SCNIC: Sparse correlation network investigation for compositional data

Microbiome studies are often limited by a lack of statistical power due to small sample sizes and a large number of features. This problem is exacerbated in correlative studies of multi-omic datasets. Statistical power can be increased by finding and summarizing modules of correlated observations, which is one dimensionality reduction method. Additionally, modules provide biological insight as correlated groups of microbes can have relationships among themselves. To address these challenges, we developed SCNIC: Sparse Cooccurrence Network Investigation for compositional data. SCNIC is open-source software that can generate correlation networks and detect and summarize modules of highly correlated features. Modules can be formed using either the Louvain Modularity Maximization (LMM) algorithm or a Shared Minimum Distance algorithm (SMD) that we newly describe here and relate to LMM using simulated data. We applied SCNIC to two published datasets and we achieved increased statistical power and identified microbes that not only differed across groups, but also correlated strongly with each other, suggesting shared environmental drivers or cooperative relationships among them. SCNIC provides an easy way to generate correlation networks, identify modules of correlated features and summarize them for downstream statistical analysis. Although SCNIC was designed considering properties of microbiome data, such as compositionality and sparsity, it can be applied to a variety of data types including metabolomics data and used to integrate multiple data types. SCNIC allows for the identification of functional microbial relationships at scale while increasing statistical power through feature reduction.     

Using theoretical models to explore dispersal variation and fragmentation in urban environments

Cities are fundamentally changing the environment that plants inhabit, most notably through habitat fragmentation. Urban plant habitat patches are separated by impervious surfaces like buildings and roads and may vary from small, isolated green spaces to large green spaces like parks. Understanding the consequences of this urban fragmentation on seed dispersal is essential to both maintain urban biodiversity and mitigate the spread of unwanted weeds or invasive species but we currently lack enough empirical data to draw generalities. Theoretical reasoning (via both verbal and mathematical models) is well positioned to contribute to this knowledge gap in dispersal by providing useful predictions when empirical data are lacking. Variation in dispersal can easily be captured by models by incorporating different dispersal kernel shapes, and multiple habitat configurations can be examined. Urban environments are rarely considered by mathematical models, and our literature review indicates that most models that include dispersal variation via a dispersal kernel use only one or two shapes, suggesting a gap in the theoretical literature as well. We present a proof-of-concept model of fragmentation in an urban environment illustrating how varying habitat width can lead to different outcomes depending on the dispersal kernel. We also provide some thoughts for future directions on the application of mathematical models in urban areas.     

Addressing a potential weakness in indices of predation,herbivory, and parasitism

Quantification of predation, herbivory, and parasitism is critical to understanding the dynamics and trophic interactions of populations in an ecosystem. Such quantification can be challenging if the availability or consumption of the taxa are difficult to assess. Sometimes the consumption of a single prey, forage, or host is used as an overall index of the predation, herbivory, or parasitism for a population of interest. Occasionally, human-manipulated baits are used to derive similar indices. However, all such indices are susceptible to influence by variation in the abundance of the preferred taxon relative to other taxa as the result of preference switching. In this article, I describe a test for preference switching (and an adjustment, if detected) that does not require availability and consumption of the prey (forage, or host) to be measured on the same scale. The ability to detect and adjust for preference switching in such situations may advance the understanding of biological preference in taxa not previously studied in this respect.     

Quantifying the direct fire threat to a critically endangered arboreal marsupial using biophysical,mechanistic modelling

Historically unprecedented areas of forest habitat have been impacted by fire, as climate change and other anthropogenic disturbances drive increases in fire burned area and severity. Although 88% of Australia's [threatened] land mammals are threatened by inappropriate fire regimes, calculations of animal mortality resulting from specific events have been impeded by knowledge gaps relating to both the direct (first-order) and long-term (second-order) effects of fire on different species. This study addresses the need for a quantified, mechanistic understanding of first-order effects, presenting an extension of the Fire Research and Modelling Environment (FRaME) to allow prediction of species-specific mortality. FRaME is demonstrated and tested here by replicating an incident in which a prescribed burn caused 77% mortality of a population of the critically endangered ngwayir (Pseudocheirus occidentalis, Pseudocheiridae). FRaME correctly predicted heavy mortality (62–79%) arising from partial and full-thickness burns and asphyxiation due to burns in the respiratory tract. Mortality varied with animal fire-avoidance strategies (p < 0.001) and the thickness of tree hollow walls (r = −0.95, p < 0.001). Although management guidelines specified low intensity fire, mortality had no significant relationship with Byram intensity and larger flames due to ‘torching’ were most frequent when fire spread was slowest. FRaME modelling predicted that individuals would be impacted by temperatures exceeding 500°C for several minutes. Fire management that is premised on discredited notions of fire behaviour and overly simple models can lead to catastrophic management outcomes such as those documented here. FRaME addresses this need by providing a platform to account for heterogeneous fire behaviour as well as animal behaviour and habitat quality, calculating fire risk to fauna and guiding management that maximizes safe habitat.     

