Despite being a fundamental aspect of biodiversity, little is known about what controls species range sizes. This is especially the case for hyperdiverse organisms such as plants. We use the largest ...botanical data set assembled to date to quantify geographical variation in range size for ~ 85 000 plant species across the New World. We assess prominent hypothesised range‐size controls, finding that plant range sizes are codetermined by habitat area and long‐ and short‐term climate stability. Strong short‐ and long‐term climate instability in large parts of North America, including past glaciations, are associated with broad‐ranged species. In contrast, small habitat areas and a stable climate characterise areas with high concentrations of small‐ranged species in the Andes, Central America and the Brazilian Atlantic Rainforest region. The joint roles of area and climate stability strengthen concerns over the potential effects of future climate change and habitat loss on biodiversity.
Positive and negative associations between species are a key outcome of community assembly from regional species pools. These associations are difficult to detect and can be caused by a range of ...processes such as species interactions, local environmental constraints and dispersal. We integrate new ideas around species distribution modeling, covariance matrix estimation, and network analysis to provide an approach to inferring non-random species associations from local- and regional-scale occurrence data. Specifically, we provide a novel framework for identifying species associations that overcomes three challenges: 1) correcting for indirect effects from other species, 2) avoiding spurious associations driven by regional-scale distributions, and 3) describing these associations in a multi-species context. We highlight a range of research questions and analyses that this framework is able to address. We show that the approach is statistically robust using simulated data. In addition, we present an empirical analysis of > 1000 North American tree communities that gives evidence for weak positive associations among small groups of species. Finally, we discuss several possible extensions for identifying drivers of associations, predicting community assembly, and better linking biogeography and community ecology.
Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure ...and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development.
The objective of science is to understand the natural world; we argue that prediction is the only way to demonstrate scientific understanding, implying that prediction should be a fundamental aspect ...of all scientific disciplines. Reproducibility is an essential requirement of good science and arises from the ability to develop models that make accurate predictions on new data. Ecology, however, with a few exceptions, has abandoned prediction as a central focus and faces its own crisis of reproducibility. Models are where ecological understanding is stored and they are the source of all predictions – no prediction is possible without a model of the world. Models can be improved in three ways: model variables, functional relationships among dependent and independent variables, and in parameter estimates. Ecologists rarely test to assess whether new models have made advances by identifying new and important variables, elucidating functional relationships, or improving parameter estimates. Without these tests it is difficult to know if we understand more today than we did yesterday. A new commitment to prediction in ecology would lead to, among other things, more mature (i.e. quantitative) hypotheses, prioritization of modeling techniques that are more appropriate for prediction (e.g. using continuous independent variables rather than categorical) and, ultimately, advancement towards a more general understanding of the natural world.
Synthesis
Ecology, with a few exceptions, has abandoned prediction and therefore the ability to demonstrate understanding. Here we address how this has inhibited progress in ecology and explore how a renewed focus on prediction would benefit ecologists. The lack of emphasis on prediction has resulted in a discipline that tests qualitative, imprecise hypotheses with little concern for whether the results are generalizable beyond where and when the data were collected. A renewed commitment to prediction would allow ecologists to address critical questions about the generalizability of our results and the progress we are making towards understanding the natural world.
Trait‐based ecology aims to understand the processes that generate the overarching diversity of organismal traits and their influence on ecosystem functioning. Achieving this goal requires ...simplifying this complexity in synthetic axes defining a trait space and to cluster species based on their traits while identifying those with unique combinations of traits. However, so far, we know little about the dimensionality, the robustness to trait omission and the structure of these trait spaces. Here, we propose a unified framework and a synthesis across 30 trait datasets representing a broad variety of taxa, ecosystems and spatial scales to show that a common trade‐off between trait space quality and operationality appears between three and six dimensions. The robustness to trait omission is generally low but highly variable among datasets. We also highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, whereas species tend to disproportionately pack in the richest cluster. Based on these results, we propose some rules of thumb to build species trait spaces and estimate subsequent functional diversity indices.
We highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, while species tend to disproportionately pack in the richest cluster.
