Adapting Macroecology to Microbiology: Using Occupancy Modeling To Assess Functional Profiles across Metagenomes

Metagenomics is maturing rapidly as a field but is hampered by a lack of available statistical tools. A primary area of uncertainty is around missing genes or functions from a metagenomic data set.

Variation in herpetofauna detection probabilities: implications for study design

Population monitoring is fundamental for informing management decisions aimed at reducing the rapid rate of global biodiversity decline. Herpetofauna are experiencing declines worldwide and include species that are challenging to monitor. Raw counts and associated metrics such as richness indices are common for monitoring populations of herpetofauna; however, these methods are susceptible to bias as they fail to account for varying detection probabilities. Our goal was to develop a program for efficiently monitoring herpetofauna in southern Texas. Our objectives were to (1) estimate detection probabilities in an occupancy modeling framework using trap arrays for a diverse group of herpetofauna and (2) to evaluate the relative effectiveness of funnel traps, pitfall traps, and cover boards. We collected data with 36 arrays at 2 study sites in 2015 and 2016, for 2105 array-days resulting in 4839 detections of 51 species. We modeled occupancy for 21 species and found support for the hypothesis that detection probability varied over our sampling duration for 10 species and with rainfall for 10 species. For herpetofauna in our study, we found 14 and 12 species were most efficiently captured with funnel traps and pitfall traps, respectively, and no species were most efficiently captured with cover boards. Our results show that using methods that do not account for variations in detection probability are highly subject to bias unless the likelihood of false absences is minimized with exceptionally long capture durations. For monitoring herpetofauna in southern Texas, we recommend using arrays with funnel and pitfall traps and an analytical method such as occupancy modeling that accounts for variation in detection.

Occupancy and Population Abundance of Two Serpent-Eagles (Spilornis elgini and S. cheela) In the Andaman Islands, India

ABSTRACT We estimated occupancy and population abundance of the Andaman Serpent-Eagle (Spilornis elgini) and Crested Serpent-Eagle (Spilornis cheela) in the Andaman Islands, India. We divided the islands that were > 100 km2 into a grid of 84 cells, of which we used 34 cells (5 km × 5 km each) for surveys of two populations in the districts of (1) the North and Middle Andaman Islands, and (2) the South Andaman Islands, which includes Little Andaman Island. We performed single-season, single-species occupancy modeling independently for both regions and single-season, two-species occupancy modeling for co-occupancy in the surveyed landscapes. The estimated abundance for the Andaman Serpent-Eagle and the Crested Serpent-Eagle was 4–5 and 7–8 individuals per 25 km2, respectively. The Andaman Serpent-Eagle is commonly distributed in both regions and has a high detection probability (detection probability, P = 0.8). The Crested Serpent-Eagle is widely distributed in the South Andaman Islands with a low detection probability (P = 0.5). The single-season, two-species occupancy model showed that the endemic Andaman Serpent-Eagle occupied only 22% of the area and did not co-occur with the Crested Serpent-Eagle. It also indicates the possible avoidance or exclusion of the Crested Serpent-Eagle by the Andaman Serpent-Eagle. We encountered both serpent-eagles in all the identified habitat types. The Crested Serpent-Eagle's habitat use was not restricted to the coastal forests, as previously reported, and the Crested Serpent-Eagle is probably dominating the Andaman Serpent-Eagle in the co-occupied areas. We further conclude that the occupancy dynamics and competition for space between these two Spilornis species might significantly affect the distribution and population of the vulnerable and endemic Andaman Serpent-Eagle in the future.

Rethinking habitat occupancy modeling and the role of diel activity in an anthropogenic world

Current methods to model species habitat use through space and diel time are limited. Development of such models is critical when considering rapidly changing habitats where species are forced to adapt to anthropogenic change, often by shifting their diel activity across space. We use an occupancy modeling framework to develop a new model, the multi-state diel occupancy model (MSDOM), which can evaluate species diel activity against continuous response variables which may impact diel activity within and across seasons or years. We used two case studies, fosa in Madagascar and coyote in Chicago, USA, to conceptualize the application of this model and to quantify the impacts of human activity on species spatial use in diel time. We found support that both species varied their habitat use by diel states—in and across years, and by human disturbance. Our results exemplify the importance of understanding animal diel activity patterns and how human disturbance can lead to temporal habitat loss. The MSDOM will allow more focused attention in ecology and evolution studies on the importance of the short temporal scale of diel time in animal-habitat relationships and lead to improved habitat conservation and management.