Influence of nest box design on internal microclimate: Comparisons of plastic prototypes

Hollow-dependent fauna are declining worldwide, due primarily to the widespread clearing of hollow-bearing trees. Artificial cavities such as timber and plywood boxes are commonly used to increase hollow availability, yet there is increasing evidence that they are poor facsimiles of natural cavities, characterized by lower insulative properties and a shorter field life. We evaluated whether plastic materials could create a nest box with a stable thermal profile that more closely resembles the complex shapes and textures of natural tree hollows while containing fewer mechanical joins that represent potential failure points when installed. We developed three sets of prototype nest boxes comprising various combinations of plastic density (10%, 25% and 50%), insulation (single vs. double wall with or without sawdust between them), nesting chamber (with or without timber inserts) and bedding (with or without decomposed heartwood) and compared their thermal performance in a temperature-controlled laboratory to compare internal temperature and relative humidity. We found double-walled plastic nest box with an internal timber-lined chamber was best able to buffer ambient temperature fluctuations, consistently recording internal temperatures of 6⁺°C below maximum ambient temperature, maintaining high levels of relative humidity (76%–92%) when furnished with decomposed timber heartwood. This design also performed better during a simulated hot day; internal temperatures exhibiting twice the lag time of single-walled designs, noting that plastic density had little influence on internal conditions. While the recruitment and protection of hollow-bearing trees must be a priority, this work shows significant potential in improving the design and functionality of artificial hollows that are critical to the conservation of hollow-dependent species.     

Interannual patterns of avian diseases in wild New Zealand avifauna near conservation areas

The past few years have seen a noticeable increase in the emergence of infectious diseases in wildlife, especially vector-borne diseases, presenting a challenge for the conservation of endangered species. One such vector-borne disease, avian malaria (Plasmodium spp.) is on the rise in New Zealand avifauna, threatening bird populations that are among the most extinction-prone in the world. Furthermore, recent reports have outlined an increase in deaths of native iconic bird species specifically due to this disease. In order to help manage breakouts of this pathogen at a local scale, we need a better understanding of potential drivers of the emergence of avian malaria in wild New Zealand avifauna. Here, we set to test the role of climatic drivers in synchronizing contacts between avian hosts and vectors, assess the temporal stability of transmission dynamics between years, and determine the role of introduced species in causing spill-over of this pathogen towards native species. Our study focused on three sites that were sampled regularly during two consecutive years in the austral summer, each site being adjacent to a breeding colony of Yellow-eyed penguins (Megadyptes antipodes). Our results reveal an overall temporal stability of avian malaria incidence patterns, with a decrease in infection throughout the austral summer for both sampled years. Moreover, we highlight a phylogenetic signal among sampled bird species, with introduced species being more heavily infected by avian malaria than their native counterparts. In contrast, we found no effect of the two climatic drivers investigated, temperature and rainfall, on mosquito abundance. Our results suggest a strong effect of alien species acting as reservoirs for diseases spilling-over towards immunologically naïve species, and provide conservation managers with a critical timeframe to control avian malaria breakouts.     

Patch size and breeding status influence movement patterns in the threatened Malleefowl (Leipoa ocellata)

Information on the movement ecology of species can assist with identifying barriers to dispersal and appropriate management actions. We focus on the threatened Malleefowl (Leipoa ocellata) whose ability to move and disperse within fragmented landscapes is critical for their survival. We also investigate the possible effects of climate change on Malleefowl movement. We used solar-powered GPS telemetry to collect movement data and determine the influence of breeding status, remnant vegetation patches and environmental variables. Seven Malleefowl were tracked between 1 and 50 months, resulting in 20 932 fixes. While breeding, Malleefowl had significantly smaller home ranges (92 ± 43 ha breeding; 609 ± 708 ha non-breeding), moved shorter daily distances (1283 ± 605 breeding; 1567 ± 841 non-breeding) and stayed closer to the incubation mound (349 ± 324 m breeding; 3293 ± 2715 m non-breeding). Most Malleefowl effectively disassociated from the mound once breeding stopped, with two birds dispersing up to 10.2 km. Movement patterns were significantly correlated with the size of the remnant native vegetation patch, with smaller home ranges being utilized in small patches than in large patches. One male almost exclusively remained within a 107-ha patch for over 4 years, but a female crossed between closely spaced uncleared patches. Long-range movements of nearly 10 km daily displacement were recorded in large remnants almost exclusively when not breeding. Temperature and rain had a significant effect on movement: modelling suggests daily distances decline from 1.3 km at 25°C to 0.9 km at 45°C, with steeper declines over 30°C. The influence of patch size on movement patterns suggests that Malleefowl movement may be governed by the size of remnant patches and that habitat continuity may be important for facilitating recolonization after catastrophic events and maintaining genetic diversity. Climate change may reduce Malleefowl movement during hot, dry periods possibly affecting breeding success.     

Humidity – The overlooked variable in the thermal biology of mosquito-borne disease

Vector-borne diseases cause significant financial and human loss, with billions of dollars spent on control. Arthropod vectors experience a complex suite of environmental factors that affect fitness, population growth and species interactions across multiple spatial and temporal scales. Temperature and water availability are two of the most important abiotic variables influencing their distributions and abundances. While extensive research on temperature exists, the influence of humidity on vector and pathogen parameters affecting disease dynamics are less understood. Humidity is often underemphasized, and when considered, is often treated as independent of temperature even though desiccation likely contributes to declines in trait performance at warmer temperatures. This Perspectives explores how humidity shapes the thermal performance of mosquito-borne pathogen transmission. We summarize what is known about its effects and propose a conceptual model for how temperature and humidity interact to shape the range of temperatures across which mosquitoes persist and achieve high transmission potential. We discuss how failing to account for these interactions hinders efforts to forecast transmission dynamics and respond to epidemics of mosquito-borne infections. We outline future research areas that will ground the effects of humidity on the thermal biology of pathogen transmission in a theoretical and empirical framework to improve spatial and temporal prediction of vector-borne pathogen transmission.