Niche overlap of congeneric invaders supports a single-species hypothesis and provides insight into future invasion risk: implications for global management of the Bactrocera dorsalis complex

Abstract

Background: The invasive fruit fly, Bactrocera invadens, has expanded its range rapidly over the past 10 years. Here we aimed to determine if the recent range expansion of Bactrocera invadens into southern Africa can be better understood through niche exploration tools, ecological niche models (ENMs), and through incorporating information about Bactrocera dorsalis s.s., a putative conspecific species from Asia. We test for niche overlap of environmental variables between Bactrocera invadens and Bactrocera dorsalis s.s. as well as two other putative conspecific species, Bactrocera philippinensis and B. papayae. We examine overlap and similarity in the geographical expression of each species' realised niche through reciprocal distribution models between Africa and Asia. We explore different geographical backgrounds, environmental variables and model complexity with multiple and single Bactrocera species hypotheses in an attempt to predict the recent range expansion of B. invadens into northern parts of South Africa.

Principal findings: Bactrocera invadens has a high degree of niche overlap with B. dorsalis s.s. (and B. philippinensis and B. papayae). Ecological niche models built for Bactrocera dorsalis s.s. have high transferability to describe the range of B. invadens, and B. invadens is able to project to the core range of B. dorsalis s.s. The ENMs of both Bactrocera dorsalis and B. dorsalis combined with B. philipenesis and B. papayae have significantly higher predictive ability to capture the distribution points in South Africa than for B. invadens alone.

Conclusions/significance: Consistent with other studies proposing these Bactrocera species as conspecific, niche similarity and overlap between these species is high. Considering these other Bactrocera dorsalis complex species simultaneously better describes the range expansion and invasion potential of B. invadens in South Africa. We suggest that these species should be considered the same-at least functionally-and global quarantine and management strategies applied equally to these Bactrocera species.

Figure 1. Asian and African distributions of Bactrocera spp. a) Bactrocera dorsalis s.s (grey circles), Bactrocera invadens (white circles), Bactrocera philippinensis (grey squares), Bactrocera papayae (white squares).

Grey area represents area not used for background selection. Colours refer to Köppen-Geiger classifications for presence records of each species investigated. Af = tropical rainforest; Am = tropical monsoon; tropical wet and dry or savannah climate; BSh = arid steppe climate; BWh = arid desert climate; Cfa = humid, subtropical; Cfb = Oceanic, highlands; Cwa = humid, subtropical; Cwb = temperate highland climate. Black outlines represent administrative boundaries selected prior to climate zone selection. b) Species occupation of different GEnS strata classifications (see [52]). All = all four species combined.

Figure 2. Principal components analysis (PCA) of four different Bactrocera spp. across different predictor variable sets.

Light grey points represent 1000 random background points across the range of B. dorsalis s.s. and dark grey, B. invadens. a) PCA for “expert” predictor set. Proportion of variance for PC1 = 88.8% and for PC2 = 6.4%. b) PCA for ENFA driven predictor set (note: eight variables were loaded, most informative across the 4 “species”) Proportion of variance for PC1 = 68.4% and for PC2 = 24.6%.

Figure 3. Reciprocal distribution models RDM for B. dorsalis s.s. + B. philippinensis + B. papayae (blue dots) and B. invadens (red dots).

Ecological Niche Models shown here were constructed on ENFA-derived predictor sets as they had higher AUC_TEST and D scores than did those built on expert-driven predictor sets (see Table 2). Shading indicates suitability and solid grey areas are those that fall outside Asia and Africa. a) RDM trained on B. dorsalis + B. papayae + B. philippinensis distribution projected to the background of B. invadens, Model H (Table 2). b) RDM trained on B. invadens distribution projected to the background of B. dorsalis s.s. + B. philippinensis + B. papayae, Model E (Table 2).

Figure 4. Niche metrics calculated for Bactrocera spp. Ecological Niche Models.

a) Niche breadth (Levin’s B) for 10 replicates of each final ENM projected to mainland southern Africa (see Fig. 5a). Note: DPP = B. dorsalis + B. philippinensis + B. papayae. b) Niche overlap (Schoener’s D) between ENMs projected to mainland southern Africa (see Fig. 5a): A = B. invadens & B. invadens De Meyer et al. (2010); B = B. invadens & B. dorsalis; C = B. invadens & B. dorsalis + B. philippinensis + B. papayae (DPP); D = B. invadens & All four species combined.

Figure 5. Final Bactrocera spp. Ecological Niche Models (ENMs) projected spatially a) Final ENMs projected to southern Africa to predict the range expansion of B. invadens.

Hatched area = area affected by recent B. invadens incursions. Red points are known localities of trapped flies. Models displayed at a binary presence/absence threshold set at maximum training sensitivity plus specificity. b) Final ENMs projected to show global invasion potential of Bactrocera invadens and when considered as a single species with B. dorsalis, B. philippinensis and B. papayae. Shading indicates variables outside training range and extrapolation (calculated with the multivariate environmental similarity surface (MESS) analysis in Maxent [26]). Models displayed at a binary presence/absence threshold set at maximum training sensitivity plus specificity.