The influence of scale-dependent geodiversity on species distribution models in a biodiversity hotspot.

Improving models of species' distributions is essential for conservation, especially in light of global change. Species distribution models (SDMs) often rely on mean environmental conditions, yet species distributions are also a function of environmental heterogeneity and filtering acting at multiple spatial scales. Geodiversity, which we define as the variation of abiotic features and processes of Earth's entire geosphere (inclusive of climate), has potential to improve SDMs and conservation assessments, as they capture multiple abiotic dimensions of species niches, however they have not been sufficiently tested in SDMs. We tested a range of geodiversity variables computed at varying scales using climate and elevation data. We compared predictive performance of MaxEnt SDMs generated using CHELSA bioclimatic variables to those also including geodiversity variables for 31 mammalian species in Colombia. Results show the spatial grain of geodiversity variables affects SDM performance. Some variables consistently exhibited an increasing or decreasing trend in variable importance with spatial grain, showing slight scale-dependence and indicating that some geodiversity variables are more relevant at particular scales for some species. Incorporating geodiversity variables into SDMs, and doing so at the appropriate spatial scales, enhances the ability to model species-environment relationships, thereby contributing to the conservation and management of biodiversity. This article is part of the Theo Murphy meeting issue 'Geodiversity for science and society'.

GenePlexus: a web-server for gene discovery using network-based machine learning.

Biomedical researchers take advantage of high-throughput, high-coverage technologies to routinely generate sets of genes of interest across a wide range of biological conditions. Although these technologies have directly shed light on the molecular underpinnings of various biological processes and diseases, the list of genes from any individual experiment is often noisy and incomplete. Additionally, interpreting these lists of genes can be challenging in terms of how they are related to each other and to other genes in the genome. In this work, we present GenePlexus (https://www.geneplexus.net/), a web-server that allows a researcher to utilize a powerful, network-based machine learning method to gain insights into their gene set of interest and additional functionally similar genes. Once a user uploads their own set of human genes and chooses between a number of different human network representations, GenePlexus provides predictions of how associated every gene in the network is to the input set. The web-server also provides interpretability through network visualization and comparison to other machine learning models trained on thousands of known process/pathway and disease gene sets. GenePlexus is free and open to all users without the need for registration.

Early-life relationships matter: Social position during early life predicts fitness among female spotted hyenas.

How social development in early-life affects fitness remains poorly understood. Though there is growing evidence that early-life relationships can affect fitness, little research has investigated how social positions develop or whether there are particularly important periods for social position development in an animal's life history. In long-lived species in particular, understanding the lasting consequences of early-life social environments requires detailed, long-term datasets. Here we used a 25-year dataset to test whether social positions held during early development predicted adult fitness. Specifically, we quantified social position using three social network metrics: degree, strength and betweenness. We determined the social position of each individual in three types of networks during each of three stages of ontogeny to test whether they predict annual reproductive success (ARS) or longevity among adult female spotted hyenas Crocuta crocuta. The social positions occupied by juvenile hyenas did predict their fitness, but the effects of social position on fitness measures differed between stages of early development. Network metrics when individuals were young adults better predicted ARS, but network metrics for younger animals, particularly when youngsters were confined to the communal den, better predicted longevity than did metrics assessed during other stages of development. Our study shows how multiple types of social bonds formed during multiple stages of social development predict lifetime fitness outcomes. We suggest that social bonds formed during specific phases of development may be more important than others when considering fitness outcomes.

Lions, hyenas and mobs (oh my!).

Understanding the factors that facilitate the emergence of cooperation among organisms is central to the study of social evolution. Spotted hyenas Crocuta crocuta frequently cooperate to mob lions Panthera leo, approaching the lions as a tightknit group while vocalizing loudly in an attempt to overwhelm them and drive them away. Whereas cooperative mobbing behavior has been well documented in birds and some mammals, to our knowledge it has never been described during interactions between 2 apex predators. Using a 27-year dataset, we characterize lion-hyena encounters, assess rates of mobbing behavior observed during these interactions, and inquire whether mobbing results in successful acquisition of food. Lions and hyenas interacted most often at fresh kills, especially as prey size and the number of hyenas present increased. Possession of food at the beginning of an interaction positively affected retention of that food by each predator species. The presence of male lions increased the probability of an interspecific interaction but decreased the likelihood of hyenas obtaining or retaining possession of the food. Hyena mobbing rates were highest at fresh kills, but lower when adult male lions were present. The occurrence of mobbing was predicted by an increase in the number of hyenas present. Whether or not mobbing resulted in acquisition of food from lions was predicted by an increase in the number of mobs formed by the hyenas present, suggesting that cooperation among hyenas enhances their fitness.