Using dynamic sustainability indicators to assess environmental policy measures in Biosphere Reserves

The assessment of different policy options represents a major tool for decision-makers in Biosphere Reserves, to develop more-resilient strategies for sustainable development and to visualise unintended consequences of these policies.In this work we analyse eight measures proposed by different agents in order to meet the main objectives of environmental sustainability, included in the Action Plan of the Fuerteventura Biosphere Reserve (Spain). We quantified the effects of these measures in terms of the sustainability thresholds of 10 environmental indicators, also proposed by the Action Plan, which was integrated in the Fuerteventura Biosphere Reserve dynamic model. Their behaviours under these measures allow determination of whether the objectives will be met in the period 2012–2025. Although some indicators would improve under these measures, fitting certain objectives, some negative effects on other indicators confirm the existence of trade-offs among these objectives. For instance, grazing limitation would improve the proportion of high-quality vegetation but would negatively affect the Egyptian vulture population, which would even fall below its sustainability threshold. The definition of thresholds for each indicator allows decision-makers to establish a way to prioritise among the eight measures analysed. The results show that these measures are insufficient to meet the sustainability thresholds of four indicators (the landscape indicator, the proportion of renewable energy, the per capita primary energy consumption and carbon dioxide emissions). Focusing on the remaining six indicators and following the rule “Threshold out, measure out”, seven out of the eight measures would exceed some thresholds and should be avoided. Only one option, aimed at growing fodder to feed cattle on restored traditional agricultural lands, would not exceed any of these thresholds. However, this measure also presents certain negative effects regarding indicators related to flagship species (the houbara habitat and the Egyptian vulture population), which would require compensation measures.     

Models for Trypanosoma evansi (surra), its control and economic impact on small-hold livestock owners in the Philippines

Simple demographic and infectious disease models of buffaloes and other domestic hosts for animal trypanosomosis (surra) caused by Trypanosoma evansi were developed. The animal models contained deterministic and stochastic elements and were linked to simulate the benefit of control regimes for surra in village domestic animal populations in Mindanao, Philippines. The impact of the disease on host fertility and mortality were key factors in determining the economic losses and net-benefit from the control regimes. If using a high (99%) efficacy drug in surra-moderate to high risk areas, then treating all animals twice each year yielded low prevalence in 2 years; targeted treatment of clinically sick animals, constantly monitored (monthly), required 75% fewer treatments but took longer to reach a low prevalence than treating all animals twice each year. At high drug efficacy both of these treatment strategies increased the benefit over untreated animals by 81%. If drug efficacy declined then the benefit obtained from twice yearly treatment of all animals declined rapidly compared with regular monitoring and targeting treatment to clinically sick animals. The current control regimen applied in the Philippines of annual sero-testing for surra and only treating sero-positive animals provided the lowest net-benefit of all the control options simulated and would not be regarded as effective control. The total net-benefit from effective surra control for a typical village in a moderate/high risk area was 7.9 million pesos per annum (US $158,000). The value added to buffaloes, cattle, horses, goats/sheep and pigs as a result of this control was US $88, $84, $151, $7, $114 per animal/year, respectively.     

Individual-based model of spatio-temporal dynamics of mixed forest stands

This research presents the results of constructing and parameterizing an individual-based model of spatiotemporal dynamics of mixed forest stands. The model facilitates computerized experiments with forest stands having different combinations of species and age structures. These forest stands grow on temperate areas where light is the main system-forming factor that shapes and develops forest ecosystems. The model TEMFORM (TEMperate FORests Model) is developed with few equations and parameters, most of which can be estimated using standard forest inventory data. Parameterization of the model used the growth tables of a set of basic forest-forming species in Far East Russia. Simulation results of the development of the natural single- and mixed-species stands and the effects of different types of disturbances on the stand dynamics and compositions are presented.     

Non‐parametric habitat models with automatic interactions

Questions: Can a statistical model be designed to represent more directly the nature of organismal response to multiple interacting factors? Can multiplicative kernel smoothers be used for this purpose? What advantages does this approach have over more traditional habitat modelling methods? Methods: Non‐parametric multiplicative regression (NPMR) was developed from the premises that: the response variable has a minimum of zero and a physiologically‐determined maximum, species respond simultaneously to multiple ecological factors, the response to any one factor is conditioned by the values of other factors, and that if any of the factors is intolerable then the response is zero. Key features of NPMR are interactive effects of predictors, no need to specify an overall model form in advance, and built‐in controls on overfitting. The effectiveness of the method is demonstrated with simulated and real data sets. Results: Empirical and theoretical relationships of species response to multiple interacting predictors can be represented effectively by multiplicative kernel smoothers. NPMR allows us to abandon simplistic assumptions about overall model form, while embracing the ecological truism that habitat factors interact.     

