Tutorial : applying machine learning in behavioral research

Machine-learning algorithms hold promise for revolutionizing how educators and clinicians make decisions. However, researchers in behavior analysis have been slow to adopt this methodology to further develop their understanding of human behavior and improve the application of the science to problems of applied significance. One potential explanation for the scarcity of research is that machine learning is not typically taught as part of training programs in behavior analysis. This tutorial aims to address this barrier by promoting increased research using machine learning in behavior analysis. We present how to apply the random forest, support vector machine, stochastic gradient descent, and k-nearest neighbors algorithms on a small dataset to better identify parents of children with autism who would benefit from a behavior analytic interactive web training. These step-by-step applications should allow researchers to implement machine-learning algorithms with novel research questions and datasets

Molecular Identification of Atlantic Bluefin Tuna (Thunnus thynnus, Scombridae) Larvae and Development of a DNA Character-Based Identification Key for Mediterranean Scombrids

The Atlantic bluefin tuna, Thunnus thynnus, is a commercially important species that has been severely over-exploited in the recent past. Although the eastern Atlantic and Mediterranean stock is now showing signs of recovery, its current status remains very uncertain and as a consequence their recovery is dependent upon severe management informed by rigorous scientific research. Monitoring of early life history stages can inform decision makers about the health of the species based upon recruitment and survival rates. Misidentification of fish larvae and eggs can lead to inaccurate estimates of stock biomass and productivity which can trigger demands for increased quotas and unsound management conclusions. Herein we used a molecular approach employing mitochondrial and nuclear genes (CO1 and ITS1, respectively) to identify larvae (n = 188) collected from three spawning areas in the Mediterranean Sea by different institutions working with a regional fisheries management organization. Several techniques were used to analyze the genetic sequences (sequence alignments using search algorithms, neighbour joining trees, and a genetic character-based identification key) and an extensive comparison of the results is presented. During this process various inaccuracies in related publications and online databases were uncovered. Our results reveal important differences in the accuracy of the taxonomic identifications carried out by different ichthyoplanktologists following morphology- based methods. While less than half of larvae provided were bluefin tuna, other dominant taxa were bullet tuna (Auxis rochei), albacore (Thunnus alalunga) and little tunny (Euthynnus alletteratus). We advocate an expansion of expertise for a new generation of morphology-based taxonomists, increased dialogue between morphology-based and molecular taxonomists and increased scrutiny of public sequence databases.Versión del editor4,411

Distribution and Habitat Associations of Billfish and Swordfish Larvae across Mesoscale Features in the Gulf of Mexico

Ichthyoplankton surveys were conducted in surface waters of the northern Gulf of Mexico (NGoM) over a three-year period (2006–2008) to determine the relative value of this region as early life habitat of sailfish (Istiophorus platypterus), blue marlin (Makaira nigricans), white marlin (Kajikia albida), and swordfish (Xiphias gladius). Sailfish were the dominant billfish collected in summer surveys, and larvae were present at 37.5% of the stations sampled. Blue marlin and white marlin larvae were present at 25.0% and 4.6% of the stations sampled, respectively, while swordfish occurred at 17.2% of the stations. Areas of peak production were detected and maximum density estimates for sailfish (22.09 larvae 1000 m−2) were significantly higher than the three other species: blue marlin (9.62 larvae 1000 m−2), white marlin (5.44 larvae 1000 m−2), and swordfish (4.67 larvae 1000 m−2). The distribution and abundance of billfish and swordfish larvae varied spatially and temporally, and several environmental variables (sea surface temperature, salinity, sea surface height, distance to the Loop Current, current velocity, water depth, and Sargassum biomass) were deemed to be influential variables in generalized additive models (GAMs). Mesoscale features in the NGoM affected the distribution and abundance of billfish and swordfish larvae, with densities typically higher in frontal zones or areas proximal to the Loop Current. Habitat suitability of all four species was strongly linked to physicochemical attributes of the water masses they inhabited, and observed abundance was higher in slope waters with lower sea surface temperature and higher salinity. Our results highlight the value of the NGoM as early life habitat of billfishes and swordfish, and represent valuable baseline data for evaluating anthropogenic effects (i.e., Deepwater Horizon oil spill) on the Atlantic billfish and swordfish populations

Mangroves and seagrass beds as diurnal feeding habitats for juvenile Haemulon flavolineatum

Item does not contain fulltextCaribbean seagrass beds supposedly are important feeding habitats for so-called nocturnally active zoobenthivorous fish, but the extent to which these fishes use mangroves and seagrass beds as feeding habitats during daytime remains unclear. Therefore, we studied daytime behavior of large juvenile (5–10 cm) and sub-adult (10–15 cm) Haemulon flavolineatum in mangroves and seagrass beds in Curaçao. Sub-adults occurred in mangroves only, spent most time on resting, and showed rare opportunistic feeding events, regardless of their social mode (solitary or schooling). They probably feed predominantly during the night in seagrass beds. Large juveniles were present in both habitat types and solitary fishes mainly foraged, while schooling fishes mainly rested. Large juveniles showed more feeding activity in seagrass beds than in mangroves. The study shows that both mangroves and seagrass beds p

Changes in Seagrass Species Composition in Northwestern Gulf of Mexico Estuaries: Effects on Associated Seagrass Fauna

The objective of this study was to measure the communities associated with different seagrass species to predict how shifts in seagrass species composition may affect associated fauna. In the northwestern Gulf of Mexico, coverage of the historically dominant shoal grass (Halodule wrightii) is decreasing, while coverage of manatee grass (Syringodium filiforme) and turtle grass (Thalassia testudinum) is increasing. We conducted a survey of fishes, crabs, and shrimp in monospecific beds of shoal, manatee, and turtle grass habitats of South Texas, USA to assess how changes in sea grass species composition would affect associated fauna. We measured seagrass parameters including shoot density, above ground biomass, epiphyte type, and epiphyte abundance to investigate relationships between faunal abundance and these seagrass parameters. We observed significant differences in communities among three seagrass species, even though these organisms are highly motile and could easily travel among the different seagrasses. Results showed species specific relationships among several different characteristics of the seagrass community and individual species abundance. More work is needed to discern the drivers of the complex relationships between individual seagrass species and their associated fauna