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 - THES A1 - Maercklin, Nils T1 - Seismic structure of the Arava Fault, Dead Sea Transform N2 - Ein transversales Störungssystem im Nahen Osten, die Dead Sea Transform (DST), trennt die Arabische Platte von der Sinai-Mikroplatte und erstreckt sich von Süden nach Norden vom Extensionsgebiet im Roten Meer über das Tote Meer bis zur Taurus-Zagros Kollisionszone. Die sinistrale DST bildete sich im Miozän vor etwa 17 Ma und steht mit dem Aufbrechen des Afro-Arabischen Kontinents in Verbindung. Das Untersuchungsgebiet liegt im Arava Tal zwischen Totem und Rotem Meer, mittig über der Arava Störung (Arava Fault, AF), die hier den Hauptast der DST bildet. Eine Reihe seismischer Experimente, aufgebaut aus künstlichen Quellen, linearen Profilen über die Störung und entsprechend entworfenen Empfänger-Arrays, zeigt die Untergrundstruktur in der Umgebung der AF und der Verwerfungszone selbst bis in eine Tiefe von 3-4 km. Ein tomographisch bestimmtes Modell der seismischen Geschwindigkeiten von P-Wellen zeigt einen starken Kontrast nahe der AF mit niedrigeren Geschwindigkeiten auf der westlichen Seite als im Osten. Scherwellen lokaler Erdbeben liefern ein mittleres P-zu-S Geschwindigkeitsverhältnis und es gibt Anzeichen für Änderungen über die Störung hinweg. Hoch aufgelöste tomographische Geschwindigkeitsmodelle bestätigen der Verlauf der AF und stimmen gut mit der Oberflächengeologie überein. Modelle des elektrischen Widerstands aus magnetotellurischen Messungen im selben Gebiet zeigen eine leitfähige Schicht westlich der AF, schlecht leitendes Material östlich davon und einen starken Kontrast nahe der AF, die den Fluss von Fluiden von einer Seite zur anderen zu verhindern scheint. Die Korrelation seismischer Geschwindigkeiten und elektrischer Widerstände erlaubt eine Charakterisierung verschiedener Lithologien im Untergrund aus deren physikalischen Eigenschaften. Die westliche Seite lässt sich durch eine geschichtete Struktur beschreiben, wogegen die östliche Seite eher einheitlich erscheint. Die senkrechte Grenze zwischen den westlichen Einheiten und der östlichen scheint gegenüber der Oberflächenausprägung der AF nach Osten verschoben zu sein. Eine Modellierung von seismischen Reflexionen an einer Störung deutet an, dass die Grenze zwischen niedrigen und hohen Geschwindigkeiten eher scharf ist, sich aber durch eine raue Oberfläche auf der Längenskala einiger hundert Meter auszeichnen kann, was die Streuung seismischer Wellen begünstigte. Das verwendete Abbildungsverfahren (Migrationsverfahren) für seismische Streukörper basiert auf Array Beamforming und der Kohärenzanalyse P-zu-P gestreuter seismischer Phasen. Eine sorgfältige Bestimmung der Auflösung sichert zuverlässige Abbildungsergebnisse. Die niedrigen Geschwindigkeiten im Westen entsprechen der jungen sedimentären Füllung im Arava Tal, und die hohen Geschwindigkeiten stehen mit den dortigen präkambrischen Magmatiten in Verbindung. Eine 7 km lange Zone seismischer Streuung (Reflektor) ist gegenüber der an der Oberfläche sichtbaren AF um 1 km nach Osten verschoben und lässt sich im Tiefenbereich von 1 km bis 4 km abbilden. Dieser Reflektor markiert die Grenze zwischen zwei lithologischen Blöcken, die vermutlich wegen des horizontalen Versatzes entlang der DST nebeneinander zu liegen kamen. Diese Interpretation als lithologische Grenze wird durch die gemeinsame Auswertung der seismischen und magnetotellurischen Modelle gestützt. Die Grenze ist möglicherweise ein Ast der AF, der versetzt gegenüber des heutigen, aktiven Asts verläuft. Der Gesamtversatz der DST könnte räumlich und zeitlich auf diese beiden Äste und möglicherweise auch auf andere Störungen in dem Gebiet verteilt sein. N2 - The Dead Sea Transform (DST) is a prominent shear zone in the Middle East. It separates the Arabian plate from the Sinai microplate and stretches from the Red Sea rift in the south via the Dead Sea to the Taurus-Zagros collision zone in the north. Formed in the Miocene about 17 Ma ago and related to the breakup of the Afro-Arabian continent, the DST accommodates the left-lateral movement between the two plates. The study area is located in the Arava Valley between the Dead Sea and the Red Sea, centered across the Arava Fault (AF), which constitutes the major branch of the transform in this region. A set of seismic experiments comprising controlled sources, linear profiles across the fault, and specifically designed receiver arrays reveals the subsurface structure in the vicinity of the AF and of the fault zone itself down to about 3-4 km depth. A tomographically determined seismic P velocity model shows a pronounced velocity contrast near the fault with lower velocities on the western side than east of it. Additionally, S waves from local earthquakes provide an average P-to-S velocity ratio in the study area, and there are indications for a variations across the fault. High-resolution tomographic velocity sections and seismic reflection profiles confirm the surface trace of the AF, and observed features correlate well with fault-related geological observations. Coincident electrical resistivity sections from magnetotelluric measurements across the AF show a conductive layer west of the