Publications by authors named "Peter A Vesk"

Future changes in climate, together with rising atmospheric , may reorganise the functional composition of ecosystems. Without long-term historical data, predicting how traits will respond to environmental conditions-in particular, water availability-remains a challenge. While eco-evolutionary optimality theory (EEO) can provide insight into how plants adapt to their environment, EEO approaches to date have been formulated on the assumption that plants maximise carbon gain, which omits the important role of tissue construction and size in determining growth rates and fitness.

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Monitoring vegetation restoration is challenging because monitoring is costly, requires long-term funding, and involves monitoring multiple vegetation variables that are often not linked back to learning about progress toward objectives. There is a clear need for the development of targeted monitoring programs that focus on a reduced set of variables that are tied to specific restoration objectives. In this paper, we present a method to progress the development of a targeted monitoring program, using a pre-existing state-and-transition model.

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Trait-based approaches are commonly used to understand ecological phenomena and processes. Trait data are typically gathered by measuring local specimens, retrieving published records, or a combination of the two. Implications of methodological choices in trait-based ecological studies-including source of data, imputation technique, and species selection criteria-are poorly understood.

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Understanding the impact of management interventions on the environment over decadal and longer timeframes is urgently required. Longitudinal or large-scale studies with consistent methods are best practice, but more commonly, small datasets with differing methods are used to achieve larger coverage. Changes in methods and interpretation affect our ability to understand data trends through time or across space, so an ability to understand and adjust for such discrepancies between datasets is important for applied ecologists.

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Article Synopsis
  • The study investigates how functional traits of plants, like maximum height and seed mass, influence their distribution across different environments, specifically along elevation and slope.
  • Researchers found that shorter tree species thrive at higher elevations, while taller trees (>22m) exhibit a decline in occurrence at those heights.
  • Additionally, heavy-seeded trees favor drier, southerly aspects, while light-seeded trees prefer cooler, moister locations, revealing critical insights into plant responses to environmental conditions.
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Article Synopsis
  • Genetic differentiation and phenotypic plasticity both contribute to variation in traits within a species, but their influence differs between types of traits in short-lived plants.
  • In a study of Plantago lanceolata, researchers used greenhouse experiments and field data to analyze how traits respond to environmental changes.
  • They found that reproductive traits are primarily influenced by genetic factors related to fitness, while vegetative traits demonstrate greater plasticity, which complicates understanding the genetic influences in natural settings.
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Conservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which have already undergone recent changes in climate and experienced more frequent large-scale bushfires.

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1. The establishment of new botanic gardens in tropical regions highlights a need for weed risk assessment tools suitable for tropical ecosystems. The relevance of plant traits for invasion into tropical rainforests has not been well studied.

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Trait-based invasiveness studies typically categorize exotic species as invasive or noninvasive, implicitly assuming species form two homogenous groups. However, species can become invasive in different ways (e.g.

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The contribution of urban greenspaces to support biodiversity and provide benefits for people is increasingly recognized. However, ongoing management practices favor vegetation oversimplification, often limiting greenspaces to lawns and tree canopy rather than multi-layered vegetation that includes under- and midstorey, and the use of nonnative species. These practices hinder the potential of greenspaces to sustain indigenous biodiversity, particularly for taxa like insects that rely on plants for food and habitat.

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Biological invasions are a major human induced global change that is threatening global biodiversity by homogenizing the world's fauna and flora. Species spread because humans have moved species across geographical boundaries and have changed ecological factors that structure ecosystems, such as nitrogen deposition, disturbance, etc. Many biological invasions are caused accidentally, as a byproduct of human travel and commerce driven product shipping.

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Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions.

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Effective environmental assessment and management requires quantifiable biodiversity targets. Biodiversity benchmarks define these targets by focusing on specific biodiversity metrics, such as species richness. However, setting fixed targets can be challenging because many biodiversity metrics are highly variable, both spatially and temporally.

