Beyond central-tendency: If we agree discrete vegetation communities do not exist, should we investigate other methods of clustering?

Clustering is indispensable in the quest for robust vegetation classification schemes that aim to partition, summarise and communicate patterns. However, clustering solutions are sensitive to methods and data and are therefore unstable, a feature that is usually attributed to noise. Viewed through a central-tendency lens, noise is defined as the degree of departure from type, which is problematic since vegetation types are abstractions of continua, and so noise can only be quantified relative to the particular solution at hand. Graph theory models the structure of vegetation data based on the interconnectivity of samples. Through a graph-theoretic lens, the causes of instability can be quantified in absolute terms via the degree of connectivity among objects. We simulated incremental increases in sampling intensity in a dataset over five iterations and assessed classification stability across successive solutions derived using algorithms implementing, respectively, models of central-tendency and interconnectivity. We used logistic regression to model the likelihood of a sample changing groups between iterations as a function of distance to the centroid and degree of interconnectivity. Our results show that the degree to which samples are interconnected is a more powerful predictor of instability than the degree to which they deviate from their nearest centroid. The removal of weakly interconnected samples resulted in more stable classifications, although solutions with many clusters were apparently inherently less stable than those with few clusters, and improvements in stability flowing from the removal of outliers declined as the number of clusters increased. Our results reinforce the fact that clusters abstracted from continuous data are inherently unstable and that the quest for stable, fine-scale classifications from large regional datasets is illusory. Nevertheless, our results show that using models better suited to the analysis of continuous data may yield more stable classifications of the available data.

A comparison of central-tendency and interconnectivity approaches to clustering multivariate data with irregular structure.

Questions: Most clustering methods assume data are structured as discrete hyperspheroidal clusters to be evaluated by measures of central tendency. If vegetation data do not conform to this model, then vegetation data may be clustered incorrectly. What are the implications for cluster stability and evaluation if clusters are of irregular shape or density? Location: Southeast Australia. Methods: We define misplacement as the placement of a sample in a cluster other than (distinct from) its nearest neighbor and hypothesize that optimizing homogeneity incurs the cost of higher rates of misplacement. Chameleon is a graph-theoretic algorithm that emphasizes interconnectivity and thus is sensitive to the shape and distribution of clusters. We contrasted its solutions with those of traditional nonhierarchical and hierarchical (agglomerative and divisive) approaches. Results: Chameleon-derived solutions had lower rates of misplacement and only marginally higher heterogeneity than those of k-means in the range of 15-60 clusters, but their metrics converged with larger numbers of clusters. Solutions derived by agglomerative clustering had the best metrics (and divisive clustering the worst) but both produced inferior high-level solutions to those of Chameleon by merging distantly-related clusters. Conclusions: Graph-theoretic algorithms, such as Chameleon, have an advantage over traditional algorithms when data exhibit discontinuities and variable structure, typically producing more stable solutions (due to lower rates of misplacement) but scoring lower on traditional metrics of central tendency. Advantages are less obvious in the partitioning of data from continuous gradients; however, graph-based partitioning protocols facilitate the hierarchical integration of solutions.

A function-based typology for Earth's ecosystems.

As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of 'living in harmony with nature'1,2. Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management3. Ecosystems vary in their biota4, service provision5 and relative exposure to risks6, yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth's ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework.

Hydrological and geochemical responses of fire in a shallow cave system.

The influence of wildfire on surface soil and hydrology has been widely investigated, while its impact on the karst vadose zone is still poorly understood. A moderate to severe experimental fire was conducted on a plot (10 m × 10 m) above the shallow Wildman's Cave at Wombeyan Caves, New South Wales, Australia in May 2016. Continuous sampling of water stable isotopes, inorganic geochemistry and drip rates were conducted from Dec 2014 to May 2017. After the fire, drip discharge patterns were significantly altered, which is interpreted as the result of increased preferential flows and decreased diffuse flows in the soil. Post-fire drip water δ18O decreased by 6.3‰ in the first month relative to the average pre-fire isotopic composition. Post-fire monitoring showed an increase in drip water δ18O in the following six months. Bedrock related solutes (calcium, magnesium, strontium) decreased rapidly after the fire due to reduced limestone dissolution time and potentially reduced soil CO2. Soil- and ash-derived solutes (boron, lead, potassium, sodium, silicon, iodine and iron) all decreased after the fire due to volatilisation at high temperatures, except for SO42-. This is the first study to understand the hydrological impact from severe fires conducted on a karst system. It provides new insights on the cave recharge process, with a potential explanation for the decreased d18O in speleothem-based fire study, and also utilise the decreased bedrock solutes to assess the wildfire impacts both in short and long time scales.

The impact of fire on the geochemistry of speleothem-forming drip water in a sub-alpine cave.

