Papers by Juliano Sarmento Cabral
Diversity and Distributions
Methods in Ecology and Evolution
Although the effects of species richness on ecosystem functioning have been extensively studied, ... more Although the effects of species richness on ecosystem functioning have been extensively studied, there is increased interest in understanding how community assembly in general might alter the functioning of ecosystems. We focus on two complementary approaches for evaluating how community assembly influences ecosystem function (here, productivity). The first quantifies the relative importance of complementarity and selection by contrasting monocultures with polycultures. The second identifies the effects of species losses and/or gains relative to the baseline polyculture, as well as the indirect effects on other species’ productivity. We evaluate and contrast these two approaches, using simulated communities structured by different, known competition mechanisms, where species compete for different resources and experience varying levels of environmental heterogeneity. We find that the metrics provided by these approaches can jointly discriminate the mechanisms of competition driving ...
Ecology Letters
Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore re... more Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species-specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi-dimensional assessments are still to be recommended.
abstractAimsThe General Dynamic Model of oceanic island biogeography (GDM) predicts how biogeogra... more abstractAimsThe General Dynamic Model of oceanic island biogeography (GDM) predicts how biogeographical rates, species richness, and endemism vary depending on island age, area, and isolation, based on the interplay of colonization, extinction, and speciation. Here, we used a simulation model to test whether GDM predictions may arise from individual- and population-level processes.LocationHypothetical hotspot islands.MethodsOur model (i) considers an idealized island ontogeny, (ii) metabolic constraints, and (iii) stochastic, spatially-explicit, and niche-based processes at the level of individuals and populations (plant demography, dispersal, competition, mutation, and speciation). Isolation scenarios involved varying dispersal ability and distances to mainland.ResultsHumped temporal trends were obtained for species richness, endemic richness, proportion of cladogenetic endemic species, number of radiating lineages, number of species per radiating lineage, and biogeographical rates...
ABSTRACTAimsUnderstanding how biodiversity emerges and varies in space and time is central to eco... more ABSTRACTAimsUnderstanding how biodiversity emerges and varies in space and time is central to ecology and biogeography. Multiple processes affect biodiversity at different scales and organizational levels, hence progress in understanding biodiversity dynamics requires the integration of these underlying processes. Here we present BioGEEM (BioGeographical Eco-Evolutionary Model), a spatially-explicit, process-based model that integrates all processes hypothesized to be relevant for biodiversity dynamics and that can be used to evaluate their relative roles.LocationHypothetical oceanic islandsMethodsThe model is stochastic, grid-based, and integrates ecological (metabolic constraints, demography, dispersal, and competition), evolutionary (mutation and speciation), and environmental (geo-climatic dynamics) processes. Plants on oceanic islands served as model system. We used the full model to test hypotheses about emergent patterns at different spatio-temporal scales and organizational ...
PLOS Biology
Understanding the origins of biodiversity has been an aspiration since the days of early naturali... more Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary, and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolutionary models are comparatively less developed. We present a general, spatially explicit, eco-evolutionary engine with a modular implementation that enables the modeling of multiple macroecological and macroevolutionary processes and feedbacks across representative spatiotemporally dynamic landscapes. Modeled processes can include species’ abiotic tolerances, biotic interactions, dispersal, speciation, and evolution of ecological traits. Commonly observed biodiversity patterns, such as α, β, and γ diversity, species ranges, ecological traits, and phylogenies, emerge as simulations proceed. As an illustration, we examine alternative hypothese...
Trends in Ecology & Evolution
The success of species invasions depends on multiple factors acting over the four invasion stages... more The success of species invasions depends on multiple factors acting over the four invasion stages transport, colonisation, establishment, and landscape spread. Each of these stages is influenced simultaneously by particular species traits and abiotic factors. While the importance of many of these determinants has already been investigated in relative isolation, they are rarely studied in combination and even then mostly ignore the final phase, i.e., landscape spread.Here we address this shortcoming by exploring the effect of both species traits and abiotic factors on the success of invasions using an individual-based mechanistic model, and relate those factors to the stages of invasion. This approach enables us to explicitly control abiotic factors (temperature as surrogate for productivity, disturbance and propagule pressure) as well as to monitor whole-community trait distributions of environmental adaptation, mass and dispersal abilities. We simulated introductions of plant indiv...
