No abstract

Species that respond to ecosystem change in a timely, measurable, and interpretable way can be used as sentinels of global change. Contrary to a pervasive view, we suggest that, among Carnivora, small carnivores are more appropriate sentinels than large carnivores. This reasoning is built around six key points: that, compared to large carnivores, small carnivores 1) are more species-rich and diverse, providing more potential sentinels in many systems; 2) occupy a wider range of ecological niches, exhibiting a greater variety of sensitivities to change; 3) hold an intermediate trophic position that is more directly affected by changes at the producer, primary consumer, and tertiary consumer levels; 4) have shorter life spans and higher reproductive rates, exhibiting more rapid responses to change; 5) have smaller home ranges and are more abundant, making it easier to investigate fine-scale management interventions; 6) are easier to monitor, manage, and manipulate. Therefore, we advocate for incorporating

Access to field experiences can increase participation of diverse groups in the environmental and natural resources (ENR) workforce. Despite a growing interest among the ENR community to attract and retain diverse students, minimal data exist on what factors undergraduate students prioritize when applying for field experiences. Using a nationwide survey of US undergraduate ENR students, we show that attracting most students to field experiences—especially racial or ethnic minority students—will require pay above minimum wage. However, the concurrent landscape of pay in ENR fell short of meeting many students’ pay needs. Aside from pay, ENR students valued training in technical field skills and analytical or research skills, working with their desired study species or taxa, and working near school or family. Additional barriers beyond limited pay included incompatible schedules and noninclusive work environments. Our findings provide important insights for attracting a diverse workforce to this critical stage in career advancement for students in ENR.

Wild pigs (Sus scrofa), which are invasive in many regions globally, can alter ecosystems and compete with native species through interference competition and resource exploitation. Wild pig impacts on other species may increase with greater niche overlap, which could vary over time based on environmental conditions, resource availability, or biological traits like diet, especially as seasonal variation in wild pig diet has been widely documented. A limited number of studies have assessed spatial or temporal overlap between native species and invasive wild pigs, with only a handful simultaneously assessing overlap in these niche dimensions. We investigated the potential for interspecific interactions involving invasive wild pigs in the Piedmont region of South Carolina, USA, by examining seasonal spatiotemporal overlap with other wildlife using N‐mixture models and diel activity overlap analyses. Site use by white‐tailed deer (Odocoileus virginianus) and coyote (Canis latrans) was negatively associated with wild pig activity in the fall, when the species had high diel activity overlap, indicating spatial partitioning could reduce interference competition with wild pigs in this season. Conversely, white‐tailed deer site use was positively associated with wild pig activity in the winter, suggesting higher spatial overlap may be necessary if resources are limited. Site use by bobcat (Lynx rufus) and nine‐banded armadillo (Dasypus novemcinctus) in the spring, along with raccoon (Procyon lotor) and wild turkey (Meleagris gallopavo) site use in the summer, was positively associated with wild pig activity. With the exception of diurnal wild turkey, diel activity overlap between these species and wild pigs was high, although temporal partitioning could have occurred at finer spatiotemporal scales than we examined. Our results collectively emphasize the importance of accounting for seasonal spatial and temporal responses by individual species to invasive wild pigs, with special consideration given to species in seasons where high niche overlap with wild pigs is anticipated.

River systems face negative impacts from development and removal of riparian vegetation that provide critical shading in the face of climate change. This study used supervised deep learning to accurately classify the land cover, including shading, of the Chauga River watershed, located in Oconee County, South Carolina, for 2011 and 2019. The study examined the land cover differences along the Chauga River and its tributaries, inside and outside the Sumter National Forest. LiDAR data were incorporated in solar radiation calculations for the Chauga River inside and outside the National Forest. The deep learning classifications produced land cover maps with high overall accuracy (97.09% for 2011; 97.58% for 2019). The most significant difference in land cover was in tree cover in the 50 m buffer of the tributaries inside the National Forest compared to the tributaries outside the National Forest (2011: 95.39% vs. 81.84%, 2019: 92.86% vs. 82.06%). The solar radiation calculations also confirmed a difference between the area inside and outside the National Forest, with the mean temperature being greater outside the protected area (outside: 455.845 WH/m2; inside: 416,770 WH/m2). This study suggests that anthropogenic influence in the Chauga River watershed is greater in the areas outside the Sumter National Forest, which could cause damage to the river ecosystem if left unchecked in the future as development pressures increase. This study demonstrates the accurate application of deep learning for high-resolution classification of river shading combined with the use of LiDAR data to estimate solar radiation reaching the Chauga River. Techniques to monitor riparian zones and shading at high spatial resolutions are critical for the mitigation of the negative impacts of warming climates on aquatic ecosystems.