Climate Change or Land Use Dynamics: Do We Know What Climate Change Indicators Indicate?

Different components of global change can have interacting effects on biodiversity and this may influence our ability to detect the specific consequences of climate change through biodiversity indicators. Here, we analyze whether climate change indicators can be affected by land use dynamics that are not directly determined by climate change. To this aim, we analyzed three community-level indicators of climate change impacts that are based on the optimal thermal environment and average latitude of the distribution of bird species present at local communities. We used multiple regression models to relate the variation in climate change indicators to: i) environmental temperature; and ii) three landscape gradients reflecting important current land use change processes (land abandonment, fire impacts and urbanization), all of them having forest areas at their positive extremes. We found that, with few exceptions, landscape gradients determined the figures of climate change indicators as strongly as temperature. Bird communities in forest habitats had colder-dwelling bird species with more northern distributions than farmland, burnt or urban areas. Our results show that land use changes can reverse, hide or exacerbate our perception of climate change impacts when measured through community-level climate change indicators. We stress the need of an explicit incorporation of the interactions between climate change and land use dynamics to understand what are current climate change indicators indicating and be able to isolate real climate change impacts.     

Landscape Ideologies,Indigenous Governance,and Land Use Change in the Ecuadorian Amazon, 1960–1992

In recent years, states have ceded governance over large territories to indigenous organizations. This article examines the history of an early case of territorial governance (dating from the 1970s) to probe the social, political, and environmental processes that occur when an indigenous social movement becomes a governing body. It argues that indigenous organizations can quickly learn to “see like states” (Scott 1998) without adopting the particular visions promoted by the state that facilitated their new role. In the case explored here, indigenous leaders created landscape improvement schemes that went beyond those promoted by the state and others in terms of changing the legibility of land use and tenure categories. Furthermore, their schemes had significant impacts on forest cover as evidenced by remotely sensed images. These processes challenge theories that position the state as the primary arbitrator of human-environmental relations as well as theories that dichotomize between states and indigenous organizations.     

The Risk of Peat Erosion from Climate Change: Land Management Combinations—An Assessment with Bayesian Belief Networks

Modeling risk factors to soils is constrained by the lack of key data and understanding that explicitly and quantitatively link specific threats to risk. Peat erosion results from the complex interaction of climatic, topographic, and anthropogenic influences acting over a long period of time. With numerous contemporary factors operating to perpetuate the erosion processes, it is often difficult to identify with certainty what actually are the initial and subsequent drivers of erosion. In this situation, expert opinion forms a vital source of information. Here we demonstrate how Bayesian Belief Networks (BBN) can be used to combine quantitative data from the National Soils Inventory of Scotland (NSIS) with qualitative expert knowledge to estimate risk of peat erosion in Scotland. This model was used to identify the main factors associated with peat erosion. It was shown that climatic variables (increased temperature, decreased precipitation) are the most important risk factors for perpetuating peatland erosion. However, the BBN approach also indicated that maintaining good vegetation cover is a significant mitigating factor. It would follow that land management practices that impact negatively on vegetation cover would also exacerbate peatland erosion given a hot dry climate.     

Climate–ecosystem modelling made easy: The Land Sites Platform

Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.     

Northern Hemisphere Plant Disjunctions: A Window on Tertiary Land Bridges and Climate Change?

AIMS: This botanical briefing examines how molecular systematics has contributed to progress in understanding the history of Tertiary relict genera, i.e. those that that now occur disjunctly in parts of Eurasia and N America, and how progress in understanding Southern Hemisphere biogeography paradoxically makes unravelling Northern Hemisphere biogeography more complex. SCOPE: Tertiary relict floras comprise genera of warm wet climates that were once circumboreal in distribution but are now confined to E Asia, south-eastern and western N America, and SW Eurasia. The intercontinental disjunctions among these genera have long been believed to result from land connections between Eurasia and N America, across Beringia and the N Atlantic. This view is reassessed in the light of new evidence for long dispersal of propagules across oceans being responsible for many plant disjunctions involving southern continents. The impact of molecular dating, which has been very different in Southern and Northern Hemisphere biogeography, is discussed. CONCLUSIONS: For N America-Eurasia disjunctions involving Tertiary relict floras, land connections remain the more likely cause of disjunctions but data from fossils or infraspecific variation will be required to exclude long-dispersal explanations for disjunctions in any individual genus. Molecular dating of divergence between disjunctly distributed Tertiary relict floras can tell us which palaeoclimatic or palaeogeographic events impacted on them, and how, but only if migration over land and vicariance can be proved and molecular dating is sufficiently accurate.     

