Abstract

Methods derived from ecological niche modeling allow to define species distribution based on presence-only data. This is particularly useful to develop models from literature records such as available for the Anopheles dirus complex, a major group of malaria mosquito vectors in Asia. This research defines an innovative modeling design based on presence-only model and hierarchical framework to define the distribution of the complex and attempt to delineate sibling species distribution and environmental preferences. At coarse resolution, the potential distribution was defined using slow changing abiotic factors such as topography and climate representative for the timescale covered by literature records of the species. The distribution area was then refined in a second step using a mask of current suitable land cover. Distribution area and ecological niche were compared between species and environmental factors tested for relevance. Alternatively, extreme values at occurrence points were used to delimit environmental envelopes. The spatial distribution for the complex was broadly consistent with its known distribution and influencing factors included temperature and rainfall. If maps developed from environmental envelopes gave similar results to modeling when the number of sites was high, the results were less similar for species with low number of recorded presences. Using presence-only models and hierarchical framework this study not only predicts the distribution of a major malaria vector, but also improved ecological modeling analysis design and proposed final products better adapted to malaria control decision makers. The resulting maps can help prioritizing areas which need further investigation and help simulate distribution under changing conditions such as climate change or reforestation. The hierarchical framework results in two products one abiotic based model describes the potential maximal distribution and remains valid for decades and the other including a biotic mask easy to update with frequently available information gives current species distribution.

Highlights

  • The Anopheles dirus complex (Peyton & Ramalingam, 1988) [1] includes the most efficient malaria vectors of Asia and species transmitting Artemisin-resistant malaria parasites which could compromise control efforts globally [2]

  • Step 1: Potential Distribution Area: the ‘‘Potential Niche’’ The suitability maps based on the mean of the 100 replicates of model ECOOPT at a resolution of 1 km (ECOOPT1) depict the potential distribution areas for the complex and the species with reasonable sample size (Figure 1)

  • Using presence-only models and hierarchical framework this study managed to predict the distribution of a major malaria vector, and improve ecological modeling analysis design and proposed final products better adapted to malaria control decision makers

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Summary

Introduction

The Anopheles dirus complex (Peyton & Ramalingam, 1988) [1] includes the most efficient malaria vectors of Asia and species transmitting Artemisin-resistant malaria parasites which could compromise control efforts globally [2]. Remote sensing and Geographical Information Systems (GIS) technologies increase the availability of environmental digital datasets and geo-referenced species occurrence data which can be combined to estimate species distribution over a large region at coarse scale [15]. Amongst those new modeling techniques, the Maxent method selected for this study [13,16] performs well [10], does not require absence data and can be transferred to large areas with sparse or no species sampling records

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