### Abstract

1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

Original language | English (US) |
---|---|

Pages (from-to) | 828-834 |

Number of pages | 7 |

Journal | Journal of Applied Ecology |

Volume | 43 |

Issue number | 4 |

DOIs | |

State | Published - Aug 2006 |

Externally published | Yes |

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### Keywords

- Body size
- Fecundity
- Life table
- Population surface area
- Reproductive value
- Stress response

### ASJC Scopus subject areas

- Ecology

### Cite this

*Journal of Applied Ecology*,

*43*(4), 828-834. https://doi.org/10.1111/j.1365-2664.2006.01180.x

**The use of image analysis to estimate population growth rate in Daphnia magna.** / Hooper, Helen L.; Connon, Richard E; Callaghan, Amanda; Maund, Steve J.; Liess, Matthias; Duquesne, Sabine; Hutchinson, Thomas H.; Moggs, Jonathan; Sibly, Richard M.

Research output: Contribution to journal › Article

*Journal of Applied Ecology*, vol. 43, no. 4, pp. 828-834. https://doi.org/10.1111/j.1365-2664.2006.01180.x

}

TY - JOUR

T1 - The use of image analysis to estimate population growth rate in Daphnia magna

AU - Hooper, Helen L.

AU - Connon, Richard E

AU - Callaghan, Amanda

AU - Maund, Steve J.

AU - Liess, Matthias

AU - Duquesne, Sabine

AU - Hutchinson, Thomas H.

AU - Moggs, Jonathan

AU - Sibly, Richard M.

PY - 2006/8

Y1 - 2006/8

N2 - 1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

AB - 1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

KW - Body size

KW - Fecundity

KW - Life table

KW - Population surface area

KW - Reproductive value

KW - Stress response

UR - http://www.scopus.com/inward/record.url?scp=33745727186&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33745727186&partnerID=8YFLogxK

U2 - 10.1111/j.1365-2664.2006.01180.x

DO - 10.1111/j.1365-2664.2006.01180.x

M3 - Article

AN - SCOPUS:33745727186

VL - 43

SP - 828

EP - 834

JO - Journal of Applied Ecology

JF - Journal of Applied Ecology

SN - 0021-8901

IS - 4

ER -