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Modeling plant growth using functional traits is important for understanding the mechanisms that underpin growth and for predicting new situations. We use three data sets on plant height over time and two validation methods-in-sample model fit and leave-one--out cross-validation-to evaluate non-linear growth model predictive performance based on functional traits. In-sample measures of model fit differed substantially from out-of-sample model predictive performance; the best models were rarely the best models.

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Field data collection can be expensive, time consuming, and difficult; insightful research requires statistical analyses supported by sufficient data. Pilot studies and power analysis provide guidance on sampling design but can be challenging to perform, as ecologists increasingly collect multiple types of data over different scales. Despite a growing simulation literature, it remains unclear how to appropriately design data collection for many complex projects.

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Fire is a major determinant of savanna tree communities and, as such, manipulation of fire frequency is an important management tool. Resolving the effects of fire management on tree size class distributions can help managers predict and plan for short-term ecological and economic outcomes, reveal different strategies by which woody plants cope with frequent fire, and help us predict vegetation changes under future fire scenarios. Savanna structure and size class distribution are strongly influenced by the ability of suppressed tree resprouts to escape stem death by frequent fire.

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Plant ecologists require spatial information on functional soil properties but are often faced with soil classifications that are not directly interpretable or useful for statistical models. Sand and clay content are important soil properties because they indicate soil water-holding capacity and nutrient content, yet these data are not available for much of the landscape. Remotely sensed soil radiometric data offer promise for developing statistical models of functional soil properties applicable over large areas.

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Losing a species from a community can cause further extinctions, a process also known as coextinction. The risk of being extirpated with an interaction partner is commonly inferred from a species' host-breadth, derived from observing interactions between species. But observational data suffers from imperfect detection, making coextinction estimates highly unreliable.

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Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We examined the influence of specific leaf area, woody density, seed size and leaf nitrogen content on three aspects of plant growth; maximum relative growth rate, age at maximum growth and asymptotic height.

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For many parasites, the full set of hosts that are susceptible to infection is not known, and this could lead to a bias in estimates of transmission. We used counts of individual adult parasites from historical parasitology studies in southern Africa to map a bipartite network of the nematode parasites of herbivore hosts that occur in Botswana. Bipartite networks are used in community ecology to represent interactions across trophic levels.

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Climate change is expected to increase fire activity and woody plant encroachment in arctic and alpine landscapes. However, the extent to which these increases interact to affect the structure, function and composition of alpine ecosystems is largely unknown. Here we use field surveys and experimental manipulations to examine how warming and fire affect recruitment, seedling growth and seedling survival in four dominant Australian alpine shrubs.

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Conservation translocations, anthropogenic movements of species to prevent their extinction, have increased substantially over the last few decades. Although multiple species are frequently moved to the same location, current translocation guidelines consider species in isolation. This practice ignores important interspecific interactions and thereby risks translocation failure.

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Background: Considerable resources are spent on habitat restoration across the globe to counter the impacts of habitat loss and degradation on wildlife populations. But, because of time and resourcing constraints on many conservation programs, the effectiveness of these habitat restoration programs in achieving their long-term goals of improving the population viability of particular wildlife species is rarely assessed and many restoration programs cannot demonstrate their effectiveness. Without such demonstration, and in particular demonstrating the causal relationships between habitat restoration actions and demographic responses of the target species, investments in restoration to achieve population outcomes are of uncertain value.

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Introgressive hybridization is increasingly recognized as having influenced the gene pools of large genera of plants, yet it is rarely invoked as an explanation for why closely related plant species do not co-occur. Here, we asked how the environment and tendency to interbreed relate to neighborhood co-occurrence patterns for Eucalyptus species in the Grampians National Park, Victoria, Australia. We identified species pairs that have experienced ongoing hybridization and introgression on the basis of the extent of incongruence between chloroplast DNA (JLA+ region) and nuclear ribosomal DNA (internal transcribed spacer region) phylogenies, geographic patterns of gene sharing, and field observation of intermediate morphologies.

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