A random survival forest illustrates the importance of natural enemies compared to host plant quality on leaf beetle survival rates

Reliability of satellite-based vegetation maps for planning wildfire-fuel treatments in shrub steppe: Inferences from two contrasting national parks

Protecting habitat threatened by increasing wildfire size and frequency requires identifying the spatial intersection of wildfire behavior and ecological conditions that favor positive management outcomes. In the perennial sagebrush steppe of Western North America, invasions by fire-prone annual grasses are a key concern, and management of them requires reliable maps of vegetation cover, fuels, and wildfire behavior. We compared commonly used, publicly available vegetation cover and fuels maps, specifically the Rangeland Analysis Platform (RAP) and LANDFIRE, with field-based assessments at two U.S. National Parks dominated by sagebrush steppe: City of Rocks National Reserve and Craters of the Moon National Monument and Preserve. Plant-community composition and fuels measured at ∼1700 field locations spanning ∼300,000 ha revealed that 1) RAP generally underestimated each vegetation cover type where the cover was actually abundant, and conversely overestimated cover types where they were actually scarce, and 2) there was considerable disagreement in fuel-bed maps derived from LANDFIRE compared to field observations. As a result, there were substantial discrepancies in the spatial patterning of wildfire behavior estimated from the fire-spread model FLAMMAP when parameterized with LANDFIRE compared to field-based fuel-bed maps created from Random Forests models. Reliable maps of vegetation cover and fuel conditions are needed to help guide fuels and invasive species management, especially given recent increases in pre- and post-fire treatments in arid and semiarid landscapes. The costs associated with poorly informed fuel reduction may greatly exceed the costs of field-based vegetation and fuels inventory to inform effective design of vegetative fuels treatments.

Poor air quality raises mortality in honey bees, a concern for all pollinators

Human well-being relies on the presence and role of pollinators, as they contribute to the vitality of ecosystems, support the reproduction of wild plants, increase crop yields, and strengthen overall food security. While wild bee populations are dwindling due to climate and environmental change, there has been a notable 45% rise globally in the number of managed honey bee (Apis mellifera) colonies over the past five decades. Given their economic significance and their relative ease of tracking, honey bees have the potential to serve as bioindicators of global pollinator health. Consequently, honey bees have emerged as a keystone species requiring protection and conservation efforts. Here, we investigate the intricate relationship between air quality, environmental factors, and honey bee mortality across Canada and the United States. Using statistical and machine learning modeling, our findings underscore the honey bee's role as a bioindicator. We found that air quality is an important predictor of honey bee mortality. The risk of honey bee mortality increased with poor air quality (ozone and Air Quality Health Index) but was substantially reduced in regions with greater vegetation availability (Normalized Difference Vegetation Index). Therefore, our study offers a beacon of hope: improving management practices by increasing greenery can significantly mitigate the impact of deteriorating air quality on honey bees, providing a vital solution to safeguard our essential pollinators.

Aggregation pheromones have a non-linear effect on oviposition behavior in Drosophila melanogaster

Female fruit flies (Drosophila melanogaster) oviposit at communal sites where the larvae may cooperate or compete for resources depending on group size. This offers a model system to determine how females assess quantitative social information. We show that the concentration of pheromones found on a substrate increases linearly with the number of adult flies that have visited that site. Females prefer oviposition sites with pheromone concentrations corresponding to an intermediate number of previous visitors, whereas sites with low or high concentrations are unattractive. This dose-dependent decision is based on a blend of 11-cis-Vaccenyl Acetate (cVA) indicating the number of previous visitors and heptanal (a novel pheromone deriving from the oxidation of 7-Tricosene), which acts as a dose-independent co-factor. This response is mediated by detection of cVA by odorant receptor neurons Or67d and Or65a, and at least five different odorant receptor neurons for heptanal. Our results identify a mechanism allowing individuals to transform a linear increase of pheromones into a non-linear behavioral response.

Seven Questions on the Chemical Ecology and Neurogenetics of Resource-Mediated Speciation

Adaptation to different environments can result in reproductive isolation between populations and the formation of new species. Food resources are among the most important environmental factors shaping local adaptation. The chemosensory system, the most ubiquitous sensory channel in the animal kingdom, not only detects food resources and their chemical composition, but also mediates sexual communication and reproductive isolation in many taxa. Chemosensory divergence may thus play a crucial role in resource-mediated adaptation and speciation. Understanding how the chemosensory system can facilitate resource-mediated ecological speciation requires integrating mechanistic studies of the chemosensory system with ecological studies, to link the genetics and physiology of chemosensory properties to divergent adaptation. In this review, we use examples of insect research to present seven key questions that can be used to understand how the chemosensory system can facilitate resource-mediated ecological speciation in consumer populations.

Discrete-time survival forests with Hellinger distance decision trees

Random survival forests (RSF) are a powerful nonparametric method for building prediction models with a time-to-event outcome. RSF do not rely on the proportional hazards assumption and can be readily applied to both low- and higher-dimensional data. A remaining limitation of RSF, however, arises from the fact that the method is almost entirely focussed on continuously measured event times. This issue may become problematic in studies where time is measured on a discrete scale $$t = 1, 2, ...$$ t = 1 , 2 , . . . , referring to time intervals $$[0,a_1), [a_1,a_2), \ldots $$ [ 0 , a 1 ) , [ a 1 , a 2 ) , … . In this situation, the application of methods designed for continuous time-to-event data may lead to biased estimators and inaccurate predictions if discreteness is ignored. To address this issue, we develop a RSF algorithm that is specifically designed for the analysis of (possibly right-censored) discrete event times. The algorithm is based on an ensemble of discrete-time survival trees that operate on transformed versions of the original time-to-event data using tree methods for binary classification. As the outcome variable in these trees is typically highly imbalanced, our algorithm implements a node splitting strategy based on Hellinger’s distance, which is a skew-insensitive alternative to classical split criteria such as the Gini impurity. The new algorithm thus provides flexible nonparametric predictions of individual-specific discrete hazard and survival functions. Our numerical results suggest that node splitting by Hellinger’s distance improves predictive performance when compared to the Gini impurity. Furthermore, discrete-time RSF improve prediction accuracy when compared to RSF approaches treating discrete event times as continuous in situations where the number of time intervals is small.

Ecology of Terrestrial Arthropods in Freshwater Wetlands

The terrestrial arthropod fauna of wetlands has been largely ignored by scientists compared to other ecological elements, yet these organisms are among the most important influences on the ecology of these systems, with the vast majority of the biodiversity in wetlands found among the terrestrial arthropods. Wetlands present a range of habitat for terrestrial arthropods, with unique faunas being associated with soils and ground litter, living-plant substrates, and peatlands. Myriapoda, Araneae, Collembola, Carabidae, Formicidae, and assorted herbivorous Coleoptera and Lepidoptera are the terrestrial arthropod groups that most influence the ecology of wetlands. Despite their success, most terrestrial arthropods possess fairly rudimentary adaptations for life in wetlands, with most simply moving to higher ground or up vegetation during floods, although some species can tolerate immersion. Many terrestrial arthropods are environmentally sensitive and show considerable promise as bioindicators of wetland ecological conditions.