Evaluating Land Use Dynamics and Forest Cover Change in Nepal’s Bara District (1973–2003)

This research uses Landsat Multi-Spectral Scanner of 1973, Thematic Mapper of 1989, Advance Earth Observing Satellite of 1996, and Enhanced Thematic Mapper of 2003 imagery to examine the effects of socioeconomic and demographic factors on land use and forest cover dynamics in the Bara district of the Central Tarai Region of Nepal for 1973–2003. These satellite images are used to generate three transition matrices for 1973–1989, 1989–1996, and 1996–2003; and the outcomes of the final transition matrix are compared with the land use and cover patterns seen on the IKONOS (1 × 1 m) 2003 images. This paper contributes to our understanding of how land use and cover dynamics correspond to national-level socioeconomic developments, demographic changes, and environmental awareness as envisioned by Ecological Modernization Theory. It also demonstrates how such a set of transition matrices generated from different resolution images helps assess these explanatory relationships at different temporal and spatial scales.     

Vegetation–Climate Interactions among Native and Invasive Species in Hawaiian Rainforest

We compiled a time series of Earth Observing-1 Hyperion satellite observations with field measurements to compare the structural, biochemical, and physiological characteristics of an invasive nitrogen-fixing tree Myrica faya and native Metrosideros polymorpha in montane rainforests in Hawai’i. Satellite-based canopy water measurements closely tracked variations in leaf area index, and the remotely sensed photochemical and carotenoid reflectance indices (PRI, CRI) indicated variations in upper-canopy leaf chlorophyll and carotenoid content during a climatological transition. The PRI and CRI were related to differences in light-use efficiency of each species, as indicated by field measurements of leaf electron transport rate. The suite of hyperspectral metrics indicated maximum differences in the structure, biochemistry, and physiology of Myrica and Metrosideros when canopy vapor pressure deficit was high during hotter and drier periods. These satellite data, combined with the Carnegue-Ames-Stanford Approach (CASA) carbon cycle model, suggested that Myrica growth rates were 16–44% higher than Metrosideros, with relative differences between species closely linked to climate conditions. The satellite hyperspectral data identified the basic biological mechanisms favoring the spread of an introduced tree, and provided a more detailed understanding of how vegetation–climate interactions affect the time course of plant growth with respect to the invasion process.     

Post-Glacial Climate–Fire Interactions Control Tree Composition of Mesic Temperate Forests in Eastern North America

Stand-scale gap-phase dynamics is generally viewed as the main driver of development in mesic deciduous forests of the temperate biome. Soil charcoal of temperate forests in eastern North America are unnoticed in most surveys, thus explaining why fire is undervalued as a driver of forest succession. The extent to which gap-phase, fire, or other processes are responsible for the regeneration and maintenance of mesic deciduous forests is unknown because paleoecological evidence is lacking. We tested the fire-driven succession hypothesis on the development of this major forest type. Based on charcoal ¹⁴C dates of two sites, 44 and 55 fires occurred since early Holocene, with a mean interval of 170 to 215 years. The vegetation of both sites followed comparable post-glacial trajectories consisting of three distinct periods. Conifers dominated the two first periods during 5200–6000 years and were replaced by hardwoods–conifers over the last 3500 years. The first period was represented by boreal conifers, whereas the second period, dominated by white pine (Pinus strobus) forests, persisted during 3000–4300 years. The third period marked the development of hardwood (sugar maple, Acer saccharum) forests. Fires occurred continuously on the sites since early Holocene likely under dry conditions during the conifer periods and cooler and moister conditions during the hardwood–conifer period. Recurrent fires appear with climate as key drivers of the long-term dynamics of several temperate forests in eastern North America. Similar studies on other temperate forests should be pursued to test the hypothesis of climate–fire interactions influencing tree composition change.

