Identifying core habitats and corridors for giant pandas by combining multiscale random forest and connectivity analysis

Habitat loss and fragmentation are widely acknowledged as the main driver of the decline of giant panda populations. The Chinese government has made great efforts to protect this charming species and has made remarkable achievements, such as population growth and habitat expansion. However, habitat fragmentation has not been reversed. Protecting giant pandas in a large spatial extent needs to identify core habitat patches and corridors connecting them. This study used an equal‐sampling multiscale random forest habitat model to predict a habitat suitability map for the giant panda. Then, we applied the resistant kernel method and factorial least‐cost path analysis to identify core habitats connected by panda dispersal and corridors among panda occurrences, respectively. Finally, we evaluated the effectiveness of current protected areas in representing core habitats and corridors. Our results showed high scale dependence of giant panda habitat selection. Giant pandas strongly respond to bamboo percentage and elevation at a relatively fine scale (1 km), whereas they respond to anthropogenic factors at a coarse scale (≥2 km). Dispersal ability has significant effects on core habitats extent and population fragmentation evaluation. Under medium and high dispersal ability scenarios (12,000 and 20,000 cost units), most giant panda habitats in the Qionglai mountain are predicted to be well connected by dispersal. The proportion of core habitats covered by protected areas varied between 38% and 43% under different dispersal ability scenarios, highlighting significant gaps in the protected area network. Similarly, only 43% of corridors that connect giant panda occurrences were protected. Our results can provide crucial information for conservation managers to develop wise strategies to safeguard the long‐term viability of the giant panda population.     

A Hybrid Approach for Assessing the Multi‐Scale Impacts of Urban Resource Use: Transportation in Phoenix,Arizona

Life cycle assessment (LCA) and urban metabolism (UM) are popular approaches for urban system environmental assessment. However, both approaches have challenges when used across spatial scales. LCA tends to decompose systemic information into micro‐level functional units that mask complexity and purpose, whereas UM typically equates aggregated material and energy flows with impacts and is not ideal for revealing the mechanisms or alternatives available to reduce systemic environmental risks. This study explores the value of integrating UM with LCA, using vehicle transportation in the Phoenix metropolitan area as an illustrative case study. Where other studies have focused on the use of LCA providing upstream supply‐chain impacts for UM, we assert that the broader value of the integrated approach is in (1) the ability to cross scales (from micro to macro) in environmental assessment and (2) establishing an analysis that captures function and complexity in urban systems. The results for Phoenix show the complexity in resource supply chains and critical infrastructure services, how impacts accrue well beyond geopolitical boundaries where activities occur, and potential system vulnerabilities.     

Scaling Theory: Application to Marine Ornithology

The problem of scale has three components: (a) direct measurement is usually confined to small areas and brief periods, (b) the most pressing issues occur at the scale of ecosystems and decades, but (c) direct scale-up fails when pattern and process at small scales differ from those at larger scales. Recognition of this dilemma has grown exponentially since around 1980. The problem of scale is particularly acute for seabirds, which inhabit one of the most extensive habitats on the planet—the surface of the ocean. The application of power laws is a promising solution to the problem. Power laws have a long empirical tradition, are readily estimated from data, and now have a theoretical basis. Power law behavior (with nonintegral exponents) appears in systems with episodically warring exponential rates. In marine ornithology, examples of areas where power laws can be applied include patchy spatial distributions, the association of predator with prey, the scaling of food intake to body size, and fractal habitat structure. Scaling theory and power laws are applicable to a wide variety of ecosystem phenomena and dynamics, including fluxes of material and energy. Received 7 May 2001; accepted 12 April 2002.     

Spatial Controls of Pre–Euro-American Wind and Fire Disturbance in Northern Wisconsin (USA) Forest Landscapes

We elucidate spatial controls of wind and fire disturbance across northern Wisconsin (USA), where climatic and topographic gradients are not strong, using data from the original US Public Land Survey (PLS) notes. These records contain information on the location and extent of heavy windthrows and stand-replacing fires prior to Euro-American settlement. The spatial patterns of windthrow and fire were spatially clustered at all scales in this historical environment, with stronger associations at local than regional scales. Logistic regression shows environmental variables to have a strong influence on this pattern. In the case of heavy windthrow, environmental drivers of disturbance pattern are fairly consistent across the region. The effects of climate and vegetation are predominant at all scales, but effects are often indirect, with strong interactions between them. Interactions between these two drivers and soil characteristics are also sometimes present. In contrast, models of stand-replacing fire show simple and direct control within and across fire-prone landscapes of historical northern Wisconsin, with climate and physiography as the main factors explaining the distribution of fire disturbance. This simple and direct control is lost at the regional scale, where climate, physiographic, soil, and vegetation variables, along with interactions between them, are significant factors. Contrary to other regions, the topographic effects are generally not important in predicting either wind or fire disturbance. Our work suggests that, in landscapes that lack strong environmental patterning, climate maintains its role as a primary driver of these natural disturbances, but topography is replaced by interactions and feedbacks with other forms of environmental heterogeneity.     

