Characterization of polymorphic microsatellites in the castration parasite plant‐ant Allomerus octoarticulatus cf. demerarae (Formicidae: Myrmicinae)

Fifteen microsatellite loci were isolated from the Peruvian tropical plant‐ant Allomerus octoarticulatus cf. demerarae (Hymenoptera: Myrmicinae) and their polymorphism was characterized. High levels of within‐population variation were observed at most loci, with number of alleles ranging from one to 21, and heterozygosity from 0 to 1 per population sample. Cross‐species amplification of these loci was also tested in one other species of the ant genus Allomerus (Allomerus decemarticulatus), displaying similar life history.     

Observations on the Ecology of Weaver Ants (Oecophylla smaragdina Fabricius) in a Thai Mangrove Ecosystem and Their Effect on Herbivory of Rhizophora mucronata Lam.

Ants of the genus Oecophylla are predators of other insects and are able to protect a variety of terrestrial plants against pest insects; however, observations on the ecology of these ants in mangrove forests are lacking. General observations on the ecology of Oecophylla smaragdina were carried out in a Thai mangrove forest to determine if these ants can protect their host plants in less favorable mangrove habitats. Leaf herbivory and the density of O. smaragdina ants were measured on Rhizophora mucronata trees at two sites. The results showed a negative correlation between ant density and herbivory. At both sites, the mean percent damaged leaf area was more than four times higher on trees without ants compared to “ant‐trees.” A significant negative correlation was found between tree mean percent leaf damage and the density of ants on the tree. Furthermore, on trees with ants, there was less herbivory on leaves close to ant nests compared to other leaves on the tree. Most damage was caused by chrysomelid beetles (62%) and sesarmid crabs (25%) and both types of herbivory were significantly reduced on ant‐trees.     

Dinucleotide microsatellite DNA loci from the ant Myrmica scabrinodis

We describe the isolation and characterization of five dinucleotide microsatellite loci in the ant Myrmica scabrinodis, which were obtained using a magnetic bead hybridization selection protocol. The PCR primers were tested on nine to 11 individuals. The number of alleles ranged from two to 13, and the observed heterozygosity from 0.200 to 0.778.     

Antennae: the strongest magnetic part of the migratory ant

Pachycondyla marginata (P.m.), a migratory and termitophageous ant, hunting only the termite species Neocapritermes opacus, migrates significantly oriented 13 degrees with respect to the magnetic North-South axis. Results of hysteresis curves at room temperature of four Pachycondyla marginata heads, thorax, pairs of antennae and abdomens, oriented parallel to the magnetic field, indicate that the antennae give the strongest saturation magnetization, suggesting this sensory organ as being also a magnetic sensory organ. The total saturation magnetization in a whole P.m. is composed by 42 +/- 3%, 24 +/- 3%, 19 +/- 3% and 15 +/- 3% of antennae, head, thorax and abdomen contributions, respectively. The abdomen hysteresis curve presents a wasp-waisted loop with Hcr/Hc of 4.75, characteristic of mixed magnetic systems.     

Are ants botanists? Ant associative learning of plant chemicals mediates foraging for carbohydrates

1. Although associative learning is widespread across animals, its ecological importance is difficult to assess because learning is rarely studied in the field, where informative cues are juxtaposed against complex backgrounds of uninformative noise. 2. Ants rely heavily on chemical cues for foraging and engage in many ecologically important interactions with plants. Nevertheless, little is known about the role of associative learning of plant chemicals in ant foraging for carbohydrates. 3. In a field setting, the present study investigated whether the distantly related ant species Formica podzolica (Formicinae subfamily) and Tapinoma sessile (Dolichoderinae subfamily) exhibited associative learning of the chemical cues from two co-occurring plant species that are taxonomically and chemically distinct (Asteraceae: Helianthella quinquenervis and Apiaceae: Ligusticum porteri). 4. For two consecutive summers, ants were trained to forage from artificial sugar-rich baits associated with the leaf chemicals from either H. quinquenervis or L. porteri for 24 h, after which a two-choice test was deployed to assess whether ants would be more likely to select baits associated with the same (versus different) plant chemicals on which they had been trained. 5. The present study demonstrates associative learning of chemicals from both plant species, and these effects were consistent between ant species and years; training increased bait occupancy from 42% on the untrained scent to 66% on the trained scent. These results indicate that associative odour-learning may be widespread across ants and serve as an important mechanism mediating ant selection of resources.     

Characterization of microsatellite loci for the Argentine ant,Linepithema humile,and their potential for analysis of colony structure in invading Hawaiian populations

We developed primers for five polymorphic microsatellite loci to analyse the genetic structure of colonies in an invading Argentine ant population located in Haleakala National Park on the island of Maui, Hawaii. Microsatellite loci were isolated using both a polymerase chain reaction‐based and a cloning‐based method. With a range of 3–18 alleles and expected levels of heterozygosity of 0.46–0.77, these loci provide useful markers for the detection of colony and population structure in new or expanding populations of this species.     

Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder

Aim Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location California, USA. Methods We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching.