Do Community-Level Models Account for the Effects of Biotic Interactions? A Comparison of Community-Level and Species Distribution Modeling of Rocky Mountain Conifers

Community-level models (CLMs) aim to improve species distribution modeling (SDM) methods by attempting to explicitly incorporate the influences of interacting species. However, the ability of CLMs to appropriately account for biotic interactions is unclear. We applied CLM and SDM methods to predict the distributions of three dominant conifer tree species in the U.S. Rocky Mountains and compared CLM and SDM predictive accuracy as well as the ability of each approach to accurately reproduce species co-occurrence patterns. We specifically evaluated the performance of two statistical algorithms, MARS and CForest, within both CLM and SDM frameworks. Across all species, differences in SDM and CLM predictive accuracy were slight and can be attributed to differences in model structure rather than accounting for the effects of biotic interactions. In addition, CLMs generally over-predicted species cooccurrence, while SDMs under-predicted cooccurrence. Our results demonstrate no real improvement in the ability of CLMs to account for biotic interactions relative to SDMs. We conclude that alternative modeling approaches are needed in order to accurately account for the effects of biotic interactions on species distributions

plantTracker: An R Package to Translate Maps of Plant Occurrence Into Demographic Data

Long-term demographic data are rare yet invaluable for conservation, management, and basic research on the underlying mechanisms of population and community dynamics. Historical and contemporary mapped datasets of plant location and basal area present a relatively untapped source of demographic records that, in some cases, span over 20 years of sequential data collection. However, these maps do not uniquely mark individual plants, making the process of collecting growth, survival, and recruitment data difficult. Recent efforts to translate historical maps of plant occurrence into shapefiles make it possible to use computer algorithms to track individuals through time and determine individual growth and survival. We summarize the plantTracker R package, which contains user-friendly functions to extract neighbourhood density, growth, and survival data from repeatedly-sampled maps of plant location and basal area. These functions can be used with data derived from quadrat maps, aerial photography, and remote sensing, and while designed for use with perennial plants, can be applied to any repeatedly mapped sessile organism. This package contains two primary functions: trackSpp(), which tracks individuals through time and assigns demographic data, as well as getNeighbors(), which calculates both within and between-species neighbourhood occupancy around each mapped individual. plantTracker also contains functions to estimate plot-level recruitment, calculate plot-level population growth rate, and create quadrat maps. We tested the accuracy of the trackSpp() function on two spatial demographic datasets. The function was nearly perfect at assigning individual identities and survival status when tested on maps of tree basal area and perennial forb point locations. In both cases, the function correctly assigned survival and recruitment with 99% accuracy. These accurate and precise functions will expand the amount of data available to investigate demographic processes, which are fundamental drivers of population, community, and ecosystem processes

Landscape Features Affecting Northern Bobwhite Predator-Specific Nest Failures in Southeastern USA

Nest predation is a critical component in avian productivity and typically is the leading cause of nest failure for most birds. Several landscape features are thought to drive the behavioral interaction between northern bobwhite (Colinus virginianus; e.g., nest placement) and their predators (e.g., search methods for food acquisition). In order to understand habitat characteristics influencing predation, we studied bobwhite nests using 24-hour near-infrared video cameras. We monitored 675 bobwhite nests with cameras on 3 properties in northern Florida and southern Georgia, USA, during 2000–2006. To test the association between nest failures and specific failure causes with landscape structure, we calculated a suite of landscape metrics and examined these at 3 spatial scales (3.1 ha, 19.6 ha, and 50.3 ha). We found increased probability of nest success with greater proportions of, and proximity to, fallow and annually disked fields at larger scales (50.3 ha), but we found no landscape metrics to be important predictors of bobwhite nest failures at small scales (,20 ha). Fallow and disked fields may provide alternative prey items (e.g., rodents) important in buffering nest predation. Relative to meso-mammal predation, we observed increases in proportion of the landscape in field to be related to lower incidental nest failures at the smallest scale (3.1 ha). Nests closer to feed lines were more likely depredated by meso-mammals than ants at the 2 larger spatial scales. Interestingly, the fate of a nest was independent of the fate of neighboring nests, suggesting bobwhite nest predation may be primarily incidental

Landscape Features Affecting Northern Bobwhite Predator-Specific Nest Failures in Southeastern USA

Nest predation is a critical component in avian productivity and typically is the leading cause of nest failure for most birds. Several landscape features are thought to drive the behavioral interaction between northern bobwhite (Colinus virginianus; e.g., nest placement) and their predators (e.g., search methods for food acquisition). In order to understand habitat characteristics influencing predation, we studied bobwhite nests using 24-hour near-infrared video cameras. We monitored 675 bobwhite nests with cameras on 3 properties in northern Florida and southern Georgia, USA, during 2000–2006. To test the association between nest failures and specific failure causes with landscape structure, we calculated a suite of landscape metrics and examined these at 3 spatial scales (3.1 ha, 19.6 ha, and 50.3 ha). We found increased probability of nest success with greater proportions of, and proximity to, fallow and annually disked fields at larger scales (50.3 ha), but we found no landscape metrics to be important predictors of bobwhite nest failures at small scales (\u3c20 \u3eha). Fallow and disked fields may provide alternative prey items (e.g., rodents) important in buffering nest predation. Relative to meso-mammal predation, we observed increases in proportion of the landscape in field to be related to lower incidental nest failures at the smallest scale (3.1 ha). Nests closer to feed lines were more likely depredated by meso-mammals than ants at the 2 larger spatial scales. Interestingly, the fate of a nest was independent of the fate of neighboring nests, suggesting bobwhite nest predation may be primarily incidental

