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AIM: The Irrawaddy dolphin (Orcaella brevirostris) is an endangered cetacean found throughout Southeast Asia. The main threat to this species is human encroachment, led by entanglement in fishing gear. Information on this data-poor species ecology and habitat use is needed to effectively inform spatial management. LOCATION: We investigated the habitat of a previously unstudied group of Irrawaddy dolphins in the eastern Gulf of Thailand, between the villages of Laem Klat and Khlong Yai, in Trat Province. This location is important as government groups plan to establish a marine protected area. METHODS: We carried out boat-based visual line transect surveys with concurrent oceanographic measurements and used hurdle models to evaluate this species patterns of habitat use in this area. RESULTS: Depth most strongly predicted dolphin presence, while temperature was a strong predictor of group size. The highest probability of dolphin presence occurred at around 10.0 m with an optimal depth range of 7.50 to 13.05 m. The greatest number of dolphins was predicted at 24.93°C with an optimal range between 24.93 and 25.31°C. Dolphins are most likely to occur in two primary locations, one large region in the center of the study area (11o5418N to 11o5923N) and a smaller region in the south (11o4728N to 11o4959N). Protections for this population will likely have the greatest chance of success in these two areas. MAIN CONCLUSIONS: The results of this work can inform management strategies within the immediate study area by highlighting areas of high habitat use that should be considered for marine spatial planning measures, such as the creation of marine protected areas. Species distribution models for this species in Thailand can also assist conservation planning in other parts of the species range by expanding our understanding of habitat preferences.

Establishing marine species distributions is essential for guiding management and can be estimated by identifying potential favorable habitat at a population level and incorporating individual‐level information (e.g., movement constraints) to inform realized space use. In this research, we applied a combined modeling approach to tracking data of adult female and juvenile South American sea lions (Otaria flavescens; n = 9) from July to November 2011 to make habitat predictions for populations in northern Chile. We incorporated topographic and oceanographic predictors with sea lion locations and environmentally based pseudo‐absences in a generalized linear model for estimating population‐level distribution. For the individual approach, we used a generalized linear mixed‐effects model with a negative exponential kernel variable to quantify distance‐dependent movement from the colony. Spatial predictions from both approaches were combined in a bivariate color map to identify areas of agreement. We then used a GIS‐based risk model to characterize bycatch risk in industrial and artisanal purse‐seine fisheries based on fishing set data from scientific observers and artisanal fleet logs (2010–2015), the bivariate sea lion distribution map, and criteria ratings of interaction characteristics. Our results indicate population‐level associations with productive, shallow, low slope waters, near to river‐mouths, and with high eddy activity. Individual distribution was restricted to shallow slopes and cool waters. Variation between approaches may reflect intrinsic factors restricting use of otherwise favorable habitat; however, sample size was limited, and additional data are needed to establish the full range of individual‐level distributions. Our bycatch risk outputs identified highest risk from industrial fisheries operating nearshore (within 5 NM) and risk was lower, overall, for the artisanal fleet. This research demonstrates the potential for integrating potential and realized distribution models within a spatial risk assessment and fills a gap in knowledge on this species' distribution, providing a basis for targeting bycatch mitigation outreach and interventions. [ABSTRACT FROM AUTHOR]