Tree species appear to prefer distinct climatic conditions, but the true nature of these preferences is obscured by species interactions and dispersal, which limit species’ ranges. We quantified ...realized and potential thermal niches of 188 North American tree species to conduct a continental-scale test of the architecture of niches. We found strong and consistent evidence that species occurring at thermal extremes occupy less than three-quarters of their potential niches, and species’ potential niches overlap at a mean annual temperature of ~12°C. These results clarify the breadth of thermal tolerances of temperate tree species and support the centrifugal organization of thermal niches. Accounting for the nonrealized components of ecological niches will advance theory and prediction in global change ecology.
Editor’s summary Ecologists use information on species’ environmental tolerances to predict how they will respond to environmental changes. However, species’ observed environmental tolerances, or realized niche, may be narrower than their potential niche if limited by dispersal, competition, or other biotic interactions. Laughlin and McGill investigated how much of their potential niches North American trees occupy by comparing temperature data from their native ranges with those from the arboreta where they have been planted around the world. Some species occupy almost all of their potential thermal niche, whereas others take up less than half. Although trees clearly occupy different climates across North America, all 188 studied species can live at a mean temperature of 12°C, possibly because of past selection events. —Bianca Lopez
Little consensus has emerged regarding how proximate and ultimate drivers such as productivity, disturbance and temperature may affect species richness and other aspects of biodiversity. Part of the ...confusion is that most studies examine species richness at a single spatial scale and ignore how the underlying components of species richness can vary with spatial scale.
We provide an approach for the measurement of biodiversity that decomposes changes in species rarefaction curves into proximate components attributed to: (a) the species abundance distribution, (b) density of individuals and (c) the spatial arrangement of individuals. We decompose species richness by comparing spatial and nonspatial sample‐ and individual‐based species rarefaction curves that differentially capture the influence of these components to estimate the relative importance of each in driving patterns of species richness change.
We tested the validity of our method on simulated data, and we demonstrate it on empirical data on plant species richness in invaded and uninvaded woodlands. We integrated these methods into a new r package (mobr).
The metrics that mobr provides will allow ecologists to move beyond comparisons of species richness in response to ecological drivers at a single spatial scale toward a dissection of the proximate components that determine species richness across scales.
Zusammenfassung
Es herrscht nur wenig Konsens darüber, auf welche Weise unmittelbare und mittelbare Faktoren wie Produktivität, Störung und Temperatur die Artenzahl und andere Aspekte der Biodiversität beeinflussen. Zum Teil rührt diese Unklarheit daher, dass die meisten Studien die Artenzahl nur auf einer einzigen räumlichen Skala betrachten und dabei außer Acht lassen, wie die zugrundeliegenden Komponenten der Artenzahl mit der räumlichen Skala variieren können.
Hier stellen wir unseren Ansatz “measurement of biodiversity” vor, mit dem Unterschiede zwischen Rarefaction‐Kurven auf die unmittelbaren Komponenten der Artenzahl zurückgeführt werden können. Dies sind: (a) Die Abundanzverteilung der Arten, (b) die Individuendichte und (c) die räumliche Anordnung der Individuen. Um den relativen Beitrag dieser Komponenten an der Änderung der Artenzahl einzuschätzen, teilen wir diese mithilfe von räumlichen und nicht‐räumlichen, Stichproben‐ und Individuen‐basierten Rarefaction‐Kurven auf, die den Einfluss der Komponenten auf unterschiedliche Weise widerspiegeln.
Wir haben unsere Methode mit simulierten Daten validiert und zeigen ihre Anwendung an einem empirischen Fallbeispiel zur Artenzahl in Wäldern mit und ohne invasive Arten. Unsere Methode wird in einem neuen r‐paket (mobr) zur Verfügung gestellt.
Die Biodiversitätsmetriken, die von mobr ausgegeben werden, erlauben es Ökologen, einen differenzierteren Blick auf Biodiversitätsmuster zu werfen: Statt die Änderung von Artenzahl auf einer einzigen räumlichen Skala zu betrachten, kann der Effekt von ökologischen Faktoren auf die unmittelbaren Komponenten der Artentenzahl skalenübergreifend analysiert werden.
