Long-term multiparameter assessment of the impact of Hurricane Mara - - PowerPoint PPT Presentation

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Long-term multiparameter assessment of the impact of Hurricane Mara - - PowerPoint PPT Presentation

Long-term multiparameter assessment of the impact of Hurricane Mara on colony measures: A case study in gentle Africanized honey bees (gAHB) from Puerto Rico Jos L. Agosto-Rivera Department of Biology University of Puerto Rico, Ro


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Long-term multiparameter assessment of the impact of Hurricane María on colony measures: A case study in gentle Africanized honey bees (gAHB) from Puerto Rico

José L. Agosto-Rivera Department of Biology University of Puerto Rico, Río Piedras Campus

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Hurricane Maria’s Trajectory

https://www.vox.com/science-and-health/2017/9/21/16345176/hurricane-maria-2017-puerto-rico-san-juan-meteorology-wind-rain-power

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SLIDE 3

Maria’s impact on vegetation

  • severe damage to

23-31 million trees. 1 day before hurricane 1 day after hurricane

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SLIDE 4

Vegetation Recovery After Hurricane María in Puerto Rico

(Hu & Smith, 2018) (Feng et.al., 2018)

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SLIDE 5

How were honey bees affected by the loss of vegetation due to the hurricane?

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SLIDE 6

Impact of Maria on honey bees

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SLIDE 7

How did the colonies that survived perform with the dramatic loss in vegetation? Did our management strategies worked?

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SLIDE 8

Experimental Set Up and Timeline

Aug. 2017 Sept. 2017 Nov. 2017 Jan. 2018 Oct. 2017 Dec. 2017 Feb. 2018 Sugar Feeding Started: Sept. 19 Hurricane Maria

  • Sept. 20

Protein feeding Started: Nov. 3 Monthly or biweekly photos Hive with camera and sensors

Data Collection Timeline

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SLIDE 9

Dependent variables and types of data recorded

Video Camera

  • Foraging trips

(entries and exits)

  • Pollen carrying bees

(Pollen foragers)

  • Fanning bees

(not analyzed yet) Photos

  • Brood
  • Honey stores
  • Pollen Stores

Sensors

  • Thermoregulation
  • Humidity control
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SLIDE 10

Automated foraging trips detection using machine learning and pose detection

Rodriguez et al., 2018

  • Exits
  • Entries
  • Body length

(drones and queen)

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SLIDE 11

Automatic detection of pollen foragers using machine learning

Rodriguez et al., 2018 Pollen foragers Non-Pollen foragers

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SLIDE 12

Quantifying brood, pollen and honey stores from photos

Pollen Larvae Pupae Sealed brood Frame with brood and pollen Zoom in of quadrant with brood and pollen Honey

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SLIDE 13

Results

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SLIDE 14

Brood pattern after María parallels the impact of vegetation: a decrease in October and recovery by November

A u g S e p t O c t N

  • v

D e c J a n F e b 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000

Time (months) Number of cells Brood Levels

Larva Pupae Sealed Brood

Sugar Feeding Protein Feeding

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SLIDE 15

October’s decrease in brood is not related to depletion of honey stores

A u g S e p t O c t N

  • v

D e c J a n F e b 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000

Time (months) Number of cells Brood Levels

Larva Pupae Sealed Brood

A u g S e p t O c t N

  • v

D e c J a n F e b 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000

Time (months) Number of cells Honey Levels

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SLIDE 16

A u g S e p t O c t N

  • v

D e c J a n F e b 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000

Time (months) Number of cells Brood Levels

Larva Pupae Sealed Brood

A u g S e p t O c t N

  • v

D e c J a n F e b 100 200 300 400 500 600 700 800

Time (months) Number of cells Pollen Stores

October’s decrease in brood is not related to depletion of Pollen stores

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SLIDE 17

Pollen entry was normalized by November and January’s increase in brood coincides with increased pollen entry

A u g S e p t O c t N

  • v

D e c J a n F e b 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000

Time (months) Number of cells Brood Levels

Larva Pupae Sealed Brood

Aug Sept Oct Nov Dec Jan Feb 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Time (months) Number of bees (bees /day) Pollen Foragers

?

1 day before hurricane 1 day after hurricane

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SLIDE 18

Minor or no changes in non-pollen foragers before and after hurricane Maria

A u g S e p t O c t N

  • v

D e c J a n F e b 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000

Time (months) Number of cells Brood Levels

Larva Pupae Sealed Brood

A u g S e p t O c t N

  • v

D e c J a n F e b 5000 10000 15000 20000 25000 30000

Time (months) Number of bees (bees /day) Non-Pollen Foragers

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Summary and Conclusions

  • Brood pattern after María parallels the impact of vegetation: a decrease in

October and recovery by November.

  • Whether the January increased in brood and pollen entry correspond to

increased flora is unknown.

  • Sugar feeding may support survival of adults but is not sufficient to support

brood rearing (decrease in October despite high honey levels).

  • Brood levels were already increased by the time we started the protein

administration and no further increase was observed afterwards. Administration was probably too late to see effects.

  • The decrease in pollen entry may have serve as a signal to reduced brood

levels by one of the following mechanisms:

○ Reducing egg laying of the queen ○ Triggering a behavioral switch from feeding to cannibalism in nurses

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SLIDE 20

Hypothetical model of the impact of Hurricane Maria

https://www.knowablemagazine.org/article/sustainability/2017/whole-food-diet-bees

Flora Pollen Forager Pollen Stored Nurse bees Cannibalism

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SLIDE 21

Undergraduate Students

  • Iván Collado
  • José Mayoral
  • Luis González
  • Vivian Reyes
  • Johann Santos
  • Luis Santos
  • Nashalis Martínez
  • Paola Santiago
  • Patricia Arsuaga
  • Rochelly Rivera
  • Isabel Rivera
  • Ashley Lozada
  • Esteban Morales
  • Isabel Rivera
  • Ashley Lozada
  • Esteban Morales
  • Nicole Gerena
  • Jhoniel Perez
  • Vilnery Rivera
  • Stephanie González
  • Cheryl Gonzalez
  • Giancarlo Piovanetti

Mentors

  • Dr. José L. Agosto Rivera
  • Dr. Tugrul Giray
  • Dr. Rémi Mégret
  • Dr. Edgar Acuña
  • Dr. Patricia Ordoñez
  • Dr. Manuel Giannoni-

Guzmán

Graduate Students

  • Isada Claudio Ford
  • Iván Rodriguez
  • Stephanie Feliciano
  • Jonathan Alemán-Ríos

Technician

  • Tilden Aponte

Undergraduate Students

  • Janpierre Alemán
  • Claudia Cordero
  • Airined Montes
  • Carlos Morfi
  • Courtney George
  • Edwin Caraballo
  • Edwin Rivera

Acknowledgements

This work was supported by the following NSF Grants: 1707355, 1633184, 1560389, 1545803, 1736019, 1826729