Random Forest characterization of upland vegetation and management burning from aerial imagery

Aim The upland moorlands of Great Britain form distinctive landscapes of international conservation importance, comprising mosaics of heathland, acid grassland, blanket bog and bracken. Much of this landscape is managed by rotational burning to create gamebird habitat and there is concern over whether this is driving long‐term changes in upland vegetation communities. However, the inaccessibility and scale of uplands means that monitoring changes in vegetation and burning practices is difficult. We aim to overcome this problem by developing methods to classify aerial imagery into high‐resolution maps of dominant vegetation cover, including the distribution of burns on managed grouse moors. Location  Peak District National Park, England, UK. Methods Colour and infrared aerial photographs were classified into seven dominant land‐cover classes using the Random Forest ensemble machine learning algorithm. In addition, heather (Calluna vulgaris) was further differentiated into growth phases, including sites that were newly burnt. We then analysed the distributions of the vegetation classes and managed burning using detrended correspondence analysis. Results Classification accuracy was c. 95% and produced a 5‐m resolution map for 514 km² of moorland. Cover classes were highly aggregated and strong nonlinear effects of elevation and slope and weaker effects of aspect and bedrock type were evident in structuring moorland vegetation communities. The classification revealed the spatial distribution of managed burning and suggested that relatively steep areas may be disproportionately burnt. Main conclusions Random Forest classification of aerial imagery is an efficient method for producing high‐resolution maps of upland vegetation. These may be used to monitor long‐term changes in vegetation and management burning and infer species–environment relationships and can therefore provide an important tool for effective conservation at the landscape scale.     

Regional effects as important determinants of local diversity in both marine and terrestrial systems

Community ecologists have struggled to create unified theories across diverse ecosystems, but it has been difficult to acertain whether marine and terrestrial communities differ in the mechanisms responsible for structure and dynamics. One apparent difference between marine and terrestrial ecology is that the influence of regional processes on local populations and communities is better established in the marine literature. We examine three potential explanations: 1) influential early studies emphasized local interactions in terrestrial communities and regional dispersal in marine communities. 2) regional‐scale processes are actually more important in marine than in terrestrial communities. 3) recruitment from a regional species pool is easier to study in marine than terrestrial communities. We conclude that these are interrelated, but that the second and especially the third explanations are more important than the first. We also conclude that in both marine and terrestrial systems, there are ways to improve our understanding of regional influences on local community diversity. In particular, we advocate examining local vs regional diversity relationships at localities within environmentally similar regions that differ in their diversity either because of their sizes or their varying degrees of isolation from a species source.     

Is regional species diversity bounded or unbounded?

Two conflicting hypotheses have been proposed to explain large‐scale species diversity patterns and dynamics. The unbounded hypothesis proposes that regional diversity depends only on time and diversification rate and increases without limit. The bounded hypothesis proposes that ecological constraints place upper limits on regional diversity and that diversity is usually close to its limit. Recent evidence from the fossil record, phylogenetic analysis, biogeography, and phenotypic disparity during lineage diversification suggests that diversity is constrained by ecological processes but that it is rarely asymptotic. Niche space is often unfilled or can be more finely subdivided and still permit coexistence, and new niche space is often created before ecological limits are reached. Damped increases in diversity over time are the prevalent pattern, suggesting the need for a new ‘damped increase hypothesis'. The damped increase hypothesis predicts that diversity generally increases through time but that its rate of increase is often slowed by ecological constraints. However, slowing due to niche limitation must be distinguished from other possible mechanisms creating similar patterns. These include sampling artifacts, the inability to detect extinctions or declines in clade diversity with some methods, the distorting effects of correlated speciation‐extinction dynamics, the likelihood that opportunities for allopatric speciation will vary in space and time, and the role of undetected natural enemies in reducing host ranges and thus slowing speciation rates. The taxonomic scope of regional diversity studies must be broadened to include all ecologically similar species so that ecological constraints may be accurately inferred. The damped increase hypothesis suggests that information on evolutionary processes such as time‐for‐speciation and intrinsic diversification rates as well as ecological factors will be required to explain why regional diversity varies among times, places and taxa.     

Phosphoinositide 3-kinase regulates plasma membrane targeting of the Ras-specific exchange factor RasGRP1

Receptor-induced targeting of exchange factors to specific cellular membranes is the predominant mechanism for initiating and compartmentalizing signal transduction by Ras GTPases. The exchange factor RasGRP1 has a C1 domain that binds the lipid diacylglycerol and thus can potentially mediate membrane localization in response to receptors that are coupled to diacylglycerol-generating phospholipase Cs. However, the C1 domain is insufficient for targeting RasGRP1 to the plasma membrane. We found that a basic/hydrophobic cluster of amino acids within the plasma membrane-targeting domain of RasGRP1 is instead responsible for plasma membrane targeting. This basic/hydrophobic cluster binds directly to phospholipid vesicles containing phosphoinositides via electrostatic interactions with polyanionic phosphoinositide headgroups and insertion of a tryptophan into the lipid bilayer. B cell antigen receptor ligation and other stimuli induce plasma membrane targeting of RasGRP1 by activating the phosphoinositide 3-kinase signaling pathway, which generates phosphoinositides within the plasma membrane. Direct detection of phosphoinositides by the basic/hydrophobic cluster of RasGRP1 provides a novel mechanism for coupling and co-compartmentalizing phosphoinositide 3-kinase and Ras signaling and, in coordination with diacylglycerol detection by the C1 domain, gives RasGRP1 the potential to serve as an integrator of converging signals from the phosphoinositide 3-kinase and phospholipase C pathways.     

A general mathematical framework for the analysis of spatiotemporal point processes

Spatial and stochastic models are often straightforward to simulate but difficult to analyze mathematically. Most of the mathematical methods available for nonlinear stochastic and spatial models are based on heuristic rather than mathematically justified assumptions, so that, e.g., the choice of the moment closure can be considered more of an art than a science. In this paper, we build on recent developments in specific branch of probability theory, Markov evolutions in the space of locally finite configurations, to develop a mathematically rigorous and practical framework that we expect to be widely applicable for theoretical ecology. In particular, we show how spatial moment equations of all orders can be systematically derived from the underlying individual-based assumptions. Further, as a new mathematical development, we go beyond mean-field theory by discussing how spatial moment equations can be perturbatively expanded around the mean-field model. While we have suggested such a perturbation expansion in our previous research, the present paper gives a rigorous mathematical justification. In addition to bringing mathematical rigor, the application of the mathematically well-established framework of Markov evolutions allows one to derive perturbation expansions in a transparent and systematic manner, which we hope will facilitate the application of the methods in theoretical ecology.     

A tethered bilayer sensor containing alamethicin channels and its detection of amiloride based inhibitors

Alamethicin, a small transmembrane peptide, inserts into a tethered bilayer membrane (tBLM) to form ion channels, which we have investigated using electrical impedance spectroscopy. The number of channels formed is dependent on the incubation time, concentration of the alamethicin and the application of DC voltage. The properties of the ion channels when formed in tethered bilayers are similar to those for such channels assembled into black lipid membranes (BLMs). Furthermore, amiloride and certain analogs can inhibit the channel pores, formed in the tBLMs. The potency and concentration of the inhibitors can be determined by measuring the change of impedance. Our work illustrates the possibility of using a synthetic tBLM for the study of small peptide voltage dependent ion channels. A potential application of such a device is as a screening tool in drug discovery processes.