William D. Pearse

Functional traits, the phylogeny of function, and ecosystem service vulnerability

People depend on benefits provided by ecological systems. Understanding how these ecosystem services – and the ecosystem properties underpinning them – respond to drivers of change is therefore an urgent priority. We address this challenge through developing a novel risk-assessment framework that integrates ecological and evolutionary perspectives on functional traits to determine species’ effects on ecosystems and their tolerance of environmental changes. We define Specific Effect Function (SEF) as the per-gram or per capita capacity of a species to affect an ecosystem property, and Specific Response Function (SRF) as the ability of a species to maintain or enhance its population as the environment changes. Our risk assessment is based on the idea that the security of ecosystem services depends on how effects (SEFs) and tolerances (SRFs) of organisms – which both depend on combinations of functional traits – correlate across species and how they are arranged on the species’ phylogeny. Four extreme situations are theoretically possible, from minimum concern when SEF and SRF are neither correlated nor show a phylogenetic signal, to maximum concern when they are negatively correlated (i.e., the most important species are the least tolerant) and phylogenetically patterned (lacking independent backup). We illustrate the assessment with five case studies, involving both plant and animal examples. However, the extent to which the frequency of the four plausible outcomes, or their intermediates, apply more widely in real-world ecological systems is an open question that needs empirical evidence, and suggests a research agenda at the interface of evolutionary biology and ecosystem ecology.

Using ecological thresholds to evaluate the costs and benefits of set-asides in a biodiversity hotspot

Cost-effective conservation on private land How affordable is biodiversity conservation in a fragmented landscape? Banks-Leite et al. asked this question for the biodiversity hotspot of the Brazilian Atlantic Forest. An annual investment of <10% of Brazils agricultural subsidies could support effective ecological restoration on private lands. This would increase biodiversity in set-aside land to the same level observed in protected areas. The cost-effectiveness of this scheme suggests a path forward for conservation strategies in other similarly mixed landscapes, too. Science, this issue p. 1041 A small portion of Brazil’s agricultural subsidies would be enough to preserve private land in the Brazilian Atlantic Forest. Ecological set-asides are a promising strategy for conserving biodiversity in human-modified landscapes; however, landowner participation is often precluded by financial constraints. We assessed the ecological benefits and economic costs of paying landowners to set aside private land for restoration. Benefits were calculated from data on nearly 25,000 captures of Brazilian Atlantic Forest vertebrates, and economic costs were estimated for several restoration scenarios and values of payment for ecosystem services. We show that an annual investment equivalent to 6.5% of what Brazil spends on agricultural subsidies would revert species composition and ecological functions across farmlands to levels found inside protected areas, thereby benefiting local people. Hence, efforts to secure the future of this and other biodiversity hotspots may be cost-effective.

phyloGenerator: an automated phylogeny generation tool for ecologists

Summary 1. Ecologists increasingly wish to use phylogenies, but are hampered by the technical challenge of phylogeny estimation. 2. We present phyloGenerator, an open-source, stand-alone Python program, that makes use of pre-existing sequence data and taxonomic information to largely automate the estimation of phylogenies. 3. phyloGenerator allows nonspecialists to quickly and easily produce robust, repeatable, and defensible phylogenies without requiring an extensive knowledge of phylogenetics. Experienced phylogeneticists may also find it useful as a tool to conduct exploratory analyses. 4. phyloGenerator performs a number of ‘sanity checks’ on users’ output, but users should still check their outputs carefully; we give some advice on how to do so. 5. By linking a number of tools in a common framework, phyloGenerator is a step towards an open, reproducible phylogenetic workflow. 6. Bundled downloads for Windows and Mac OSX, along with the source code and an install script for Linux, can be found at http://willpearse.github.io/phyloGenerator (note the capital ‘G’).

Using landscape history to predict biodiversity patterns in fragmented landscapes

Landscape ecology plays a vital role in understanding the impacts of land-use change on biodiversity, but it is not a predictive discipline, lacking theoretical models that quantitatively predict biodiversity patterns from first principles. Here, we draw heavily on ideas from phylogenetics to fill this gap, basing our approach on the insight that habitat fragments have a shared history. We develop a landscape ‘terrageny’, which represents the historical spatial separation of habitat fragments in the same way that a phylogeny represents evolutionary divergence among species. Combining a random sampling model with a terrageny generates numerical predictions about the expected proportion of species shared between any two fragments, the locations of locally endemic species, and the number of species that have been driven locally extinct. The model predicts that community similarity declines with terragenetic distance, and that local endemics are more likely to be found in terragenetically distinctive fragments than in large fragments. We derive equations to quantify the variance around predictions, and show that ignoring the spatial structure of fragmented landscapes leads to over-estimates of local extinction rates at the landscape scale. We argue that ignoring the shared history of habitat fragments limits our ability to understand biodiversity changes in human-modified landscapes.

pez: phylogenetics for the environmental sciences

UNLABELLED pez is an R package that permits measurement, modelling and simulation of phylogenetic structure in ecological data. pez contains the first implementation of many methods in R, and aggregates existing data structures and methods into a single, coherent package. AVAILABILITY AND IMPLEMENTATION pez is released under the GPL v3 open-source license, available on the Internet from CRAN (http://cran.r-project.org). The package is under active development, and the authors welcome contributions (see http://github.com/willpearse/pez). CONTACT will.pearse@gmail.com.