fault, resistive regions east of it, and a marked contrast near the trace of the AF, which seems to act as an impermeable barrier for fluid flow. The correlation of seismic velocities and electrical resistivities lead to a characterisation of subsurface lithologies from their physical properties. Whereas the western side of the fault is characterised by a layered structure, the eastern side is rather uniform. The vertical boundary between the western and the eastern units seems to be offset to the east of the AF surface trace. A modelling of fault-zone reflected waves indicates that the boundary between low and high velocities is possibly rather sharp but exhibits a rough surface on the length scale a few hundreds of metres. This gives rise to scattering of seismic waves at this boundary. The imaging (migration) method used is based on array beamforming and coherency analysis of P-to-P scattered seismic phases. Careful assessment of the resolution ensures reliable imaging results. The western low velocities correspond to the young sedimentary fill in the Arava Valley, and the high velocities in the east reflect mainly Precambrian igneous rocks. A 7 km long subvertical scattering zone reflector is offset about 1 km east of the AF surface trace and can be imaged from 1 km to about 4 km depth. The reflector marks the boundary between two lithological blocks juxtaposed most probably by displacement along the DST. This interpretation as a lithological boundary is supported by the combined seismic and magnetotelluric analysis. The boundary may be a strand of the AF, which is offset from the current, recently active surface trace. The total slip of the DST may be distributed spatially and in time over these two strands and possibly other faults in the area. KW - Arava-Störung KW - Totes Meer Störungssystem KW - Seitenverschiebung KW - Seismik KW - seismische Geschwindigkeit KW - Tomographie KW - Migration KW - Magnetotellurik KW - Arava Fault KW - Dead Sea Transform KW - strike-slip fault KW - seismics KW - seismic velocity KW - tomography KW - seismic imaging KW - migration KW - magnetotellurics Y1 - 2004 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-0001469 ER - TY - JOUR A1 - Kruse, Stefan A1 - Kolmogorov, Aleksey I. A1 - Pestryakova, Luidmila Agafyevna A1 - Herzschuh, Ulrike T1 - Long-lived larch clones may conserve adaptations that could restrict treeline migration in northern Siberia JF - Ecology and evolution N2 - The occurrence of refugia beyond the arctic treeline and genetic adaptation therein play a crucial role of largely unknown effect size. While refugia have potential for rapidly colonizing the tundra under global warming, the taxa may be maladapted to the new environmental conditions. Understanding the genetic composition and age of refugia is thus crucial for predicting any migration response. Here, we genotype 194 larch individuals from an similar to 1.8 km(2)area in northcentral Siberia on the southern Taimyr Peninsula by applying an assay of 16 nuclear microsatellite markers. For estimating the age of clonal individuals, we counted tree rings at sections along branches to establish a lateral growth rate that was then combined with geographic distance. Findings reveal that the predominant reproduction type is clonal (58.76%) by short distance spreading of ramets. One outlier of clones 1 km apart could have been dispersed by reindeer. In clonal groups and within individuals, we find that somatic mutations accumulate with geographic distance. Clonal groups of two or more individuals are observed. Clonal age estimates regularly suggest individuals as old as 2,200 years, which coincides with a major environmental change that forced a treeline retreat in the region. We conclude that individuals with clonal growth mode were naturally selected as it lowers the likely risk of extinction under a harsh environment. We discuss this legacy from the past that might now be a maladaptation and hinder expansion under currently strongly increasing temperatures. KW - adaptation KW - clonal growth KW - growth rate KW - Larix KW - leading edge KW - treeline KW - migration Y1 - 2020 U6 - https://doi.org/10.1002/ece3.6660 SN - 2045-7758 VL - 10 IS - 18 SP - 10017 EP - 10030 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Dalleau, Mayeul A1 - Kramer-Schadt, Stephanie A1 - Gangat, Yassine A1 - Bourjea, Jerome A1 - Lajoie, Gilles A1 - Grimm, Volker T1 - Modeling the emergence of migratory corridors and foraging hot spots of the green sea turtle JF - Ecology and evolution N2 - Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade‐offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual‐based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open‐source software, our model can coevolve with the collection and analysis of new data on energy budget and movement into a generic tool for sea turtle research and conservation. Our modeling approach could also be useful for supporting the conservation of other migratory marine animals. KW - connectivity KW - corridors KW - individual-based model KW - migration KW - movement KW - sea turtle Y1 - 2019 U6 - https://doi.org/10.1002/ece3.5552 SN - 2045-7758 VL - 9 IS - 18 SP - 10317 EP - 10342 PB - Wiley CY - Hoboken ER -