Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models

A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.

Modelling niches of arbitrary shape in genetic algorithms using Niche Linkage in the Dynamic Niche Clustering framework

We present some additions to a fuzzy variable radius niche technique called Dynamic Niche Clustering (DNC) (Gan and Warwick, 1999; 2000; 2001) that enable the identification and creation of niches of arbitrary shape through a mechanism called Niche Linkage. We show that by using this mechanism it is possible to attain better feature extraction from the underlying population.

Dynamic Niche Clustering: a fuzzy variable radius niching technique for multimodal optimisation in GAs

This paper describes the recent developments and improvements made to the variable radius niching technique called Dynamic Niche Clustering (DNC). DNC is fitness sharing based technique that employs a separate population of overlapping fuzzy niches with independent radii which operate in the decoded parameter space, and are maintained alongside the normal GA population. We describe a speedup process that can be applied to the initial generation which greatly reduces the complexity of the initial stages. A split operator is also introduced that is designed to counteract the excessive growth of niches, and it is shown that this improves the overall robustness of the technique. Finally, the effect of local elitism is documented and compared to the performance of the basic DNC technique on a selection of 2D test functions. The paper is concluded with a view to future work to be undertaken on the technique.

The role of closed ecological systems in carbon cycle modelling

Acquiring a mechanistic understanding of the role of the biotic feedbacks on the links between atmospheric CO2 concentrations and temperature is essential for trustworthy climate predictions. Currently, computer based simulations are the only available tool to estimate the global impact of the biotic feedbacks on future atmospheric CO2 and temperatures. Here we propose an alternative and complementary approaches by using materially closed and energetically open analogue/physical models of the carbon cycle. We argue that there is potential in using a materially closed approach to improve our understanding of the magnitude and sign of many biotic feedbacks, and that recent technological advance make this feasible. We also suggest how such systems could be designed and discuss the advantages and limitations of establishing physical models of the global carbon cycle.

Adding value to ecological risk assessment with population modeling

Current measures used to estimate the risks of toxic chemicals are not relevant to the goals of the environmental protection process, and thus ecological risk assessment (ERA) is not used as extensively as it should be as a basis for cost-effective management of environmental resources. Appropriate population models can provide a powerful basis for expressing ecological risks that better inform the environmental management process and thus that are more likely to be used by managers. Here we provide at least five reasons why population modeling should play an important role in bridging the gap between what we measure and what we want to protect. We then describe six actions needed for its implementation into management-relevant ERA.

Sizing reserves within a landscape: the roles of villagers' reactions and the ecological-socioeconomic setting

Traditionally, siting and sizing decisions for parks and reserves reflected ecological characteristics but typically failed to consider ecological costs created from displaced resource collection, welfare costs on nearby rural people, and enforcement costs. Using a spatial game-theoretic model that incorporates the interaction of socioeconomic and ecological settings, we show how incorporating more recent mandates that include rural welfare and surrounding landscapes can result in very different optimal sizing decisions. The model informs our discussion of recent forest management in Tanzania, reserve sizing and siting decisions, estimating reserve effectiveness, and determining patterns of avoided forest degradation in Reduced Emissions from Deforestation and Forest Degradation programs.

Multiple routes to mammalian diversity

The radiation of the mammals provides a 165-million-year test case for evolutionary theories of how species occupy and then fill ecological niches. It is widely assumed that species often diverge rapidly early in their evolution, and that this is followed by a longer, drawn-out period of slower evolutionary fine-tuning as natural selection fits organisms into an increasingly occupied niche space1,2. But recent studies have hinted that the process may not be so simple3–5. Here we apply statistical methods that automatically detect temporal shifts in the rate of evolution through time to a comprehensive mammalian phylogeny6 and data set7 of body sizes of 3,185 extant species. Unexpectedly, the majority of mammal species, including two of the most speciose orders (Rodentia and Chiroptera), have no history of substantial and sustained increases in the rates of evolution. Instead, a subset of the mammals has experienced an explosive increase (between 10- and 52-fold) in the rate of evolution along the single branch leading to the common ancestor of their monophyletic group (for example Chiroptera), followed by a quick return to lower or background levels. The remaining species are a taxonomically diverse assemblage showing a significant, sustained increase or decrease in their rates of evolution. These results necessarily decouple morphological diversification from speciation and suggest that the processes that give rise to the morphological diversity of a class of animals are far more free to vary than previously considered. Niches do not seem to fill up, and diversity seems to arise whenever, wherever and at whatever rate it is advantageous.

The monitoring of ecological quality and the classification of standing waters in temperate regions: a review and proposal based on a worked scheme for British waters

This paper reviews the ways that quality can be assessed in standing waters, a subject that has hitherto attracted little attention but which is now a legal requirement in Europe. It describes a scheme for the assessment and monitoring of water and ecological quality in standing waters greater than about I ha in area in England & Wales although it is generally relevant to North-west Europe. Thirteen hydrological, chemical and biological variables are used to characterise the standing water body in any current sampling. These are lake volume, maximum depth, onductivity, Secchi disc transparency, pH, total alkalinity, calcium ion concentration, total N concentration,winter total oxidised inorganic nitrogen (effectively nitrate) concentration, total P concentration, potential maximum chlorophyll a concentration, a score based on the nature of the submerged and emergent plant community, and the presence or absence of a fish community. Inter alia these variables are key indicators of the state of eutrophication, acidification, salinisation and infilling of a water body.