Microbiome Composition in Both Wild-Type and Disease Model Mice Is Heavily Influenced by Mouse Facility

Murine models have become essential tools for understanding the complex interactions between gut microbes, their hosts, and disease. While many intra-facility factors are known to influence the structure of mouse microbiomes, the contribution of inter-facility variation to mouse microbiome composition, especially in the context of disease, remains under-investigated. We replicated microbiome experiments using identical mouse lines housed in two separate animal facilities and report drastic differences in composition of microbiomes based upon animal facility of origin. We observed facility-specific microbiome signatures in the context of a disease model [the Ednrb (endothelin receptor type B) Hirschsprung disease mouse] and in normal C57BL/6J mice. Importantly, these facility differences were independent of cage, sex, or sequencing-related influence. In addition, we investigated the reproducibility of microbiome dysbiosis previously associated with Ednrb-/- (knock-out; KO) mice. While we observed genotype-based differences in composition between wild-type (WT) and KO mice, these differences were inconsistent with the previously reported conclusions. Furthermore, the genotype-based differences were not identical across animal facilities. Despite this, through differential abundance testing, we identified several conserved candidate taxa and candidate operational taxonomic units that may play a role in disease promotion or protection. Overall, our findings raise the possibility that previously reported microbiome-disease associations from murine studies conducted in a single facility may be heavily influenced by facility-specific effects. More generally, these results provide a strong rationale for replication of mouse microbiome studies at multiple facilities, and for the meticulous collection of metadata that will allow the confounding effects of facility to be more specifically identified

Body size and digestive system shape resource selection by ungulates : a cross-taxa test of the forage maturation hypothesis

The forage maturation hypothesis (FMH) states that energy intake for ungulates is maximised when forage biomass is at intermediate levels. Nevertheless, metabolic allometry and different digestive systems suggest that resource selection should vary across ungulate species. By combining GPS relocations with remotely sensed data on forage characteristics and surface water, we quantified the effect of body size and digestive system in determining movements of 30 populations of hindgut fermenters (equids) and ruminants across biomes. Selection for intermediate forage biomass was negatively related to body size, regardless of digestive system. Selection for proximity to surface water was stronger for equids relative to ruminants, regardless of body size. To be more generalisable, we suggest that the FMH explicitly incorporate contingencies in body size and digestive system, with small-bodied ruminants selecting more strongly for potential energy intake, and hindgut fermenters selecting more strongly for surface water.DATA AVAILABILITY STATEMENT : The dataset used in our analyses is available via Dryad repository (https://doi.org/10.5061/dryad.jsxksn09f) following a year-long embargo from publication of the manuscript. The coordinates associated with mountain zebra data are not provided in an effort to protect critically endangered black rhino (Diceros bicornis) locations. Interested researchers can contact the data owner (Minnesota Zoo) directly for inquiries.https://wileyonlinelibrary.com/journal/elehj2022Mammal Research InstituteZoology and Entomolog

salbeke/rKIN: v0.1.3 Release

In v0.1.3 I have added the input points to the estimating and plotting functions

Modeling Grassland Conversion: Challenges Of Using Satellite Imagery Data

The article focuses on the computational and empirical challenges of using satellite imagery data in modeling grassland conversion. It mentions that the U.S. temperate grasslands continue to face high conversion risk and empirical models to understand how to conserve grasslands are limited. It explains sampling strategies to reduce computational constraints in satellite imagery data

Global Vegetation Project: An Interactive Online Map of Open-Access Vegetation Photos

The Global Vegetation Project (http://gveg.wyobiodiversity.org) is a new initiative to host an online database of open-access, georeferenced vegetation photos. The mission of the Global Vegetation Project is ‘to inspire and empower people of all ages to learn about the diversity of vegetation on our planet and to provide educators with a resource for teaching ecology online’. The beta release includes two R-Shiny web applications that allow users to 1) submit photos of plant communities through a user-friendly online portal and 2) explore submissions made by others through an interactive global map. The spatial coordinates of each photo are used to extract information about the location including long-term and recent climate data to create Walter and Leith climate diagrams for each photo. User submitted photos can be filtered by biome, temperature, precipitation, and elevation on the map. The Global Vegetation Project will evolve to match the needs of vegetation scientists and ecology educators. We intend to enhance the educational value of the mapping application by incorporating additional search features, global data layers, and the publication of curricula geared towards primary, secondary, and post-secondary education. We encourage the global community of vegetation scientists to use this resource in their classrooms and to contribute photos of vegetation to grow this valuable resource for the world