Integrating Structural Information to Study the Dynamics of Protein-Protein Interactions in Cells

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Multiscale modeling of cellular actin filaments: from atomistic molecular to coarse-grained dynamics

In this article, we present a computational multiscale model for the characterization of subcellular proteins. The model is encoded inside a simulation tool that builds coarse-grained (CG) force fields from atomistic simulations. Equilibrium molecular dynamics simulations on an all-atom model of the actin filament are performed. Then, using the statistical distribution of the distances between pairs of selected groups of atoms at the output of the MD simulations, the force field is parameterized using the Boltzmann inversion approach. This CG force field is further used to characterize the dynamics of the protein via Brownian dynamics simulations. This combination of methods into a single computational tool flow enables the simulation of actin filaments with length up to 400 nm, extending the time and length scales compared to state-of-the-art approaches. Moreover, the proposed multiscale modeling approach allows to investigate the relationship between atomistic structure and changes on the overall dynamics and mechanics of the filament and can be easily (i) extended to the characterization of other subcellular structures and (ii) used to investigate the cellular effects of molecular alterations due to pathological conditions.     

Exploring the multiscale signaling behavior of phototropin1 from Chlamydomonas reinhardtii using a full‐residue space kinetic Monte Carlo molecular dynamics technique

Devising analysis tools for elucidating the regulatory mechanism of complex enzymes has been a challenging task for many decades. It generally requires the determination of the structural‐dynamical information of protein solvent systems far from equilibrium over multiple length and time scales, which is still difficult both theoretically and experimentally. To cope with the problem, we introduce a full‐residue space multiscale simulation method based on a combination of the kinetic Monte Carlo and molecular dynamics techniques, in which the rates of the rate‐determining processes are evaluated from a biomolecular forcefield on the fly during the simulation run by taking into account the full space of residues. To demonstrate its reliability and efficiency, we explore the light‐induced functional behavior of the full‐length phototropin1 from Chlamydomonas reinhardtii (Cr‐phot1) and its various subdomains. Our results demonstrate that in the dark state the light oxygen voltage‐2‐Jα (LOV2‐Jα) photoswitch inhibits the enzymatic activity of the kinase, whereas the LOV1‐Jα photoswitch controls the dimerization with the LOV2 domain. This leads to the repulsion of the LOV1‐LOV2 linker out of the interface region between both LOV domains, which results in a positively charged surface suitable for cell–membrane interaction. By contrast, in the light state, we observe that the distance between both LOV domains is increased and the LOV1‐LOV2 linker forms a helix–turn–helix (HTH) motif, which enables gene control through nucleotide binding. Finally, we find that the kinase is activated through the disruption of the Jα‐helix from the LOV2 domain, which is followed by a stretching of the activation loop (A‐loop) and broadening of the catalytic cleft of the kinase. Proteins 2014; 82:2018–2040. © 2014 Wiley Periodicals, Inc.     

A multiscale approach to predicting affinity changes in protein–protein interfaces

Substitution mutations in protein–protein interfaces can have a substantial effect on binding, which has consequences in basic and applied biomedical research. Experimental expression, purification, and affinity determination of protein complexes is an expensive and time‐consuming means of evaluating the effect of mutations, making a fast and accurate in silico method highly desirable. When the structure of the wild‐type complex is known, it is possible to economically evaluate the effect of point mutations with knowledge based potentials, which do not model backbone flexibility, but these have been validated only for single mutants. Substitution mutations tend to induce local conformational rearrangements only. Accordingly, ZEMu (Zone Equilibration of Mutants) flexibilizes only a small region around the site of mutation, then computes its dynamics under a physics‐based force field. We validate with 1254 experimental mutants (with 1–15 simultaneous substitutions) in a wide variety of different protein environments (65 protein complexes), and obtain a significant improvement in the accuracy of predicted ΔΔG. Proteins 2014; 82:2681–2690. © 2014 Wiley Periodicals, Inc.