<p&amp... more <p>Explaining the origin of large-scale biodiversity gradients has been a key aspiration of early naturalists such as Wegener, Darwin and Humboldt; who looked at natural processes in an integrated way. Early on, these naturalists acknowledged the role of plate tectonics and climate variations in shaping modern day biodiversity patterns.<span> </span></p><p>As science advanced, the complexity of ecological, evolutionary, geological and climatological processes became evident while research became increasingly fragmented across different disciplines. Nevertheless, recent development in mechanistic modeling approaches now enable bringing disciplines back together, opening a new interdisciplinary scientific pathway.</p><p>Here, we present GEN3SIS, the GENeral Engine for Eco-Evolutionary SImulationS. It is the first spatially explicit eco-evolutionary model that incorporates deep-time Earth history, including plate tectonics, as well as climate variations in a modular way. The modular design allows exploring the consequences of user-defined biological processes that act across “real world” spatio-temporal landscapes. Emerging from the model are specie’s ranges, alpha and beta diversity patterns, ecological traits as well as phylogenies. Subsequently, these patterns can be compared to empirical data. Furthermore, GEN3SIS allows assessing paleoclimatic and paleogeographic hypotheses by using different Earth history scenarios and comparing simulation outputs with empirical biological data.</p><p>As a case study, we explore the cold-adapted plant biodiversity dynamics throughout the Earth’s Cenozoic history, based on a deep-time tectonic and climate reconstruction. The Cenozoic India-Asia collision formed the Himalayan mountain range. In this highly elevated region, the first cold niches of the Cenozoic appeared, demanding adaptation from the local living flora. We hindcast diversification of cold-adapted species with GEN3SIS, for which we use a topo-climatic reconstruction for the last 55 Myr. The model predicts the emergence of current cold-species richness patterns. Moreover, simulations indicate that cold-adapted flora emerged in the Oligocene, first in the Himalayas, followed by a spread to the Arctic. This agrees with observed low species richness and high nestedness of Arctic assemblages compared to those of the Himalayan mountain ranges. Under ongoing climate change a major loss of cold-adapted plant diversity is expected by the end of the century, particularly in lower latitude mountain ranges. Hindcasting and forecasting dynamics of cold-adapted lineages highlights the transient fate of cold organisms in a warming world.</p><p>GEN3SIS is made available as an R package, which allows customizing (i) the simulated landscape including environmental variables and (ii) all the processes interacting under different spatial and temporal scales. Consequently, GEN3SIS fosters collaborations between different natural disciplines and therefore contributes to an interdisciplinary understanding of the processes that shaped Earth’s history.</p>
People and Nature
This is an open access article under the terms of the Creative Commons Attribution License, which... more This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Journal of Biogeography
Recent years have seen an exponential increase in the amount of data available in all sciences an... more Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this "Big Data" trend, with a strong rise in the volume of data that we are using for our research. Here, we summarize the most recent developments in macroecology in the age of Big Data that were presented at the 2018 annual meeting of the Specialist Group Macroecology of the Ecological Society of Germany, Austria and Switzerland (GfÖ). Supported by computational advances, macroecology has been a rapidly developing field over recent years. Our meeting highlighted important avenues for further progress in terms of standardized data collection, data integration, method development and process integration. In particular, we focus on (a) important data gaps and new initiatives to close them, for example through space-and airborne sensors, (b) how various data sources and types can be integrated, (c) how uncertainty can be assessed in data-driven analyses and (d) how Big Data and machine learning approaches have opened new ways of investigating processes rather than simply describing patterns. We discuss how Big Data opens up new opportunities, but also poses new challenges to macroecological research. In the future, it will be essential to carefully assess data quality, the reproducibility of data compilation and analytical methods, and the communication of uncertainties. Major progress in the field will depend on the definition
The American Naturalist
The latitudinal diversity gradient (LDG) is one of Earth's most iconic biodiversity patterns and ... more The latitudinal diversity gradient (LDG) is one of Earth's most iconic biodiversity patterns and still one of the most debated. Explanations for the LDG are often categorized into three broad pathways in which the diversity gradient is created by (1) differential diversification rates, (2) differential carrying capacities (ecological limits), or (3) differential time to accumulate species across latitude. Support for these pathways has, however, been mostly verbally expressed. Here, we present a minimal model to clarify the essential assumptions of the three pathways and explore the sensitivity of diversity dynamics to these pathways. We find that an LDG arises most easily from a gradient in ecological limits compared with a gradient in the time for species accumulation or diversification rate in most modeled scenarios. Differential diversification rates create a stronger LDG than ecological limits only when speciation and dispersal rates are low, but then the predicted LDG seems weaker than the observed LDG. Moreover, range dynamics may reduce an LDG created by a gradient in diversification rates or time for species accumulation, but they cannot reduce an LDG induced by differential ecological limits. We conclude that our simple model provides a null prediction for the effectiveness of the three LDG pathways and can thus aid discussions about the causal mechanisms underlying the LDG or motivate more complex models to confirm or falsify our findings.
Uploads
Papers by Juliano Sarmento Cabral