     

Wild Laboratories of Climate Change: Plants,Phenology, and Global Warming, 1955–1980

Journal of the History of Biology - Phenologists track the seasonal behavior of plants and animals in response to climatic change. During the second half of the twentieth century, phenologists...     

Rearrangements of the Actin Cytoskeleton and E-Cadherin–Based Adherens Junctions Caused by Neoplasic Transformation Change Cell–Cell Interactions

E-cadherin–mediated cell–cell adhesion, which is essential for the maintenance of the architecture and integrity of epithelial tissues, is often lost during carcinoma progression. To better understand the nature of alterations of cell–cell interactions at the early stages of neoplastic evolution of epithelial cells, we examined the line of nontransformed IAR-2 epithelial cells and their descendants, lines of IAR-6-1 epithelial cells transformed with dimethylnitrosamine and IAR1170 cells transformed with N-RasG12D. IAR-6-1 and IAR1170 cells retained E-cadherin, displayed discoid or polygonal morphology, and formed monolayers similar to IAR-2 monolayer. Fluorescence staining, however, showed that in IAR1170 and IAR-6-1 cells the marginal actin bundle, which is typical of nontransformed IAR-2 cells, disappeared, and the continuous adhesion belt (tangential adherens junctions (AJs)) was replaced by radially oriented E-cadherin–based AJs. Time-lapse imaging of IAR-6-1 cells stably transfected with GFP-E-cadherin revealed that AJs in transformed cells are very dynamic and unstable. The regulation of AJ assembly by Rho family small GTPases was different in nontransformed and in transformed IAR epithelial cells. As our experiments with the ROCK inhibitor Y-27632 and the myosin II inhibitor blebbistatin have shown, the formation and maintenance of radial AJs critically depend on myosin II-mediated contractility. Using the RNAi technique for the depletion of mDia1 and loading cells with N17Rac, we established that mDia1 and Rac are involved in the assembly of tangential AJs in nontransformed epithelial cells but not in radial AJs in transformed cells. Neoplastic transformation changed cell–cell interactions, preventing contact paralysis after the establishment of cell–cell contact and promoting dynamic cell–cell adhesion and motile behavior of cells. It is suggested that the disappearance of the marginal actin bundle and rearrangements of AJs may change the adhesive function of E-cadherin and play an active role in migratory activity of carcinoma cells.     

Computational Prediction of Protein–Protein Interactions

Recently a number of computational approaches have been developed for the prediction of protein–protein interactions. Complete genome sequencing projects have provided the vast amount of information needed for these analyses. These methods utilize the structural, genomic, and biological context of proteins and genes in complete genomes to predict protein interaction networks and functional linkages between proteins. Given that experimental techniques remain expensive, time-consuming, and labor-intensive, these methods represent an important advance in proteomics. Some of these approaches utilize sequence data alone to predict interactions, while others combine multiple computational and experimental datasets to accurately build protein interaction maps for complete genomes. These methods represent a complementary approach to current high-throughput projects whose aim is to delineate protein interaction maps in complete genomes. We will describe a number of computational protocols for protein interaction prediction based on the structural, genomic, and biological context of proteins in complete genomes, and detail methods for protein interaction network visualization and analysis.     

