Mark-recapture without estimating population sizes: a tool to evaluate termite baits

Termite population size estimation based on termite tunnel patterns using a convolutional neural network

Subterranean termites live in large colonies under the ground where they build an elaborate network of tunnels for foraging. In this study, we explored how the termite population size can be estimated using partial information on tunnel patterns. To achieve this, we used an agent-based model to create tunnel patterns that were characterized by three variables: the number of simulated termites (N), passing probability of two termites encountering one another (P), and distance that termites move soil particles (D). To explore whether the N value could be estimated using a partial termite tunnel pattern, we generated four tunnel pattern groups by partially obscuring different areas in an image of a complete tunnel pattern, where: (1) the outer area of the tunnel pattern was obscured (I-pattern); (2) half of the tunnel pattern was obscured (H-pattern); (3) the inner region of the tunnel pattern was obscured (O-pattern); and (4) I- and O-patterns (IO-pattern) were combined. For each group, 80% of the tunnel patterns were used to train a convolutional neural network while the remaining 20% were used for estimating the N value. Estimation results showed that the N estimates for IO-patterns were the most accurate, followed by I-, H-, and O-patterns. This indicates that termite population size can be estimated based on tunnel information near the center of a colony. We briefly discuss the advantages and disadvantages of this method for estimating termite population size.

Termite (order Blattodea, infraorder Isoptera) baiting 20 years after commercial release

Termite baiting is now one of the two main management tools in developed countries after 20 years of commercial release. It has two main goals: to use small amounts of active ingredient and 'colony elimination', i.e. death of all individuals in the colony. We consider how well baiting has been evaluated from 100 studies in the scientific literature. Studies have included 15 active ingredients, 23 termite species and 16 countries, yet most studies have focused on the chitin synthesis inhibitor hexaflumuron, Reticulitermes and the United States. Baiting has mostly met its goals: typically about 0.5 g of active ingredient was used, and colony elimination achieved, albeit with rates varying from 0 to 100%, and sometimes supplemented with liquid insecticide. Baiting was most successful using chitin synthesis inhibitors against Reticulitermes and Coptotermes (Rhinotermitidae), in temperate locations, although colony elimination was usually inferred indirectly - mostly by termite absence from baits - and was often slow, from 25 to 450 days. Baiting has been less tested and less successful against higher termites in tropical locations, where they are most diverse and abundant. Future research may have to consider greater termite species diversity and other active ingredients to reduce control times in order to fulfil the potential of baiting.

Foraging population and territory estimates for Microcerotermes diversus (Isoptera: Termitidae) through mark-release-recapture in Ahwaz (Khouzestan, Iran)

Microcerotermes diversus Silvestri (Isoptera: Termitidae), an important pest in Ahwaz (Khouzestan, Iran), causes serious economic damage to wooden products in buildings. In this study, we determined the foraging populations and territories of this species using mark-release-recapture techniques. Based on both the weighted mean model and Lincoln index methods, mean termite foraging population estimates for two colonies, A and B, were 2,984,489 +/- 258,802 and 326,134 +/- 8,713, respectively. Estimates with the Lincoln index were 2,731,229 +/- 813,081 for colony A and 321,493 +/- 138,499 for colony B. Estimated horizontal foraging territories for colonies A and B were 25.59 and 44.16 m2, respectively. The maximum and minimum linear foraging distances were 5.40 and 2.14 m for colony A and 9.14 and 1.86 m for colony B, respectively. Our data expand the knowledge about the biology, ecology and behavior of M. diversus.