A model for the noninvasive, habitat-inclusive estimation of upper limit abundance for synanthropes, exemplified by M. fascicularis.

Accurately estimating population sizes for free-ranging animals through noninvasive methods, such as camera trap images, remains particularly limited by small datasets. To overcome this, we developed a flexible model for estimating upper limit populations and exemplified it by studying a group-living synanthrope, the long-tailed macaque (Macaca fascicularis). Habitat preference maps, based on environmental and GPS data, were generated with a maximum entropy model and combined with data obtained from camera traps, line transect distance sampling, and direct sightings to produce an expected number of individuals. The mapping between habitat preference and number of individuals was optimized through a tunable parameter ρ (inquisitiveness) that accounts for repeated observations of individuals. Benchmarking against published data highlights the high accuracy of the model. Overall, this approach combines citizen science with scientific observations and reveals the long-tailed macaque populations to be (up to 80%) smaller than expected. The model's flexibility makes it suitable for many species, providing a scalable, noninvasive tool for wildlife conservation.

Morphodynamics of a composite sand-cobble beach in response to extratropical cyclone Fiona and seasonal wave variability.

Climate change is driving higher coastal water levels, and models project accelerated future sea-level rise and coastal storm intensification. These dynamics paired with anthropogenic coastal alterations will drive drastic coastal change worldwide. Composite beaches with mixed sediment sizes warrant detailed study as these exhibit complex morphodynamics in response to changing hydrodynamics due to the distinct transport thresholds of different sediment types. This study uses a novel multi-method approach to investigate a composite sand-cobble beach in Atlantic Canada experiencing a shortening seasonal sand-covered period. Hydrodynamic forcing and associated beach changes were monitored over a focused eight-month period, while satellite-based visual imagery and reconstructed wave data were analyzed over longer periods. Results show that intra-annual wave energy changes drive sand dynamics, with reduced summer wave energy facilitating short-term deposition. Long-term positive trends were identified in late spring wave heights, which likely contribute to the shortening sand-covered period. Seasonal dynamics were overwhelmed by extratropical cyclone Fiona, which made landfall on September 24, 2022, generating significant wave heights up to 6.8 m in the bay, mobilizing sediment, and steepening cobble berms. A new index approach based on visual imagery facilitated the investigation of beach sand appearance/disappearance using the relative redness of sand compared to cobble. Finally, the UAV-based surveys yielded high-resolution orthomosaics and LiDAR-based elevation mapping, and highlighted pronounced longshore variability in erosion and deposition during Fiona. The beach mostly recovered to pre-storm conditions in <4 months, which indicates that proposed beach nourishment activities may only experience temporary success. The longer-term results showing a conversion of sand to cobble suggest that loss of sandy beach habitat is likely to increase, even without shoreline migration or coastal squeeze driven by sea-level rise.