TY - JOUR A1 - Sachse, Dirk A1 - Billault, Isabelle A1 - Bowen, Gabriel J. A1 - Chikaraishi, Yoshito A1 - Dawson, Todd E. A1 - Feakins, Sarah J. A1 - Freeman, Katherine H. A1 - Magill, Clayton R. A1 - McInerney, Francesca A. A1 - van der Meer, Marcel T. J. A1 - Polissar, Pratigya A1 - Robins, Richard J. A1 - Sachs, Julian P. A1 - Schmidt, Hanns-Ludwig A1 - Sessions, Alex L. A1 - White, James W. C. A1 - West, Jason B. A1 - Kahmen, Ansgar ED - Jeanloz, R T1 - Molecular Paleohydrology interpreting the Hydrogen- Isotopic Composition of Lipid Biomarkers from Photosynthesizing Organisms JF - Annual review of earth and planetary sciences JF - Annual Review of Earth and Planetary Sciences N2 - Hydrogen-isotopic abundances of lipid biomarkers are emerging as important proxies in the study of ancient environments and ecosystems. A decade ago, pioneering studies made use of new analytical methods and demonstrated that the hydrogen-isotopic composition of individual lipids from aquatic and terrestrial organisms can be related to the composition of their growth (i.e., environmental) water. Subsequently, compound-specific deuterium/hydrogen (D/H) ratios of sedimentary biomarkers have been increasingly used as paleohydrological proxies over a range of geological timescales. Isotopic fractionation observed between hydrogen in environmental water and hydrogen in lipids, however, is sensitive to biochemical, physiological, and environmental influences on the composition of hydrogen available for biosynthesis in cells. Here we review the factors and processes that are known to influence the hydrogen-isotopic compositions of lipids-especially n-alkanes-from photosynthesizing organisms, and we provide a framework for interpreting their D/H ratios from ancient sediments and identify future research opportunities. KW - paleoclimate KW - paleoclimate proxy KW - deuterium KW - organic geochemistry Y1 - 2012 SN - 978-0-8243-2040-9 U6 - https://doi.org/10.1146/annurev-earth-042711-105535 SN - 0084-6597 VL - 40 IS - 1 SP - 221 EP - 249 PB - Annual Reviews CY - Palo Alto ER - TY - JOUR A1 - Sommer, Ulrich A1 - Adrian, Rita A1 - Domis, Lisette Nicole de Senerpont A1 - Elser, James J. A1 - Gaedke, Ursula A1 - Ibelings, Bas A1 - Jeppesen, Erik A1 - Lurling, Miquel A1 - Molinero, Juan Carlos A1 - Mooij, Wolf M. A1 - van Donk, Ellen A1 - Winder, Monika ED - Futuyma, DJ T1 - Beyond the Plankton Ecology Group (PEG) Model mechanisms driving plankton succession JF - Annual review of ecology, evolution, and systematics JF - Annual Review of Ecology Evolution and Systematics N2 - The seasonal succession of plankton is an annually repeated process of community assembly during which all major external factors and internal interactions shaping communities can be studied. A quarter of a century ago, the state of this understanding was described by the verbal plankton ecology group (PEG) model. It emphasized the role of physical factors, grazing and nutrient limitation for phytoplankton, and the role of food limitation and fish predation for zooplankton. Although originally targeted at lake ecosystems, it was also adopted by marine plankton ecologists. Since then, a suite of ecological interactions previously underestimated in importance have become research foci: overwintering of key organisms, the microbial food web, parasitism, and food quality as a limiting factor and an extended role of higher order predators. A review of the impact of these novel interactions on plankton seasonal succession reveals limited effects on gross seasonal biomass patterns, but strong effects on species replacements. KW - lakes KW - oceans KW - seasonal patterns KW - pelagic zone KW - light KW - overwintering KW - grazing KW - parasitism KW - food quality Y1 - 2012 SN - 978-0-8243-1443-9 U6 - https://doi.org/10.1146/annurev-ecolsys-110411-160251 SN - 1543-592X VL - 43 IS - 2-4 SP - 429 EP - 448 PB - Annual Reviews CY - Palo Alto ER - TY - JOUR A1 - Schneider, Anne-Kathrin A1 - Schröder-Esselbach, Boris T1 - Perspectives in modelling earthworm dynamics and their feedbacks with abiotic soil properties JF - Applied soil ecology : a section of agriculture, ecosystems & environment N2 - Effects of earthworms on soil abiotic properties are well documented from several decades of laboratory and mesocosm experiments, and they are supposed to affect large-scale soil ecosystem functioning. The prediction of the spatiotemporal occurrence of earthworms and the related functional effects in the field or at larger scales, however, is constrained by adequate modelling approaches. Correlative, phenomenological methods, such as species distribution models, facilitate the identification of factors that drive species' distributions. However, these methods ignore the ability of earthworms to select and modify their own habitat and therefore may lead to unreliable predictions. Understanding these feedbacks between earthworms and abiotic soil properties is a key requisite to better understand their spatiotemporal distribution as well as to quantify the various functional effects of earthworms in soil ecosystems. Process-based models that investigate either effects or responses of earthworms on soil environmental conditions are mostly applied in ecotoxicological and bioturbation studies. Process-based models that describe feedbacks between earthworms and soil abiotic properties explicitly are rare. In this review, we analysed 18 process-based earthworm dynamic modelling studies pointing out the current gaps and future challenges in feedback modelling. We identify three main challenges: (i) adequate and reliable process identification in model development at and across relevant spatiotemporal scales (individual behaviour and population dynamics of earthworms), (ii) use of information from different data sources in one model (laboratory or field experiments, earthworm species or functional type) and (iii) quantification of uncertainties in data (e.g. spatiotemporal variability of earthworm abundances and soil hydraulic properties) and derived parameters (e.g. population growth rate and hydraulic conductivity) that