Landscape Characteristics Affecting Small Mammal Occurrence in Heterogeneous Olive Grove Agro-Ecosystems

Understanding how small mammals (SM) are associated with environmental characteristics in olive groves is important to identify potential threats to agriculture and assess the overall conservation value and functioning of agro-ecosystems. Here, we provide first insights on this topic applied to traditional olive groves in northeast (NE) Portugal by assessing the landscape attributes that determine SM occurrence, focusing on one species of conservation concern (Microtus cabrerae Thomas 1906) and one species often perceived as a potential pest of olives (Microtus lusitanicus Gerbe 1879). Based on SM genetic non-invasive sampling in 51 olive groves and surrounding habitats, we identified seven rodent species and one insectivore. Occupancy modelling indicated that SM were generally less detected within olive groves than in surrounding habitats. The vulnerable M. cabrerae reached a mean occupancy (95% CI) of 0.77 (0.61–0.87), while M. lusitanicus stood at 0.37 (0.24–0.52). M. cabrerae was more likely to occur in land mosaics with high density of agricultural field edges, while M. lusitanicus was more associated with high density of pastureland patches. Overall, our study suggests that the complex structure and spatial heterogeneity of traditionally managed olive grove agro-ecosystems may favor the occurrence of species-rich SM communities, possibly including well-established populations of species of conservation importance, while keeping potential pest species at relatively low occupancy rates.

Variable detectability and El-Niño associations with riparian snakes in Sabah, Malaysian Borneo

Although snake populations are suffering numerous local declines, determining the scale of these declines is problematic due to the elusive nature of snakes. Determining the factors associated with species detection is therefore essential for quantifying disturbance effects on populations. From 2017 to 2019, we assessed the detectability associations of five river-associated snake species and all snake detections in general within two logging concessions in Sabah, Malaysian Borneo. Data collected from both stream transects and visual encounter surveys at 47 stream sites were incorporated into an occupancy-modelling framework to determine the climatological, temporal and survey distance associations with species detection probability. Detection probability of riparian snake species was significantly associated with humidity, month (2 spp. each), survey distance and total rainfall over 60 days (1 spp. each). Pooled snake species detectability was significantly positively associated with transect distance and the 2019 El-Niño year, whilst yearly pooled snake species detections in stream transects spiked during El-Niño (2017 = 2.05, 2018 = 2.47, 2019 = 4.5 snakes per km). This study provides new insights into the detectability of riparian rainforest snakes and suggests that future studies should account for short-term (climatological and temporal) and long-term (El-Niño) factors associated with detection probability when surveying and assessing snake populations.

Habitat Occupancy by Spruce Grouse (Canachites canadensis) in the south of its range, Québec, Canada

Studying habitat occupancy at the margins of species’ distributions can be helpful in clarifying species’ requirements and planning management measures. Spruce grouse (Canachites canadensis Linnaeus, 1758), a bird species associated with northern short-needle coniferous forests in North America, has its southeastern range limit where coniferous forests are mixed with temperate deciduous forests and agricultural lands. Some isolated populations are found in these habitats. Using a single-season occupancy modelling approach, we investigated habitat use by spruce grouse, accounting for imperfect detection, in the lowlands of the St. Lawrence River in southern Québec, Canada. We conducted call-response spruce over three years at 279 sites (59 sites in 2007, 100 sites in 2008 and 120 sites in 2009). At the site level, the probability of occupancy was 21% (IC: 10.7% - 37.9%) and probability of detection was 54% (IC: 34.7% - 73.0%). Based on the covariates in the models, occurrence increased with higher cover of coniferous trees and low deciduous shrubs, and decreased with higher cover of deciduous trees. Finally, detection probability was highest at the beginning of the survey (50% in late April) and was influenced by year.

Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets

We combined participatory science data and museum records to understand long-term changes in occupancy for 29 ant species in Denmark over 119 years. Bayesian occupancy modelling indicated change in occupancy for 15 species: five increased, four declined and six showed fluctuating trends. We consider how trends may have been influenced by life-history and habitat changes. Our results build on an emerging picture that biodiversity change in insects is more complex than implied by the simple insect decline narrative.