Fire dramatically modifies the surface environment by combusting vegetation and changing soil properties. Despite this well-documented impact on the surface environment, there has been limited research into the impact of fire events on karst, caves and speleothems. Here we report the first experiment designed to investigate the short-term impacts of a prescribed fire on speleothem-forming cave drip water geochemistry. Before and after the fire, water was collected on a bi-monthly basis from 18 drip sites in South Glory Cave, New South Wales, Australia. Two months post-fire, there was an increase in B, Si, Na, Fe and Pb concentrations at all drip sites. We conclude that this response is most likely due to the transport of soluble ash-derived elements from the surface to the cave drip water below. A significant deviation in stable water isotopic composition from the local meteoric water line was also observed at six of the sites. We hypothesise that this was due to partial evaporation of soil water resulting in isotopic enrichment of drip waters. Our results demonstrate that even low-severity prescribed fires can have an impact on speleothem-forming cave drip water geochemistry. These findings are significant because firstly, fires need to be considered when interpreting past climate from speleothem δ18O isotope and trace element records, particularly in fire prone regions such as Australia, North America, south west Europe, Russia and China. Secondly, it supports research that demonstrates speleothems could be potential proxy records for past fires.

Phylogenetic and functional dissimilarity does not increase during temporal heathland succession.

Succession has been a focal point of ecological research for over a century, but thus far has been poorly explored through the lens of modern phylogenetic and trait-based approaches to community assembly. The vast majority of studies conducted to date have comprised static analyses where communities are observed at a single snapshot in time. Long-term datasets present a vantage point to compare established and emerging theoretical predictions on the phylogenetic and functional trajectory of communities through succession. We investigated within, and between, community measures of phylogenetic and functional diversity in a fire-prone heathland along a 21 year time series. Contrary to widely held expectations that increased competition through succession should inhibit the coexistence of species with high niche overlap, plots became more phylogenetically and functionally clustered with time since fire. There were significant directional shifts in individual traits through time indicating deterministic successional processes associated with changing abiotic and/or biotic conditions. However, relative to the observed temporal rate of taxonomic turnover, both phylogenetic and functional turnover were comparatively low, suggesting a degree of functional redundancy among close relatives. These results contribute to an emerging body of evidence indicating that limits to the similarity of coexisting species are rarely observed at fine spatial scales.

Humidity-regulated dormancy onset in the Fabaceae: a conceptual model and its ecological implications for the Australian wattle Acacia saligna.

BACKGROUND AND AIMS: Seed dormancy enhances fitness by preventing seeds from germinating when the probability of seedling survival and recruitment is low. The onset of physical dormancy is sensitive to humidity during ripening; however, the implications of this mechanism for seed bank dynamics have not been quantified. This study proposes a model that describes how humidity-regulated dormancy onset may control the accumulation of a dormant seed bank, and seed experiments are conducted to calibrate the model for an Australian Fabaceae, Acacia saligna. The model is used to investigate the impact of climate on seed dormancy and to forecast the ecological implications of human-induced climate change. METHODS: The relationship between relative humidity and dormancy onset was quantified under laboratory conditions by exposing freshly matured non-dormant seeds to constant humidity levels for fixed durations. The model was field-calibrated by measuring the response of seeds exposed to naturally fluctuating humidity. The model was applied to 3-hourly records of humidity spanning the period 1972-2007 in order to estimate both temporal variability in dormancy and spatial variability attributable to climatic differences among populations. Climate change models were used to project future changes in dormancy onset. KEY RESULTS: A sigmoidal relationship exists between dormancy and humidity under both laboratory and field conditions. Seeds ripened under field conditions became dormant following very short exposure to low humidity (<20 %). Prolonged exposure at higher humidity did not increase dormancy significantly. It is predicted that populations growing in a temperate climate produce 33-55 % fewer dormant seeds than those in a Mediterranean climate; however, dormancy in temperate populations is predicted to increase as a result of climate change. CONCLUSIONS: Humidity-regulated dormancy onset may explain observed variation in physical dormancy. The model offers a systematic approach to modelling this variation in population studies. Forecast changes in climate have the potential to alter the seed bank dynamics of species with physical dormancy regulated by this mechanism, with implications for their capacity to delay germination and exploit windows for recruitment.

Fire management to combat disease: turning interactions between threats into conservation management.

As the number and intensity of threats to biodiversity increase, there is a critical need to investigate interactions between threats and manage populations accordingly. We ask whether it is possible to reduce the effects of one threat by mitigating another. We used long-term data for the long-lived resprouter, Xanthorrhoea resinosa Pers., to parameterise an individual-based population model. This plant is currently threatened by adverse fire regimes and the pathogen Phytophthora cinnamomi. We tested a range of fire and disease scenarios over various time horizons relevant to the population dynamics of the species and the practicalities of management. While fire does not kill the disease, it does trigger plant demographic responses that may promote population persistence when disease is present. Population decline is reduced with frequent fires because they promote the greatest number of germination events, but frequent fires reduce adult stages, which is detrimental in the long term. Fire suppression is the best action for the non-seedling stages but does not promote recruitment. With disease, frequent fire produced the highest total population sizes for shorter durations, but for longer durations fire suppression gave the highest population sizes. When seedlings were excluded, fire suppression was the best action. We conclude that fire management can play an important role in mitigating threats posed by this disease. The best approach to reducing declines may be to manage populations across a spatial mosaic in which the sequence of frequent fires and suppression are staggered across patches depending on the level of disease at the site.