Seasonal migration, driven by shifts in annual climate cycles and resources, is a key part of the life history and ecology of species across taxonomic groups. By influencing the amount of energy needed to move, external forces such as wind and ocean currents are often key drivers of migratory pathways exposing individuals to varying resources, environmental conditions, and competition pressures impacting individual fitness and population dynamics. Although wildlife movements in connection with wind and ocean currents are relatively well understood, movements within sea‐ice fields have been much less studied, despite sea ice being an integral part of polar ecology. Adélie penguins (Pygoscelis adeliae) in the southern Ross Sea, Antarctica, currently exist at the southernmost edge of their range and undergo the longest (~12,000 km) winter migration known for the species. Within and north of the Ross Sea, the Ross Gyre drives ocean circulation and the large‐scale movement of sea ice. We used remotely sensed sea‐ice movement data together with geolocation‐based penguin movement data to test the hypothesis that penguins use gyre‐driven sea‐ice movement to aid their migration. We found that penguins traveled greater distances when their movement vectors were aligned with those of sea ice (i.e., ice support) and the amount of ice support received depended on which route a penguin took. We also found that birds that took an eastern route traveled significantly further north in two of the 3 years we examined, coinciding with higher velocities of sea ice in those years. We compare our findings to patterns observed in migrating species that utilize air or water currents for their travel and with other studies showing the importance of ocean/sea‐ice circulation patterns to wildlife movement and life history patterns within the Ross Sea. Changes in sea ice may have consequences not only for energy expenditure but, by altering migration and movement pathways, to the ecological interactions that exist in this region. [ABSTRACT FROM AUTHOR]

Temporary roads are often placed in mountainous regions for logging purposes but then never decommissioned and removed. These abandoned forest roads often have unwanted environmental consequences. They can lead to altered hydrological regimes, excess erosion, and mass wasting events. These events can affect sediment budgets in streams, with negative consequences for anadromous fish populations. Maps of these roads are frequently non-existent; therefore, methods need to be created to identify and locate these roads for decommissioning. Abandoned logging roads in the Point Reyes National Seashore in California, an area partially under heavy forest canopy, were mapped using object-based image processing in concert with machine learning. High-resolution Q1 LiDAR point clouds from 2019 were used to create a bare earth model of the region, from which a slope model was derived. This slope model was then subjected to segmentation algorithms to identify and isolate regions of differing slopes. Regions of differing slopes were then used in a convolutional neural network (CNN), and a maximum likelihood classifier was used to delineate the historic road network. The accuracy assessment was conducted using historic aerial photos of the state of the region post-logging, along with ground surveys to verify the presence of logging roads in areas of question. This method was successfully able to identify road networks with a precision of 0.991 and an accuracy of 0.992. It was also found that the CNN was able to identify areas of highest disturbance to the slope gradient. This methodology is a valuable tool for decision makers who need to identify areas of high disturbance in order to mitigate adverse effects. [ABSTRACT FROM AUTHOR]

This study examined a large, nationally-representative sample of eighth-grade students in the US to assess how the frequency of group learning activity in mathematics classrooms was associated with mathematics achievement and three measures of attitudes toward mathematics. Results showed that moderate amounts of group work in class had positive effects on mathematics achievement scores. Moreover, a significant interactive effect was evident, with girls showing greater achievement benefits from group work than boys. Increased levels of group work were also associated with more positive attitudes toward mathematics.

Lesson study is a teacher-directed program for improving instruction. It focuses on improving students' learning by systematically refining the lessons used for instruction. In this article, the authors describe the use of lesson study with preservice secondary mathematics teachers to encourage collaborative reflection and professional development. (Contains 3 figures.)

This paper reports the findings of an investigation of 11 preservice secondary school teachers' interpretations of the development of proportional reasoning strategies used by middle school students. The preservice teachers examined samples of solution strategies generated by middle school students in proportional reasoning situations and prepared written responses of their views concerning the developmental levels indicated in the students' work. Each preservice teacher also participated in an hour-long interview, in which the researchers asked for elaboration and clarification of the written responses and, in some cases, challenged the preservice teachers to consider alternative interpretations for the middle school students' work. The interviews were audiotaped for later analysis by the investigators, and key aspects of both the written and audiotaped responses were entered into a spreadsheet and later tabulated into categories indicating trends in the preservice teachers' interpretations. Some implications for the preparation of preservice middle school science and mathematics teachers are included.

Reports on two investigations examining students' thinking processes with regard to functions. Concludes that students often relied on a table or some variation of a table as a cognitive link advancing the development of their reasoning about underlying function relationships. (Author/MM)

Instructional decisions about the nature and extent of teacher input in mathematics classrooms typically lie on a continuum somewhere between teachers directly telling students how to carry out mathematical procedures […]