Fine-scale distribution and occupancy modelling of the threatened pugnose shiner (Notropis anogenus) in the St. Lawrence River, Ontario, Canada1

Understanding population-level habitat requirements is important for the effective conservation of imperilled species, especially for those with fragmented distributions. This study examined fine-scale distribution of the threatened pugnose shiner (Notropis anogenus) in the upper St. Lawrence River, Ontario, Canada. Occupancy modelling, multivariate analyses, and co-occurrence modelling were used to identify environmental correlates of pugnose shiner distribution and species associations in an embayment area, Thompson’s Bay. The pugnose shiner was most abundant in outer bay sites that were cooler, less turbid, had a higher pH, and had more submerged aquatic vegetation than the inner bay sites. The probability of pugnose shiner occupancy increased with distance from the inner bay and with the presence of Chara vulgaris, and decreased with increasing conductivity. The pugnose shiner positively co-occurred with seven species, including the blackchin shiner and blacknose shiner, and negatively co-occurred with bluegill. Centrarchid species were dominant across Thompson’s Bay. This has important conservation implications because some native centrarchid predators are increasing in abundance, coincident with climate change, which may threaten the persistence of rare and imperilled cyprinids such as pugnose shiner.

Adapting macroecology to microbiology: using occupancy modelling to assess functional profiles across metagenomes

Metagenomic sequencing provides information on the metabolic capacities and taxonomic affiliations for members of a microbial community. When assessing metabolic functions in a community, missing genes in pathways can occur in two ways: the genes may legitimately be missing from the community whose DNA was sequenced, or the genes were missed during shotgun sequencing or failed to assemble, and thus the metabolic capacity of interest is wrongly absent from the sequence data. Here, we borrow and adapt occupancy modelling from macroecology to provide mathematical context to metabolic predictions from metagenomes. We review the five assumptions underlying occupancy modelling through the lens of microbial community sequence data. Using the methane cycle, we apply occupancy modelling to examine the presence and absence of methanogenesis and methanotrophy genes from nearly 10,000 metagenomes spanning global environments. We determine that methanogenesis and methanotrophy are positively correlated across environments, and note that the lack of available standardized metadata for most metagenomes is a significant hindrance to large-scale statistical analyses. We present this adaptation of macroecology’s occupancy modelling to metagenomics as a tool for assessing presence/absence of traits in environmental microbiological surveys. We further initiate a call for stronger metadata standards to accompany metagenome deposition, to enable robust statistical approaches in the future.

Extent, configuration and diversity of burned and forested areas predict bat richness in a fire-maintained forest

Context Fire transforms, fragments and sometimes maintains forests, creating mosaics of burned and unburned patches. Highly mobile animals respond to resources in the landscape at a variety of spatial scales, yet we know little about their landscape-scale relationships with fire. Objectives We aimed to identify drivers of bat richness in a landscape mosaic of forested and burned areas while identifying spatial scales at which bat richness was most strongly related to extent, configuration, and diversity measures of landscape-level habitat. Methods We used multi-species hierarchical occupancy modelling to relate bat richness to landscape variables at 10 spatial scales, based on acoustic data collected in the Sierra Nevada, United States. We also assessed redundancy among landscape variable type (extent, configuration, and diversity) and between focal patch types (forested and burned). Results Bat richness was positively associated with heterogenous landscapes, shown by positive associations with pyrodiversity, extent and mean area of burned patches, burned and forested edge density and patch density and relationships were generally consistent across scales. Extent of forest cover and burned areas were highly correlated, but configuration and diversity of these patch types diverged. Conclusions Bat communities of our study area appear to be largely resilient to wildfire and adapted to more heterogenous forests and shorter-interval fire regimes that likely predominated before the fire suppression era.

Habitat Ecology and Analysis

Habitat is crucial to the survival and reproduction of individual organisms as well as persistence of populations. As such, species-habitat relationships have long been studied, particularly in the field of wildlife ecology and to a lesser extent in the more encompassing discipline of ecology. The habitat requirements of a species largely determine its spatial distribution and abundance in nature. One way to recognize and appreciate the over-riding importance of habitat is to consider that a young organism must find and settle into the appropriate type of habitat as one of the first challenges of life. This process can be cast in a probabilistic framework and used to better understand the mechanisms behind habitat preferences and selection. There are at least six distinctly different statistical approaches to conducting a habitat analysis – that is, identifying and quantifying the environmental variables that a species most strongly associates with. These are (1) comparison among group means (e.g., ANOVA), (2) multiple linear regression, (3) multiple logistic regression, (4) classification and regression trees, (5) multivariate techniques (Principal Components Analysis and Discriminant Function Analysis), and (6) occupancy modelling. Each of these is lucidly explained and demonstrated by application to a hypothetical dataset. The strengths and weaknesses of each method are discussed. Given the ongoing biodiversity crisis largely caused by habitat destruction, there is a crucial and general need to better characterize and understand the habitat requirements of many different species, particularly those that are threatened and endangered.