Uncategorized

Selecting the right statistical model for analysis of insect count data by using information theoretic measures

Researchers and regulatory agencies often make statistical inferences from insect count data using modelling approaches that assume homogeneous variance. Such models do not allow for formal appraisal of variability which in its different forms is the subject of interest in ecology. Therefore, the objectives of this paper were to (i) compare models suitable for handling variance heterogeneity and (ii) select optimal models to ensure valid statistical inferences from insect count data. The log-normal, standard Poisson, Poisson corrected for overdispersion, zero inflated Poisson, the negative binomial distribution and zero-inflated negative binomial models were compared using six count datasets on foliage-dwelling insects and five families of soil-dwelling insects. Akaike’s and Schwarz Bayesian information criteria were used for comparing the various models. Over 50% of the counts were zeros even in locally abundant species such as Ootheca bennigseni Weise, Mesoplatys ochroptera Sta ̊l and Diaecoderus spp. The Poisson model after correction for overdispersion and the standard negative binomial distribution model provided better description of the probability distribution of seven out of the 11 insects than the log-normal, standard Poisson, zero-inflated Poisson or zero- inflated negative binomial models. It is concluded that excess zeros and variance heterogeneity are common data phenomena in insect counts. If not properly modelled, these properties can invalidate the normal distribution assumptions resulting in biased estimation of ecological effects and jeopardizing the integrity of the scientific inferences. Therefore, it is recommended that statistical models appropriate for handling these data properties be selected using objective criteria to ensure efficient statistical inference.

 

Authors: Gudeta Sileshi

Contact address: sileshigw@gmail.com

Institution: Addis Ababa University, Department of Plant Biology and Biodiversity Management

Twitter name of the institution: @AddisUniversity

Twitter link: https://x.com/AddisUniversity

 

Available downloads:

Selecting the right statistical model for analysis of insect count data by using information theoretic measures

Featured posts

featured

Striga weeds

Striga or 'witchweeds' are parasitic weeds that affect cereal crops in many parts of Africa, reducing production from 30 to 100%, or complete loss of the crop. If maize plants are attacked by both stemborers and striga weed, the yield... Continue Reading…

Upcoming Events

Twitter

🌾#UPSCALE Interesting paper

A recent study from Ethiopia shows #pushpulltechnology is more than just a method; it’s a science-backed solution that supports #sustainableagriculture and builds a stable future.

📈 Check out the full paper at https://upscale-hub.eu/publications/perception-of-farmers-on-push-pull-technology-using-farmers-research-network-approach-in-eastern-amhara-ethiopia/

Celebrating #WorldScienceDay2024

🌱 This day resonates deeply with the mission of the #UPSCALE project, which is advancing #pushpulltechnology and showcasing how science and innovation drive positive change to farmers and ecosystems worldwide.

🔗 https://upscale-hub.eu/

Load More