Applying the N‐mixture model approach to estimate mosquito population absolute abundance from monitoring data

Population abundance estimates in conservation and biodiversity research

Measuring and tracking biodiversity from local to global scales is challenging due to its multifaceted nature and the range of metrics used to describe spatial and temporal patterns. Abundance can be used to describe how a population changes across space and time, but it can be measured in different ways, with consequences for the interpretation and communication of spatiotemporal patterns. We differentiate between relative and absolute abundance, and discuss the advantages and disadvantages of each for biodiversity monitoring, conservation, and ecological research. We highlight when absolute abundance can be advantageous and should be prioritized in biodiversity monitoring and research, and conclude by providing avenues for future research directions to better assess the necessity of absolute abundance in biodiversity monitoring.

Independent evaluation of Wolbachia infected male mosquito releases for control of Aedes aegypti in Harris County, Texas, using a Bayesian abundance estimator

Among disease vectors, Aedes aegypti (L.) (Diptera: Culicidae) is one of the most insidious species in the world. The disease burden created by this species has dramatically increased in the past 50 years, and during this time countries have relied on pesticides for control and prevention of viruses borne by Ae. aegypti. The small number of available insecticides with different modes of action had led to increases in insecticide resistance, thus, strategies, like the "Incompatible Insect Technique" using Wolbachia's cytoplasmic incompatibility are desirable. We evaluated the effect of releases of Wolbachia infected Ae. aegypti males on populations of wild Ae. aegypti in the metropolitan area of Houston, TX. Releases were conducted by the company MosquitoMate, Inc. To estimate mosquito population reduction, we used a mosquito abundance Bayesian hierarchical estimator that accounted for inefficient trapping. MosquitoMate previously reported a reduction of 78% for an intervention conducted in Miami, FL. In this experiment we found a reduction of 93% with 95% credibility intervals of 86% and 96% after six weeks of continual releases. A similar result was reported by Verily Life Sciences, 96% [94%, 97%], in releases made in Fresno, CA.

Distribution Drivers of the Alien Butterfly Geranium Bronze (Cacyreus marshalli) in an Alpine Protected Area and Indications for an Effective Management

Simple Summary

Cacyreus marshalli is strictly dependent on its host plant (Pelargonium spp.), which is widely cultivated as an ornamental plant in mountain areas. An experiment demonstrated that the butterfly is able to develop on some wild geraniums, too, making mountain areas highly at risk for a potential expansion to natural habitats. We therefore decided to carry out research in a protected mountain area (Gran Paradiso National Park), focusing on the drivers which determine the distribution of C. marshalli using data provided by either an opportunistic approach or a rigorous survey protocol. The data collected via the planned survey were more informative than the opportunistic observations, which were few and narrow. We suggest investing more in citizen science projects and combining them with a designed protocol according to an integrated approach. We observed that C. marshalli distribution is strictly linked to host plant availability but is constrained by cold temperatures, although Pelargonium spp. are abundant. The temperature increase scenario showed an increase of butterfly abundance, but halving of the host plant population could drive the rate of infestation to return to what it was previously, excluding a countertrend in some high-altitude sites. It is therefore important to test management actions designed to control alien species before implementing them.

Abstract

Cacyreus marshalli is the only alien butterfly in Europe. It has recently spread in the Gran Paradiso National Park (GPNP), where it could potentially compete with native geranium-consuming butterflies. Our study aimed to (1) assess the main drivers of its distribution, (2) evaluate the potential species distribution in GPNP and (3) predict different scenarios to understand the impact of climate warming and the effect of possible mitigations. Considering different sampling designs (opportunistic and standardised) and different statistical approaches (MaxEnt and N-mixture models), we built up models predicting habitat suitability and egg abundance for the alien species, testing covariates as bioclimatic variables, food plant (Pelargonium spp.) distribution and land cover. A standardised approach resulted in more informative data collection due to the survey design adopted. Opportunistic data could be potentially informative but a major investment in citizen science projects would be needed. Both approaches showed that C. marshalli is associated with its host plant distribution and therefore confined in urban areas. Its expansion is controlled by cold temperatures which, even if the host plant is abundant, constrain the number of eggs. Rising temperatures could lead to an increase in the number of eggs laid, but the halving of Pelargonium spp. populations would mostly mitigate the trend, with a slight countertrend at high elevations.