Taking the long view: Integrating recorded, archeological, paleoecological, and evolutionary data into ecological restoration

Historical information spanning different temporal scales (from tens to millions of years) can influence restoration practice by providing ecological context for better understanding of contemporary ecosystems. Ecological history provides clues about the assembly, structure, and dynamic nature of ecosystems, and this information can improve forecasting of how restored systems will respond to changes in climate, disturbance regimes, and other factors. History recorded by humans can be used to generate baselines for assessing changes in ecosystems, communities, and populations over time. Paleoecology pushes these baselines back hundreds, thousands, or even millions of years, offering insights into how past species assemblages have responded to changing disturbance regimes and climate. Furthermore, archeology can be used to reconstruct interactions between humans and their environment for which no documentary records exist. Going back further, phylogenies reveal patterns that emerged from coupled evolutionary-ecological processes over very long timescales. Increasingly, this information can be used to predict the stability, resilience, and functioning of assemblages into the future. We review examples in which recorded, archeological, paleoecological, and evolutionary information has been or could be used to inform goal setting, management, and monitoring for restoration. While we argue that long-view historical ecology has much to offer restoration, there are few examples of restoration projects explicitly incorporating such information or of research that has evaluated the utility of such perspectives in applied management contexts. For these ideas to move from theory into practice, tests performed through research-management partnerships are needed to determine to what degree taking the long view can support achievement of restoration objectives.

A statistical estimator for determining the limits of contemporary and historic phenology

Climate change affects not just where species are found, but also when species’ key life-history events occur—their phenology. Measuring such changes in timing is often hampered by a reliance on biased survey data: surveys identify that an event has taken place (for example, the flower is in bloom), but not when that event happened (for example, the flower bloomed yesterday). Here, we show that this problem can be circumvented using statistical estimators, which can provide accurate and unbiased estimates from sparsely sampled observations. We demonstrate that such methods can resolve an ongoing debate about the relative timings of the onset and cessation of flowering, and allow us to place modern observations reliably within the context of the vast wealth of historical data that reside in herbaria, museum collections, and written records. We also analyse large-scale citizen science data from the United States National Phenology Network and reveal not just earlier but also potentially more variable flowering in recent years. Evidence for greater variability through time is important because increases in variation are characteristic of systems approaching a state change.A statistical-estimators technique adapted from extinction research is shown to estimate accurately the timing of the onset and cessation of flowering, using sparsely sampled data from a variety of historical and contemporary sources.

Barro Colorado Island's phylogenetic assemblage structure across fine spatial scales and among clades of different ages

Phylogenetic analyses of assemblage membership provide insight into how ecological communities are structured. However, despite the scale-dependency of many ecological processes, little is known about how assemblage and source pool size definitions can be altered, either alone or together, to provide insight into how ecological diversity is maintained. Moreover, although studies have acknowledged that different clades within an assemblage may be structured by different forces, there has been no attempt to relate the age of a clade to its community phylogenetic structure. Using assemblage phylogenies and spatially explicit data for trees from Barro Colorado Island (BCI), we show that larger assemblages, and assemblages with larger source pools, are more phylogenetically clustered. We argue that this reflects competition, the influence of pathogens, and chance assembly at smaller spatial scales, all operating within the context of wider-scale habitat filtering. A community phylogenetic measure that is based on a null model derived explicitly from trait evolution theory, D, is better able to detect these differences than commonly used measures such as SES(MPD) and SES(MNTD). We also detect a moderate tendency for stronger phylogenetic clustering in younger clades, which suggests that coarse analyses of diverse assemblages may be missing important variation among clades. Our results emphasize the importance of spatial and phylogenetic scale in community phylogenetics and show how varying these scales can help to untangle complex assembly processes.

Metrics and Models of Community Phylogenetics

Community phylogenetics combines ideas from community ecology and evolutionary biology, using species phylogeny to explore the processes underlying ecological community assembly. Here, we describe the development of the field’s comparative methods and their roots in conservation biology, biodiversity quantification, and macroevolution. Next, we review the multitude of community phylogenetic structure metrics and place each into one of four classes: shape, evenness, dispersion, and dissimilarity. Shape metrics examine the structure of an assemblage phylogeny, while evenness metrics incorporate species abundances. Dispersion metrics examine assemblages given a phylogeny of species that could occupy those assemblages (the source pool), while dissimilarity metrics compare phylogenetic structure between assemblages. We then examine how metrics perform in simulated communities that vary in their phylogenetic structure. We provide an example of model-based approaches and argue that they are a promising area of future research in community phylogenetics. Code to reproduce all these analyses is available in the Online Practical Material (http://www.mpcm-evolution.com). We conclude by discussing future research directions for the field as a whole.

The influence of life history traits on the phenological response of British butterflies to climate variability since the late‐19th century

Many species of plants and animals have advanced their phenology in response to climate warming in recent decades. Most of the evidence available for these shifts is based on data from the last few decades, a period coinciding with rapid climate warming. Baseline data is required to put these recent phenological changes in a long-term context. We analysed the phenological response of 51 resident British butterfly species using data from 83 500 specimens in the collections of the Natural History Museum, London, covering the period 1880–1970. Our analysis shows that only three species significantly advanced their phenology between 1880 and 1970, probably reflecting the relatively small increase in spring temperature over this period. However, the phenology of all but one of the species we analysed showed phenological sensitivity to inter-annual climate variability and a significant advancement in phenology in years in which spring or summer temperatures were warm and dry. The phenologies of butterfly species were more sensitive to weather if the butterfly species was early flying, southerly distributed, and a generalist in terms of larval diet. This observation is consistent with the hypothesis that species with greater niche breadth may be more phenologically sensitive than species with important niche constraints. Comparison of our results with post-1976 data from the UK Butterfly Monitoring Scheme show that species flying early in the year had a greater rate of phenological advancement prior to the mid-1970s. Additionally, prior to the mid-1970s, phenology was influenced by temperatures in March or April, whereas since 1976, February temperature had a stronger influence on the phenology. These results suggest that early flying species may be approaching the limits of phenological advancement in response to recent climate warming.