Specificity of Intramembrane Protein–Lipid Interactions

Our concept of biological membranes has markedly changed, from the fluid mosaic model to the current model that lipids and proteins have the ability to separate into microdomains, differing in their protein and lipid compositions. Since the breakthrough in crystallizing membrane proteins, the most powerful method to define lipid-binding sites on proteins has been X-ray and electron crystallography. More recently, chemical biology approaches have been developed to analyze protein–lipid interactions. Such methods have the advantage of providing highly specific cellular probes. With the advent of novel tools to study functions of individual lipid species in membranes together with structural analysis and simulations at the atomistic resolution, a growing number of specific protein–lipid complexes are defined and their functions explored. In the present article, we discuss the various modes of intramembrane protein–lipid interactions in cellular membranes, including examples for both annular and nonannular bound lipids. Furthermore, we will discuss possible functional roles of such specific protein–lipid interactions as well as roles of lipids as chaperones in protein folding and transport.Our concept of biological membranes has markedly changed in the last two decades, from the fluid mosaic model (Singer and Nicolson 1972), in which the membrane was thought to be formed by a homogenous lipid fluid phase with proteins embedded, to the current model that lipids and proteins are not homogenously distributed, but have the ability to separate into microdomains, differing in their protein and lipid compositions. A well established example of domains are lipid rafts (see Box 1 for definitions). Raft domains are described as dynamic domain structures enriched in cholesterol, sphingolipids, and membrane proteins (Brown and London 1998; Simons and Ikonen 1997) that have an important role in different cellular processes (Lingwood and Simons 2010). Formation of domains within cellular membranes has been extensively investigated over the past years leading to various models that differ in the primary forces involved in the formation and the recruitment of surrounding membrane components into such domains.

BOX 1.

Definitions

Annular Lipids/Lipid Shell

An annular lipid shell is formed when selected lipid classes or molecular species bind preferentially to the hydrophobic and/or hydrophilic surfaces of a membrane protein. Per definition these lipids show markedly reduced residence times at the protein–lipid interface as compared to bulk lipids.

Bulk Lipids

Lipids within the membrane that diffuse rapidly in the bilayer plane and show a low residence time at the protein–lipid interface following random collisions. Typical diffusion coefficients for bulk lipids in a liquid disordered phase are in the range of D_L = 7×10⁻¹² m²/sec (DOPC) (Filippov et al. 2003).

Hydrophobic Mismatch

A term to describe any deviation from the compatibility of the hydrophobic surface of membrane proteins (their TMDs) to the vertically and laterally encountered hydrophobic surfaces of the lipid bilayer in biological membranes. In the case of a hydrophobic mismatch, the resulting energy penalty may cause the recruitment of a suitable local lipid environment, the deformation of the membrane and/or in conformational changes of the protein to achieve a status of hydrophobic match (for advanced reading, see Killian 1998).

Lateral Pressure Field/Profile of Membranes

Biological membranes can be considered as the “solvent” for membrane proteins that are embedded in them. The lateral pressure profile (Ω(z)) describes the force or pressure that is exerted by the membrane on the matter residing inside it. This pressure is modulated by different extents of lipid–lipid interactions and asymmetries across and within the bilayer, which in turn results in varying lateral pressures that may locally correspond to several hundreds of atmospheres.

Lipid Rafts

Sterol and sphingolipid-dependent microdomains that form a network of lipid–lipid, protein–protein, and protein–lipid interactions; involved in the compartmentalization of processes such as signaling within biological membranes.

Liquid-Disordered Phase (I_d)

A predominantly fluid phase of lipids, characterized by a high degree of mobility (cis-gauche flexibility of acyl chains; lateral diffusion) and a high content of short and/or unsaturated fatty acyl chains.

Liquid-Ordered Phase (I_o)

A liquid crystalline phase (that displays physical properties of both liquids and of solid crystals), characterized by a high degree of acyl chain order (“packing”), a reduced lateral mobility of lipid and protein molecules, and a reduction in the elasticity of the membrane as a result of specific interactions between sterols and phospholipids containing long, saturated acyl chains and/or glycosphingolipids.

Microdomains

Membrane compartments of distinct lipid and protein composition that may modulate the enzymatic functions of membrane proteins.

Molecular Lipid Species

Individual members of a lipid class that differ in their fatty acid composition.

