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Abstract Ecologists, foresters and conservation practitioners need ‘biodiversity scanners’ to effectively inventory biodiversity, audit conservation progress and track changes in ecosystem function. Quantifying biological diversity using remote sensing methods remains challenging, especially for small invertebrates. However, insect aggregations can drastically alter landscapes and vegetation, and these ‘extended phenotypes’ could serve as environmental landmarks of insect presence in remotely sensed data. To test the feasibility of this approach, we studied symbiotic ants that alter the canopy shape of whistling thorn acacias (Acacia [syn. Vachellia] drepanolobium), a keystone tree species of the black cotton soils of east African savannas. We demonstrate a protocol for using light detection and ranging (LiDAR) data to collect, prepare (including a customizable tree‐segmentation algorithm) and apply a convolutional neural network‐based classification for the detection of ant‐inhabited acacia tree phenotypic variations. Applying this protocol enabled us to effectively detect intra‐specific tree phenotypic variation induced by insects. Surveying ant occupancy across 16 ha and 9680 acacia trees took 1000 work hours, whereas surveyed patterns of ant distribution were replicated by our trained classifier using only an hour‐long airborne LiDAR collection time. We suggest that large‐scale surveys of insect occupancy (including insect‐vectored disease) can be automated through a combination of airborne LiDAR and machine learning.

Abstract Background For multicellular organisms, much remains unknown about the dynamics of synonymous codon and amino acid use in highly expressed genes, including whether their use varies with expression in different tissue types and sexes. Moreover, specific codons and amino acids may have translational functions in highly transcribed genes, that largely depend on their relationships to tRNA gene copies in the genome. However, these relationships and putative functions are poorly understood, particularly in multicellular systems. Results Here, we studied codon and amino acid use in highly expressed genes from reproductive and nervous system tissues (male and female gonad, somatic reproductive system, brain and ventral nerve cord, and male accessory glands) in the cricket Gryllus bimaculatus. We report an optimal codon, defined as the codon preferentially used in highly expressed genes, for each of the 18 amino acids with synonymous codons in this organism. The optimal codons were mostly shared among tissue types and both sexes. However, the frequency of optimal codons was highest in gonadal genes. Concordant with translational selection, a majority of the optimal codons had abundant matching tRNA gene copies in the genome, but sometimes obligately required wobble tRNAs. We suggest the latter may comprise a mechanism for slowing translation of abundant transcripts, particularly for cell-cycle genes. Non-optimal codons, defined as those least commonly used in highly transcribed genes, intriguingly often had abundant tRNAs, and had elevated use in a subset of genes with specialized functions (gametic and apoptosis genes), suggesting their use promotes the translational upregulation of particular mRNAs. In terms of amino acids, we found evidence suggesting that amino acid frequency, tRNA gene copy number, and amino acid biosynthetic costs (size/complexity) had all interdependently evolved in this insect model, potentially for translational optimization. Conclusions Collectively, the results suggest a model whereby codon use in highly expressed genes, including optimal, wobble, and non-optimal codons, and their tRNA abundances, as well as amino acid use, have been influenced by adaptation for various functional roles in translation within this cricket. The effects of expression in different tissue types and the two sexes are discussed.