Complementary strengths of spatially-explicit and multi-species distribution models

Species distribution models (SDMs) project the outcome of community assembly processes – dispersal, the abiotic environment and biotic interactions – onto geographic space. Recent advances in SDMs account for these processes by simultaneously modeling the species that comprise a community in a multivariate statistical framework or by incorporating residual spatial autocorrelation in SDMs. However, the effects of combining both multivariate and spatially-explicit model structures on the ecological inferences and the predictive abilities of a model are largely unknown. We used data on eastern hemlock Tsuga canadensis and five additional co-occurring overstory tree species in 35 569 forest stands across Michigan, USA to evaluate how the choice of model structure, including spatial and non-spatial forms of univariate and multivariate models, affects ecological inference about the processes that shape community composition as well as model predictive ability. Incorporating residual spatial autocorrelation via spatial random effects did not improve out-of-sample prediction for the six tree species, although in-sample model fit was higher in the spatial models. Spatial models attributed less variation in occurrence probability to environmental covariates than the non-spatial models for all six tree species, and estimated higher (more positive) residual co-occurrence values for most species pairs. The non-spatial multivariate model was better suited for evaluating habitat suitability and hypotheses about the processes that shape community composition. Environmental correlations and residual correlations among species pairs were positively related, perhaps indicating that residual correlations were due to shared responses to unmeasured environmental covariates. This work highlights the importance of choosing a non-spatial model formulation to address research questions about the species–environment relationship or residual co-occurrence patterns, and a spatial model formulation when within-sample prediction accuracy is the main goal.     

Landscape structure shapes activity levels and composition of aerial insectivorous bats at different spatial scales

Biodiversity and Conservation - Tropical forests are being lost and modified at an unprecedented rate, with extant biodiversity increasingly restricted to human-modified landscapes. Resulting...     

Variation in the ratio of curli and phosphoethanolamine cellulose associated with biofilm architecture and properties

Bacterial biofilms are communities of bacteria entangled in a self‐produced extracellular matrix (ECM). Escherichia coli direct the assembly of two insoluble biopolymers, curli amyloid fibers, and phosphoethanolamine (pEtN) cellulose, to build remarkable biofilm architectures. Intense curiosity surrounds how bacteria harness these amyloid‐polysaccharide composites to build biofilms, and how these biopolymers function to benefit bacterial communities. Defining ECM composition involving insoluble polymeric assemblies poses unique challenges to analysis and, thus, to comparing strains with quantitative ECM molecular correlates. In this work, we present results from a sum‐of‐the‐parts ¹³C solid‐state nuclear magnetic resonance (NMR) analysis to define the curli‐to‐pEtN cellulose ratio in the isolated ECM of the E. coli laboratory K12 strain, AR3110. We compare and contrast the compositional analysis and comprehensive biofilm phenotypes for AR3110 and a well‐studied clinical isolate, UTI89. The ECM isolated from AR3110 contains approximately twice the amount of pEtN cellulose relative to curli content as UTI89, revealing plasticity in matrix assembly principles among strains. The two parent strains and a panel of relevant gene mutants were investigated in three biofilm models, examining: (a) macrocolonies on agar, (b) pellicles at the liquid‐air interface, and (c) biomass accumulation on plastic. We describe the influence of curli, cellulose, and the pEtN modification on biofilm phenotypes with power in the direct comparison of these strains. The results suggest that curli more strongly influence adhesion, while pEtN cellulose drives cohesion. Their individual and combined influence depends on both the biofilm modality (agar, pellicle, or plastic‐associated) and the strain itself.     

Valveless pumping behavior of the simulated embryonic heart tube as a function of contractile patterns and myocardial stiffness

Biomechanics and Modeling in Mechanobiology - During development, the heart begins pumping as a valveless multilayered tube capable of driving blood flow throughout the embryonic vasculature. The...     

Jackfruit trees as seed attractors and nurses of early recruitment of native plant species in a secondary forest in Brazil

The Atlantic Forest is one of the most threatened tropical forests in the world, being drastically reduced, fragmented, and disturbed. The drastic process of anthropic occupation and exploitation of this biome has, in many cases, led to the introduction of exotic species, such as the jackfruits (Artocarpus heterophyllus). However, studies on the influence of jackfruits on the native biota are still scarce. Here we investigated the influence of fruit trees on the seed rain and early recruitment of seedlings in native remnants, comparing these patterns with those observed for a native species tapirira (Tapirira guianensis), which similarly to jackfruits, produces many fruits throughout the year, attracting a variety of frugivore species. Seed rain and seedlings observed under the jackfruits were both more abundant and equally rich to the assemblages reported under the native tapirira trees. In both species, co-specifics comprise a large part of the number of seeds (>?70%) and seedlings (>?45%) individuals and, although they attract similar seed assemblages, seedling composition diverge, particularly when co-specifics are excluded. We reported that jackfruits can attract a diverse seed and seedling assemblages, and we find no evidence that the presence of jackfruits negatively affects the arrival and initial recruitment of native plant species in the study area. These results should be analyzed with caution but considered when evaluating costs and benefits of management options to control exotic species.