Nonannular Lipids

Lipids that specifically interact with membrane proteins are neither bulk lipids, nor do they belong to the shell/annulus of lipids that surround the membrane protein. These nonannular lipids often reside within membrane protein complexes, in which they may fulfill diverse functions ranging from structural building blocks to allosteric effectors of enzymatic activity (see text). Nonannular lipids bind to distinct hydrophobic sites of membrane proteins or membrane protein complexes.According to one model, membrane domains can form by specific protein–protein interactions (Douglass and Vale 2005). This model is based on single-molecule microscopy experiments. In these studies, single fluorophores were chemically attached to specific proteins, and the dynamics of individual proteins was tracked by monitoring the fluorescent probe. In this kind of set up, a dynamic behavior of lipids is not assessed. Here, proteins involved in signaling processes are trapped within interconnected microdomains created by specific protein–protein interactions, probably involving additional scaffolding proteins. The proteins of such domains can exchange with the surrounding membrane area at individual kinetics, some components are immobile over minutes, and others can diffuse rapidly.Another model emphasizes the importance of lipid–lipid interactions, initiating the formation of subdomains of defined lipid compositions. Transmembrane proteins then can be attracted to such subdomains via various specific interactions with lipids. The resulting lipid–protein complexes then eventually coalesce to form larger lipid–protein assemblies (Anderson and Jacobson 2002).The idea of lipid-dependent domain formation is inherent to the biophysical properties and therefore to the complex lipid composition of cellular membranes that include up to a thousand lipids that vary in structure (van Meer et al. 2008). This wide range of lipid species has been proposed to facilitate the “solvation” of membrane proteins. Taken into account the sum of lipid species present in a cellular membrane, it is important to understand the different interactions and affinities within the bilayer between different lipids. Molecular dynamics simulations have been successfully employed to investigate lipid interactions between different lipid species and found specific interactions of various lipid classes and molecular species (Hofsass et al. 2003; Niemela et al. 2004, 2006, 2009; Pandit et al. 2004; Zaraiskaya and Jeffrey 2005; Bhide et al. 2007). These results are supported and expanded by recent data from our group that suggest a specific order of interactions of sphingomyelin species with cholesterol in membranes (A.M. Ernst, F. Wieland, and B. Brügger, unpubl.). At low cholesterol concentrations, some sphingomyelin species preferentially interact with cholesterol, whereas others prefer their kin. At higher cholesterol concentrations, all sphingomyelin species investigated display an increased affinity for the sterol. These findings open the possibility of differentiated pathways of self-assembly of microdomains, dependent on molecular lipid species.In the present article the various modes of intramembrane protein–lipid interactions in cellular membranes (Fig. 1) will be discussed. This includes possible functional roles of such specific protein–lipid interactions.Open in a separate windowFigure 1.Intramembrane protein–lipid interactions within a cell membrane. (A) Bulk lipids; (B) annular lipids; (C) nonannular lipids/lipid ligands. For details see text.     

