Climate change-induced degradation of expert range maps drawn for kissing bugs (Hemiptera: Reduviidae) and long-standing current and future sampling gaps across the Americas

Abstract

Background: Kissing bugs are the vectors of Trypanosoma cruzi, the etiological agent of Chagas disease (CD). Despite their epidemiological relevance, kissing bug species are under sampled in terms of their diversity and it is unclear what biases exist in available kissing bug data. Under climate change, range maps for kissing bugs may become less accurate as species shift their ranges to track climatic tolerance.

Objectives: Quantify inventory completeness in available kissing bug data. Assess how well range maps are at conveying information about current distributions and potential future distributions subject to shift under climate change. Intersect forecasted changes in kissing bug distributions with contemporary sampling gaps to identify regions for future sampling of the group. Identify whether a phylogenetic signal is present in expert range knowledge as more closely related species may be similarly well or lesser understood.

Methods: We used species distribution models (SDM), specifically constructed from Bayesian additive regression trees, with Bioclim variables, to forecast kissing bug distributions into 2100 and intersect these with current sampling gaps to identify priority regions for sampling. Expert range maps were assessed by the agreement between the expert map and SDM generated occurrence probability. We used classical hypothesis testing methods as well as tests of phylogenetic signal to meet our objectives.

Findings: Expert range maps vary in their quality of depicting current kissing bug distributions. Most expert range maps decline in their ability to convey information about kissing bug occurrence over time, especially in under sampled areas. We found limited evidence for a phylogenetic signal in expert range map performance.

Main conclusions: Expert range maps are not a perfect account of species distributions and may degrade in their ability to accurately convey distribution knowledge under future climates. We identify regions where future sampling of kissing bugs will be crucial for completing biodiversity inventories.

Fig. 1:. point occurrence data and years of observation (inset line plot) colored by each record’s ‘basisOfRecord’ field (of either museum specimens or human observations). A random sampling of 50% of the occurrences (n = 13,641) are illustrated on the map to avoid overplotting. Green = observation; Orange = collected specimens.

Fig. 2:. kissing bug inventory completeness at the 100×100 km spatial resolution (darker colors indicate greater inventory completeness). The inset map indicates expected richness based on overlapping expert range maps (darker colors indicate greater expected kissing bug species richness).

Fig. 3:. agreement between expert range maps (drawn in 1999 and shown here as red polygons) and species distribution model (SDM) output produced from only occurrence records collected before 1999 (A ,B, C) and occurrence records collected in all time periods (D, E, F). Only three species are highlighted here. Species and corresponding scores, from left to right pairs of panels, are (A, D) Triatoma delpontei (0.53, 0.60); (B, E) Rhodnius pallescens (0.54, 0.58); and (C, F) Rhodnius prolixus (0.51, 0.52).

Fig. 4:. degradation of expert ranges maps over time under climate change scenario RCP 8.5 into 2041-2060, 2061-2080, and 2081-2100 (Global Circulation Model: ACCESS-ESM1-5, 2.5-minute resolution) based on species distribution projections from (A) the only pre-1999 occurrence record model and (B) the full occurrence record model. Species are summarized into two groups, declining expert scores over time (red) and increasing export scores over time (blue). The shaded area represents on standard deviation of variation around the mean trend line.

Fig. 5:. potential regions in which to better sample kissing bug occurrence across the Americas. Targeted regions of sampling (green axis) between the (A) pre-1999 occurrence and (B) all occurrence models mostly overlap. Please note that this figure does not include measures of disease risk, simply projected distributions, and existing sampling gaps. Grey-green scale indicates higher probability of future kissing bug occurrence in 2080-2100 (green indicates higher probability) while the purple-grey scale indicates inventory completeness (purple indicates higher inventory completeness).