N-mixture models provide informative crocodile (Crocodylus moreletii) abundance estimates in dynamic environments

Estimates of animal abundance provide essential information for population ecological studies. However, the recording of individuals in the field can be challenging, and accurate estimates require analytical techniques which account for imperfect detection. Here, we quantify local abundances and overall population size of Morelet's crocodiles (Crocodylus moreletii) in the region of Calakmul (Campeche, Mexico), comparing traditional approaches for crocodylians (Minimum Population Size-MPS; King's Visible Fraction Method-VFM) with binomial N-mixture models based on Poisson, zero-inflated Poisson (ZIP) and negative binomial (NB) distributions. A total of 191 nocturnal spotlight surveys were conducted across 40 representative locations (hydrologically highly dynamic aquatic sites locally known as aguadas) over a period of 3 years (2017-2019). Local abundance estimates revealed a median of 1 both through MPS (min-max: 0-89; first and third quartiles, Q₁-Q₃: 0-7) and VFM (0-112; Q₁-Q₃: 0-9) non-hatchling C. moreletii for each aguada, respectively. The ZIP based N-mixture approach shown overall superior confidence over Poisson and NB, and revealed a median of 6 ± 3 individuals (min = 0; max = 120 ± 18; Q₁ = 0; Q₃ = 18 ± 4) jointly with higher detectabilities in drying aguadas with low and intermediate vegetation cover. Extrapolating these inferences across all waterbodies in the study area yielded an estimated ~10,000 (7,000-11,000) C. moreletii present, highlighting Calakmul as an important region for this species. Because covariates enable insights into population responses to local environmental conditions, N-mixture models applied to spotlight count data result in particularly insightful estimates of crocodylian detection and abundance.

Understanding Mosquito Surveillance Data for Analytic Efforts: A Case Study

Mosquito surveillance data can be used for predicting mosquito distribution and dynamics as they relate to human disease. Often these data are collected by independent agencies and aggregated to state and national level portals to characterize broad spatial and temporal dynamics. These larger repositories may also share the data for use in mosquito and/or disease prediction and forecasting models. Assumed, but not always confirmed, is consistency of data across agencies. Subtle differences in reporting may be important for development and the eventual interpretation of predictive models. Using mosquito vector surveillance data from Arizona as a case study, we found differences among agencies in how trapping practices were reported. Inconsistencies in reporting may interfere with quantitative comparisons if the user has only cursory familiarity with mosquito surveillance data. Some inconsistencies can be overcome if they are explicit in the metadata while others may yield biased estimates if they are not changed in how data are recorded. Sharing of metadata and collaboration between modelers and vector control agencies is necessary for improving the quality of the estimations. Efforts to improve sharing, displaying, and comparing vector data from multiple agencies are underway, but existing data must be used with caution.

ZanzaMapp: A Scalable Citizen Science Tool to Monitor Perception of Mosquito Abundance and Nuisance in Italy and Beyond

Mosquitoes represent a considerable nuisance and are actual/potential vectors of human diseases in Europe. Costly and labour-intensive entomological monitoring is needed to correct planning of interventions aimed at reducing nuisance and the risk of pathogen transmission. The widespread availability of mobile phones and of massive Internet connections opens the way to the contribution of citizen in complementing entomological monitoring. ZanzaMapp is the first mobile “mosquito” application for smartphones specifically designed to assess citizens’ perception of mosquito abundance and nuisance in Italy. Differently from other applications targeting mosquitoes, ZanzaMapp prioritizes the number of records over their scientific authentication by requesting users to answer four simple questions on perceived mosquito presence/abundance/nuisance and geo-localizing the records. The paper analyses 36,867 ZanzaMapp records sent by 13,669 devices from 2016 to 2018 and discusses the results with reference to either citizens’ exploitation and appreciation of the app and to the consistency of the results obtained with the known biology of main mosquito species in Italy. In addition, we provide a first small-scale validation of ZanzaMapp data as predictors of Aedes albopictus biting females and examples of spatial analyses and maps which could be exploited by public institutions and administrations involved in mosquito and mosquito-borne pathogen monitoring and control.

Mosquito surveillance and disease outbreak risk models to inform mosquito-control operations in Europe

Surveillance programs are needed to guide mosquito-control operations to reduce both nuisance and the spread of mosquito-borne diseases. Understanding the thresholds for action to reduce both nuisance and the risk of arbovirus transmission is becoming critical. To date, mosquito surveillance is mainly implemented to inform about pathogen transmission risks rather than to reduce mosquito nuisance even though lots of control efforts are aimed at the latter. Passive surveillance, such as digital monitoring (validated by entomological trapping), is a powerful tool to record biting rates in real time. High-quality data are essential to model the risk of arbovirus diseases. For invasive pathogens, efforts are needed to predict the arrival of infected hosts linked to the small-scale vector to host contact ratio, while for endemic pathogens efforts are needed to set up region-wide highly structured surveillance measures to understand seasonal re-activation and pathogen transmission in order to carry out effective control operations.