are used in the model. KW - Oligochaeta KW - Feedback biotic-abiotic KW - Functional effect KW - Population dynamics KW - Modeling KW - Ecosystem engineer Y1 - 2012 U6 - https://doi.org/10.1016/j.apsoil.2012.02.020 SN - 0929-1393 VL - 58 IS - 1 SP - 29 EP - 36 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kirby, Eric A1 - Whipple, Kelin X. T1 - Expression of active tectonics in erosional landscapes JF - Journal of structural geology N2 - Understanding the manner and degree to which topography in active mountain ranges reflects deformation of the Earth's surface remains a first order goal of tectonic geomorphology. A substantial body of research in the past decade demonstrates that incising channel systems play a central role in setting relationships among topographic relief, differential rock uplift rate, and climatically modulated erosional efficiency. This review provides an introduction to the analysis and interpretation of channel profiles in erosional mountain ranges. We show that existing data support theoretical expectations of positive, monotonic relationships between channel steepness index, a measure of channel gradient normalized for downstream increases in drainage area, and erosion rate at equilibrium, and that the transient response to perturbations away from equilibrium engenders specific spatial patterns in channel profiles that can be used to infer aspects of the forcing. These aspects of channel behavior lay the foundation for a series of case studies that we use to illustrate how focused, quantitative analysis of channel morphology can provide insight into the spatial and temporal dynamics of active deformation. Although the complexities of river response to climate, lithology, and uplift patterns mean that multiple interpretations of topographic data alone will always possible, we show that application of stream profile analysis can be a powerful reconnaissance tool with which to interrogate the rates and patterns of deformation in active mountain belts. KW - Tectonic geomorphology KW - Active tectonics KW - River profiles KW - Neotectonics Y1 - 2012 U6 - https://doi.org/10.1016/j.jsg.2012.07.009 SN - 0191-8141 VL - 44 SP - 54 EP - 75 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Schurr, Frank Martin A1 - Pagel, Jörn A1 - Sarmento, Juliano Sarmento A1 - Groeneveld, Juergen A1 - Bykova, Olga A1 - O'Hara, Robert B. A1 - Hartig, Florian A1 - Kissling, W. Daniel A1 - Linder, H. Peter A1 - Midgley, Guy F. A1 - Schröder-Esselbach, Boris A1 - Singer, Alexander A1 - Zimmermann, Niklaus E. T1 - How to understand species' niches and range dynamics: a demographic research agenda for biogeography JF - Journal of biogeography N2 - Range dynamics causes mismatches between a species geographical distribution and the set of suitable environments in which population growth is positive (the Hutchinsonian niche). This is because sourcesink population dynamics cause species to occupy unsuitable environments, and because environmental change creates non-equilibrium situations in which species may be absent from suitable environments (due to migration limitation) or present in unsuitable environments that were previously suitable (due to time-delayed extinction). Because correlative species distribution models do not account for these processes, they are likely to produce biased niche estimates and biased forecasts of future range dynamics. Recently developed dynamic range models (DRMs) overcome this problem: they statistically estimate both range dynamics and the underlying environmental response of demographic rates from species distribution data. This process-based statistical approach qualitatively advances biogeographical analyses. Yet, the application of DRMs to a broad range of species and study systems requires substantial research efforts in statistical modelling, empirical data collection and ecological theory. Here we review current and potential contributions of these fields to a demographic understanding of niches and range dynamics. Our review serves to formulate a demographic research agenda that entails: (1) advances in incorporating process-based models of demographic responses and range dynamics into a statistical framework, (2) systematic collection of data on temporal changes in distribution and abundance and on the response of demographic rates to environmental variation, and (3) improved theoretical understanding of the scaling of demographic rates and the dynamics of spatially coupled populations. This demographic research agenda is challenging but necessary for improved comprehension and quantification of niches and range dynamics. It also forms the basis for understanding how niches and range dynamics are shaped by evolutionary dynamics and biotic interactions. Ultimately, the demographic research agenda should lead to deeper integration of biogeography with empirical and theoretical ecology. KW - Biodiversity monitoring KW - climate change KW - ecological forecasts KW - ecological niche modelling KW - ecological theory KW - geographical range shifts KW - global environmental change KW - mechanistic models KW - migration KW - process-based statistics Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2012.02737.x SN - 0305-0270 VL - 39 IS - 12 SP - 2146 EP - 2162 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Dormann, Carsten F. A1 - Schymanski, Stanislaus J. A1 - Cabral, Juliano Sarmento A1 - Chuine, Isabelle A1 - Graham, Catherine A1 - Hartig, Florian A1 - Kearney, Michael A1 - Morin, Xavier A1 - Römermann, Christine A1 - Schröder-Esselbach, Boris A1 - Singer, Alexander T1 - Correlation and process in species distribution models: bridging a dichotomy JF - Journal of biogeography N2 - Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions. KW - Hypothesis generation KW - mechanistic model KW - parameterization KW - process-based model KW - species distribution model KW - SDM KW - uncertainty KW - validation Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-2699.2011.02659.x SN - 0305-0270 VL - 39 IS - 12 SP - 2119 EP - 2131 PB - Wiley-Blackwell CY - Hoboken ER -