TREES SIFTER 1.0: an approximate method to estimate the time to the most recent common ancestor of a sample of DNA sequences

trees sifter 1.0 implements an approximate method to estimate the time to the most recent common ancestor (TMRCA) of a set of DNA sequences, using population evolution modelling. In essence, the program simulates genealogies with a user‐defined model of coalescence of lineages, and then compares each simulated genealogy to the genealogy inferred from the real data, through two summary statistics: (i) the number of mutations on the genealogy (M_n), and (ii) the number of different sequence types (alleles) observed (K_n). The simulated genealogies are then submitted to a rejection algorithm that keeps only those that are the most likely to have generated the observed sequence data. At the end of the process, the accepted genealogies can be used to estimate the posterior probability distribution of the TMRCA.     

Comparison of the functional and numerical responses of resistant versus non-resistant populations of the copepod Acartia hudsonica fed the toxic dinoflagellate Alexandrium tamarense

The functional and numerical responses of grazers are key pieces of information in predicting and modeling predator–prey interactions. It has been demonstrated that exposure to toxic algae can lead to evolved resistance in grazer populations. However, the influence of resistance on the functional and numerical response of grazers has not been studied to date. Here, we compared the functional and numerical responses of populations of the copepod Acartia hudsonica that vary in their degree of resistance to the toxic dinoflagellate Alexandrium tamarense. In common environment experiments carried out after populations had been grown under identical conditions for several generations, female copepods were offered solutions containing different concentrations of either toxic A. tamarense or the non-toxic green flagellate Tetraselmis sp. ranging from 25 to 500 μgC L⁻¹, and ingestion and egg production rates were measured. Throughout most of the range of concentrations of the toxic diet, copepod populations that had been historically exposed to toxic blooms of Alexandrium exhibited significantly higher ingestion and egg production rates than populations that had little or no exposure to these blooms. In contrast, there were no significant differences between populations in ingestion or egg production for the non-toxic diet. Hence, the between population differences in functional and numerical response to A. tamarense were indeed related to resistance. We suggest that the effect of grazer toxin resistance should be incorporated in models of predator and toxic prey interactions. The potential effects of grazer toxin resistance in the development and control of Alexandrium blooms are illustrated here with a simple simulation exercise.     

A genetic and spatial Bayesian analysis of mastitis resistance

A nationwide health card recording system for dairy cattle was introduced in Norway in 1975 (the Norwegian Cattle Health Services). The data base holds information on mastitis occurrences on an individual cow basis. A reduction in mastitis frequency across the population is desired, and for this purpose risk factors are investigated. In this paper a Bayesian proportional hazards model is used for modelling the time to first veterinary treatment of clinical mastitis, including both genetic and environmental covariates. Sire effects were modelled as shared random components, and veterinary district was included as an environmental effect with prior spatial smoothing. A non-informative smoothing prior was assumed for the baseline hazard, and Markov chain Monte Carlo methods (MCMC) were used for inference. We propose a new measure of quality for sires, in terms of their posterior probability of being among the, say 10% best sires. The probability is an easily interpretable measure that can be directly used to rank sires. Estimating these complex probabilities is straightforward in an MCMC setting. The results indicate considerable differences between sires with regards to their daughters disease resistance. A regional effect was also discovered with the lowest risk of disease in the south-eastern parts of Norway.     

The influence of stream invertebrate composition at neighbouring sites on local assemblage composition

1. The composition of freshwater invertebrate assemblages at a location is determined by a range of physico‐chemical and biotic factors in the local environment, as well as larger‐scale spatial factors such as sources of recruits. We assessed the relative importance of the species composition of local neighbourhoods and proximal environmental factors on the composition of invertebrate assemblages. 2. Macroinvertebrate assemblages were sampled at 188 running‐water sites in the catchment of the River Rede, north‐east England. A total of 176 species were recorded. 3. Environmental data, in the form of 13 biotic and abiotic measurements that described stream physical structure, aquatic vegetation and water characteristics, were recorded for each site. Detrended correspondence analysis was then used to simplify nine of these stream environmental variables to create an index of stream structure. 4. The species composition of the invertebrate assemblages was related to the environmental variables, using an information theoretic approach. The impact of the species composition of neighbouring sites on each site was determined using Moran's I and autoregressive modelling techniques. 5. Species composition was primarily associated with water pH and stream structure. The importance of the species composition of neighbouring sites in determining local species assemblages differed markedly between taxa. The autoregressive component was low for Coleoptera, intermediate for Trichoptera and Plecoptera, and high for Ephemeroptera. 6. We hypothesise that the observed differences in the autoregressive component amongst these orders reflects variation in their dispersal abilities from neighbouring sites.