The future of temperate forests in the face of global change and anthropogenic stressors remains uncertain. The regeneration stage, which is a critical bottleneck for many organisms, is a key ...indicator of forest health, future canopy composition and forest adaptive capacity.
In trees, seemingly healthy forests can be at long‐term risk due to insufficient juveniles to replace them (regeneration failure), or compositional differences between juveniles and adults (regeneration mismatch). We propose ‘regeneration debt’ to collectively describe regeneration failure and mismatch in analogy to extinction debt. To demonstrate this concept, we conducted a macroecological analysis of regeneration debt and anthropogenic stressors in eastern US forests.
Using U.S. Forest Service‐Forest Inventory and Analysis data, we quantified regeneration debt in 18 states from Maine to South Carolina, and evaluated the influence of site, anthropogenic stressors and climate drivers in the most affected regions.
We identified three distinct regions, with little debt in the north, moderate debt in the south and severe regeneration debt in the central, mid‐Atlantic region. In this region, multiple anthropogenic stressors (invasive plants, deer overabundance and land use) were associated with both low‐regeneration abundance and the prevalence of disease‐prone and/or suboptimal species.
Synthesis and applications. Without management intervention, the severe regeneration debt in the mid‐Atlantic region will likely lead to long‐term declines in forest cover, with cascading negative effects on forest‐dependent taxa and ecosystem services. Moreover, the location of the regeneration debt, which is at the northern edge of and involves many of the tree species that are predicted to gain suitable habitat in the Northeastern US, has consequences that extend far beyond its current geographic extent. In fact, this regeneration debt may already be functioning as a barrier to poleward tree migration. Our results demonstrate the value of regeneration debt as an indicator of ecosystem health and forest adaptive capacity.
Without management intervention, the severe regeneration debt in the mid‐Atlantic region will likely lead to long‐term declines in forest cover, with cascading negative effects on forest‐dependent taxa and ecosystem services. Moreover, the location of the regeneration debt, which is at the northern edge of and involves many of the tree species that are predicted to gain suitable habitat in the Northeastern US, has consequences that extend far beyond its current geographic extent. In fact, this regeneration debt may already be functioning as a barrier to poleward tree migration. Our results demonstrate the value of regeneration debt as an indicator of ecosystem health and forest adaptive capacity.
Humans have elevated global extinction rates and thus lowered global scale species richness. However, there is no a priori reason to expect that losses of global species richness should always, or ...even often, trickle down to losses of species richness at regional and local scales, even though this relationship is often assumed. Here, we show that scale can modulate our estimates of species richness change through time in the face of anthropogenic pressures, but not in a unidirectional way. Instead, the magnitude of species richness change through time can increase, decrease, reverse, or be unimodal across spatial scales. Using several case studies, we show different forms of scale‐dependent richness change through time in the face of anthropogenic pressures. For example, Central American corals show a homogenization pattern, where small scale richness is largely unchanged through time, while larger scale richness change is highly negative. Alternatively, birds in North America showed a differentiation effect, where species richness was again largely unchanged through time at small scales, but was more positive at larger scales. Finally, we collated data from a heterogeneous set of studies of different taxa measured through time from sites ranging from small plots to entire continents, and found highly variable patterns that nevertheless imply complex scale‐dependence in several taxa. In summary, understanding how biodiversity is changing in the Anthropocene requires an explicit recognition of the influence of spatial scale, and we conclude with some recommendations for how to better incorporate scale into our estimates of change.
There is an urgent need for large‐scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. ...Understanding these processes is critical for predicting and handling human‐biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions.
The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and co‐occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data.
The bien r package allows users to access the multiple types of data in the BIEN database. Functions in this package query the BIEN database by turning user inputs into optimised PostgreSQL functions. Function names follow a convention designed to make it easy to understand what each function does. We have also developed a protocol for providing customised citations and herbarium acknowledgements for data downloaded through the bien r package.
The development of the BIEN database represents a significant achievement in biological data integration, cleaning and standardization. Likewise, the bien r package represents an important tool for open science that makes the BIEN database freely and easily accessible to everyone.
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