Biology subjects

Ryser, R.

Publications and source records attributed to Ryser, R..

5 recordsLinked to original sources

bioRxiv2025

MacroMove: a global database of animal movement across taxa and movement types

Animal movement is a key ecological process that shapes species distributions and interactions and connects resources, populations and habitats, underpinning ecosystem functioning and stability. While foraging, dispersal, and migration are the most widely studied movement types, they operate at distinct spatial and temporal scales, and no single resource currently integrates these processes across taxa, traits, and ecosystems. We present MacroMove, a comprehensive global movement database containing 92,207 observations from 4,329 (4,167 using GBIF backbone) species, spanning 36 classes and 648 families across 205 countries, with data sourced from 6,234 references and 36 meta-analyses/databases. It includes both vertebrates and invertebrates from terrestrial, freshwater, and marine environments. The database includes various movement metrics - home range area, dispersal distance, migration distance, day range, routine speed and maximum speed - including summary statistics (e.g. mean, median, maximum) where available. Records are reported at individual, population, or species levels and include standardised metadata describing species identity (binomial name, class, family), research methods (e.g. sampling method, sampling level and sampling dates) and location (e.g. country, location and coordinates). The dataset was assembled from published meta-analyses/databases and original studies included in these meta-analyses. Trait information (body mass and locomotion mode) from original studies and associated metadata was incorporated, with additional data sourced from established trait databases and reputable online resources. In the final dataset, body mass is available for 98 % and locomotion for 100% of species. Taxonomy was harmonised using the Global Biodiversity Information Facility (GBIF) backbone taxonomy. The database is supplied in comma-delimited text (.csv) format to maximise accessibility and compatibility with a wide range of workflows. By consolidating existing movement data into a single, standardised and openly accessible resource, MacroMove fills a major gap in available biodiversity data. It serves as a practical and extensible foundation for synthesising movement information across taxa and ecosystems, advancing data-driven research on the ecological and evolutionary correlates of animal movement.

ecology↗

bioRxiv2023

Understanding interactions in a complex world: Design and analysis of multi-species functional response experiments

O_LIThe functional response describes feeding rates of consumers as a function of resource density. While models for feeding on a single resource species are well studied and supported by a large body of empirical research, consumers feeding on multiple resource species are ubiquitous in nature. However, laboratory experiments designed for parameterizing multi-species functional responses (MSFR) are extremely rare, mainly due to logistical challenges and the non-trivial nature of their statistical analysis. C_LIO_LIHere, we describe how these models can be fitted to empirical data in a Bayesian framework. Specifically, we address the problem of prey depletion during experiments, which can be accounted for through dynamical modeling. In a comprehensive simulation study, we test the effects of experimental design, sample size and noise level on the identifiability of four distinct MSFR models. Additionally, we demonstrate the methods versatility by applying it to a list of empirical datasets. C_LIO_LIWe identify experimental designs for feeding trials that produce the most accurate parameter estimates in two- and three-prey scenarios. Although noise introduces systematic bias in parameter estimates, model selection performs surprisingly well for the four MSFRs, almost always identifying the correct model even for small datasets. C_LIO_LIThis flexible framework allows the simultaneous analysis of feeding experiments from both single- and multi-prey scenarios, either with or without prey depletion. This will help to elucidate mechanisms such as prey selectivity, prey switching and their implications for food web stability and biodiversity. Our approach equips researchers with the appropriate statistical tools to improve the understanding of feeding interactions in complex ecosystems. C_LI

ecology↗

bioRxiv2020

Landscape heterogeneity buffers biodiversity of meta-food-webs under global change through rescue and drainage effects

The impacts of habitat fragmentation and eutrophication on biodiversity have been studied in different scientific realms. Metacommunity research1-5 has shown that reduction in landscape connectivity may cause biodiversity loss in fragmentated landscapes. Food-web research addressed how eutrophication increases biomass accumulations at high trophic levels causing the breakdown of local biodiversity 6-9. However, there is very limited understanding of their cumulative impacts as they could amplify or cancel each other. Here, we show with simulations of meta-food-webs that landscape heterogeneity provides a buffering capacity against increasing nutrient eutrophication. An interaction between eutrophication and landscape homogenization precipitates the decline of biodiversity. We attribute our results to two complementary mechanisms related to source and sink dynamics. First, the "rescue effect" maintains local biodiversity by rapid recolonization after a local crash in population densities. Second, the "drainage effect" allows a more uniform spreading of biomass across the landscape, reducing overall interaction strengths and therefore stabilizing dynamics. In complex food webs on large spatial networks of habitat patches, these effects yield systematically higher biodiversity in heterogeneous than in homogeneous landscapes. Our meta-food-web approach reveals a strong interaction between habitat fragmentation and eutrophication and provides a mechanistic explanation of how landscape heterogeneity promotes biodiversity.

ecology↗

bioRxiv2019

Mismatch of the morphology model is mostly unproblematic in total-evidence dating: insights from an extensive simulation study

Calibrating the molecular clock is the most contentious step in every dating analysis, but the emerging total-evidence dating approach promises increased objectivity. It combines molecular and morphological data of extant and fossil taxa in a Bayesian framework. Information about absolute node ages stems from the inferred fossil placements and associated branch lengths, under the assumption of a morphological clock. We here use computer simulations to assess the impact of mismatch of the morphology model, such as misspecification of character states and transition rates, non-stationarity of the evolutionary process, and extensive variation of evolutionary rates among branches. Comparisons with published datasets suggest that, at least for evolutionary rates typically observed in discrete morphological characters, the total-evidence dating framework is surprisingly robust to these factors. We show that even with relatively low numbers of morphological characters sampled, extensive model mismatch is mostly irrelevant for the performance of the method. The only exception we found are cases of highly asymmetric state frequencies and thus transition rates, but these can be accounted for by appropriate morphology models. In contrast, we find that the temporal scope of fossil sampling has a major impact on divergence time estimates, with the time signal quickly eroding if only rather young fossils are included in an analysis. Our results suggest that total-evidence dating might work even without a good understanding of morphological evolution and that study design should instead focus on an adequate sampling of all relevant fossils, even those with highly incomplete preservation.

evolutionary biology↗

bioRxiv2018

The biggest losers: Habitat isolation deconstructs complex food webs from top to bottom

Habitat fragmentation is threatening global biodiversity. To date, there is only limited understanding of how habitat fragmentation or any alteration to the spatial structure of a landscape in general, affects species diversity within complex ecological networks such as food webs. Here, we present a dynamic and spatially-explicit food web model which integrates complex food web dynamics at the local scale and species-specific dispersal dynamics at the landscape scale, allowing us to study the interplay of local and spatial processes in metacommunities. We explore how habitat fragmentation, defined as a decrease of habitat availability and an increase of habitat isolation, affects the species diversity patterns of complex food webs (-, {beta}-,{gamma} -diversity), and specifically test whether there is a trophic dependency in the effect of habitat fragmentation on species diversity. In our model, habitat isolation is the main driver causing species loss and diversity decline. Our results emphasise that large-bodied consumer species at high trophic positions go extinct faster than smaller species at lower trophic levels, despite being superior dispersers that connect fragmented landscapes better. We attribute the loss of top species to a combined effect of higher biomass loss during dispersal with increasing habitat isolation in general, and the associated energy limitation in highly fragmented landscapes, preventing higher trophic levels to persist. To maintain trophic-complex and species-rich communities calls for effective conservation planning which considers the interdependence of trophic and spatial dynamics as well as the spatial context of a landscape and its energy availability.

ecology↗