95% CI of the model.

    Wireframes show the predicted shapes at the observed extremes of fishing

    pressure. Here, sites are treated as independent observations, but fish are not.

    Consequently, this test is conservative relative to that reported in Table 2.

    Negros Island

    Ayungon (AY); n=24

    Bais (BA); n=87

    Amlan (AM); n=31

    Dumaguete (DU); n=24 30 km

    12

    3°E

    Source df SS MS F P

    Fishing

    Pressure1 0.011 0.011 18.1