A Critical Assessment of Information-guided Protein–Protein Docking Predictions

The structures of protein complexes are increasingly predicted via protein–protein docking (PPD) using ambiguous interaction data to help guide the docking. These data often are incomplete and contain errors and therefore could lead to incorrect docking predictions. In this study, we performed a series of PPD simulations to examine the effects of incompletely and incorrectly assigned interface residues on the success rate of PPD predictions. The results for a widely used PPD benchmark dataset obtained using a new interface information-driven PPD (IPPD) method developed in this work showed that the success rate for an acceptable top-ranked model varied, depending on the information content used, from as high as 95% when contact relationships (though not contact distances) were known for all residues to 78% when only the interface/non-interface state of the residues was known. However, the success rates decreased rapidly to ∼40% when the interface/non-interface state of 20% of the residues was assigned incorrectly, and to less than 5% for a 40% incorrect assignment. Comparisons with results obtained by re-ranking a global search and with those reported for other data-guided PPD methods showed that, in general, IPPD performed better than re-ranking when the information used was more complete and more accurate, but worse when it was not, and that when using bioinformatics-predicted information on interface residues, IPPD and other data-guided PPD methods performed poorly, at a level similar to simulations with a 40% incorrect assignment. These results provide guidelines for using information about interface residues to improve PPD predictions and reveal a bottleneck for such improvement imposed by the low accuracy of current bioinformatic interface residue predictions.Proteins work in close association with other proteins to mediate the intricate functions of a cell. The atomic resolution of the structure of a protein complex can therefore help one understand a protein''s function in detail. Protein–protein docking (PPD),¹ a computational approach that complements experimental structure determinations, has attracted increasing research interest (1, 2), in part because it remains challenging to determine most structures of protein complexes via experimental techniques (3).To improve the performance of PPD predictions, experimentally derived data (e.g. distances) and information (e.g. the identity of interface residues) have been used either as a filter allowing less plausible docking solutions to be disregarded (4–9) or as a constraint to guide the docking process (10, 11). Various types of data and information have been used to aid PPD (12); these range from distances between, or the relative orientation of, the two interacting proteins to simple identification of the amino acid residues directly involved in the binding of the two proteins (13). Despite considerable success, the caveat for all these data-guided PPD predictions is that the data or information used must be correct in order to avoid spurious results caused by misguiding (12). It is therefore pertinent and important to evaluate the effects of errors in the incorporated data or information on the quality of PPD solutions.We have recently shown that the use of just a few distance constraints can improve the success rates of PPD such that they rival, or are even better than, those of a global search ranked using a sophisticated energy function, and that errors in the distance data significantly decrease the success rates of prediction (11). However, because distance data for interacting proteins are usually hard to obtain, other types of data or information, even if “ambiguous” (10), are increasingly used in PPD predictions (12, 14). In this study, we investigated the effects of incompletely and incorrectly assigned interface/non-interface residues, a major source of the so-called ambiguous data, on information-guided PPD predictions.As illustrated in Fig. 1, the information content of interface/non-interface residues can be rich enough to reveal the identity of every pair of residues in contact, but not their contact distances, or so poor as to reveal the interface/non-interface state of these residues but not their pairing relationship, for one or both of the two interacting proteins. To determine how these different levels of residue information content can help PPD predictions and the extent to which the use of incorrectly assigned residues degrades prediction success rates, we have developed a new interface information-driven PPD method (IPPD) and carried out a series of PPD simulations on a well-tested benchmark dataset. The results showed that when the information content was rich, excellent predictions (success rates for producing an acceptable top-ranked model > 70%) could be made via IPPD or by re-ranking a global search''s solutions using the same interface information, and that, encouragingly, the success of predictions remained respectable (top-ranked success rates > 15%) when the content was poor. However, when enough of the interface residues were incorrectly assigned, as would be the case when using interface residues predicted by a state-of-the-art bioinformatics method such as CPORT (15), few models ranked first by IPPD or other PPD methods, including HADDOCK (10), a popular ambiguous data-driven PPD method, came close to being acceptable. These results suggest that we can greatly increase the power of PPD predictions for practical applications only if the accuracy of current bioinformatics methods for predicting the interface residues of protein complexes can be significantly improved.Open in a separate windowFig. 1.Contact matrix of two interacting proteins, A and B, and the contact vectors of their residues. In the contact matrix, M_ij = 1 or 0, respectively, denotes contact or a lack of contact between residue i in protein A and residue j in protein B. In the contact vectors, V_Ai = 1 or 0, respectively, when residue Ai has, or does not have, at least one contact with any residue of protein B.     

GIS and the ‘Usual Suspects’-[Mis]understanding Land Use Change in Cambodia

GIS-RS techniques offer great potential for providing insights into the spatiality and temporality of the messy realties of deforestation. However, rather than positing that the land use maps produced using these novel technologies can cut through politics, it is argued that the map is merely an artifact of the broader process of land use planning which is constitutive of politics. This article critically reflects on a major land use mapping exercise that the two authors were involved with, in central Cambodia. It argues that GIS analysts need to go beyond merely a concern for ‘the local’, and have their own ‘honest’ teleologies that can navigate the complexities of environmental politics. This article shows how particular categorizations of land use that the analyst creates in accordance with their own desires and the technical limitations of GIS, are often bound up in techniques of government.