Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Robust optimization evaluation of reliance on locally produced foods

While local food production may be beneficial in terms of developing the local economy and reducing greenhouse gases from transportation, sustainability strategies focused on local food production may generate their own risks due to yield variability. We have developed a robust optimization (RO) model to determine the minimum amount of land (cropland and pasture) required to grow food items that would satisfy a local population’s (accounting for gender and age) calorie and nutrient needs. This model has been applied to Boone County, Missouri, which has a population of approximately 170,000. Boone County is 1790 km², with 16% of the land defined as cropland and 30% defined as pasture. The model includes 27 nutrients from 17 potential foods that could be produced: six fruits and vegetables, five grains and six animal-sourced foods. Yield estimates are based on the predominate methods of agriculture in the USA. We first run our model assuming no variability, using the midpoint yield estimates. Then, to quantify uncertainty in yield for different food types, we use historical yield data over 10 years to estimate this variability and run our RO model under these variability estimates. We compare the two model results to illustrate the impact of data uncertainty on meeting sustainable local food for communities. Solutions suggest that nutrition needs can be met for the Boone County population within the land area defined.     

Molecular composition of recycled organic wastes,as determined by solid-state 13C NMR and elemental analyses

Using solid state ¹³C NMR data and elemental composition in a molecular mixing model, we estimated the molecular components of the organic matter in 16 recycled organic (RO) wastes representative of the major materials generated in the Sydney basin area. Close correspondence was found between the measured NMR signal intensities and those predicted by the model for all RO wastes except for poultry manure char. Molecular nature of the organic matter differed widely between the RO wastes. As a proportion of organic C, carbohydrate C ranged from 0.07 to 0.63, protein C from <0.01 to 0.66, lignin C from <0.01 to 0.31, aliphatic C from 0.09 to 0.73, carbonyl C from 0.02 to 0.23, and char C from 0 to 0.45. This method is considered preferable to techniques involving imprecise extraction methods for RO wastes. Molecular composition data has great potential as a predictor of RO waste soil carbon and nutrient outcomes.     

Accelerated carbonation of different size fractions of bottom ash from RDF incineration

This paper investigates the effects of accelerated carbonation on the characteristics of bottom ash from refuse derived fuel (RDF) incineration, in terms of CO₂ uptake, heavy metal leaching and mineralogy of different particle size fractions. Accelerated aqueous carbonation batch experiments were performed to assess the influence of operating parameters (temperature, CO₂ pressure and L/S ratio) on reaction kinetics. Pressure was found to be the most relevant parameter affecting the carbonation yield. This was also found to be largely dependent on the specific BA fraction treated, with CO₂ uptakes ranging from ～4% for the coarse fractions to ～14% for the finest one. Carbonation affected both the mineralogical characteristics of bottom ash, with the appearance of neo-formation minerals, and the leaching behaviour of the material, which was found to be mainly related to the change upon carbonation in the natural pH of the ash.     

Understanding the chemical and mineralogical properties of the inorganic portion of MSWI bottom ash

This paper investigates the changes of mineralogical composition of bottom ash in the environment. The chemical and mineralogical bulk composition was determined by X-ray fluorescence (XRF) and X-ray powder diffraction (XRPD) Rietveld method. Single bottom ash particles were investigated by optical microscopy, scanning electron microscopy with quantitative energy-dispersive X-ray microanalysis (SEM/EDX) and electron probe micro analysis (EPMA). SEM/EDX and EPMA are valuable complement to bulk analysis and provide means for rapid and sensitive multi-elemental analysis of ash particles. The fresh bottom ash consists of amorphous (>30 wt.%) and major crystalline phases (>1 wt.%) such as silicates, oxides and carbonates. The mineral assemblage of the fresh bottom ash is clearly unstable and an aging process occurs by reaction towards an equilibrium mineral phase composition in the environmental conditions. The significant decrease of anhydrite and amorphous contents was observed in the aged bottom ash, leading to the formation of ettringite, hydrocalumite and rosenhahnite under atmospheric conditions. In the water-treated sample, the calcite contents increased significantly, but ettringite was altered by the dissolution and precipitation processes in part, to produce gypsum, while the remaining part reacted with chloride to form hydrocalumite. Gypsum and other Ca based minerals may take up substantial amounts of heavy metals and subsequently control leaching behaviour of bottom ash.     

Non-destructive quantification of water gradient in sludge composting with Magnetic Resonance Imaging

Sludge from a slaughter-house wastewater plant, and mixtures of bulking agent (crushed wood pallet) and sludge were studied by Nuclear Magnetic Resonance (NMR). The NMR spin–spin relaxation (T₂) and spin–lattice relaxation (T₁) signals for sludge, wet crushed wood pallet and mixtures of sludge and bulking agent were decomposed into three relaxation time components. Each relaxation time component was explained by a non-homogeneous water distribution on a microscopic length scale and by the porosity of the material. For all samples, the T₂ relaxation time value of each component was directly related to the dry matter content. The addition of wet crushed wood to sludge induced a decrease in the relaxation time, explained by water transfer between the sludge and the wood.Magnetic Resonance Imaging (MRI) and respirometric measurements were performed on sludge and wood mixtures. MR images of the mixtures were successfully obtained at different biodegradation states. Based on specific NMR measurements in an identified area located in the MRI cells, the results showed that grey levels of MR images reflected dry matter content. This preliminary study showed that MRI would be a powerful tool to measure water distribution in sludge and bulking agent mixtures and highlights the potential of this technique to increase the understanding of sludge composting.     

Effects of environmental parameters on the oxygen consumption of four marine invertebrates: a comparative factorial study

The oxygen consumption curves of two decapod crustaceans (Palaemon serratus, Penaeus monodon) and two prosobranch molluscs (Trunculariopsis trunculus, Nassarius mutabilis) have been detected in the entire pO₂ interval from 0 to 160 mmHg, under different conditions of temperature and salinity. From the experimental curves, physiological parameters such as the initial oxygen consumption velocity, the Q ₁₀ values and the oxygen independence indices have been measured. The latter parameters have been obtained using normalised plots which allow their better evaluation. The effects of temperature, salinity and oxygen partial pressure on the oxygen-consumption features have been studied using a factorial experimental plan which allows measurement of the effects of each experimental variable as well as the effects of synergistic interactions between different variables. Received: 27 March 2000 / Accepted: 13 November 2000     

Intranest relatedness and nestmate recognition in the meadow ant Formica pratensis (R.)

The impact of intranest relatedness on nestmate recognition was tested in a population of polydomous and monodomous nests of the mound-building ant Formica pratensis. Nestmate recognition was evaluated by testing aggression levels between 37 pairs of nests (n=206 tests). Workers from donor colonies were placed on the mounds of recipient nests to score aggressive interactions among workers. A total of 555 workers from 27 nests were genotyped using four DNA microsatellites. The genetic and spatial distances of nests were positively correlated, indicating budding and/or fissioning as spread mechanisms. Monodomous and polydomous nests did not show different aggression levels. Aggression behavior between nests was positively correlated with both spatial distance and intranest relatedness of recipient colonies, but not with genetic distance or intranest relatedness of donor colonies. Multiple regression analysis revealed a stronger effect of spatial distance than of genetics on aggression behavior in this study, indicating that the relative importance of environment and genetics can be variable in F. pratensis. Nevertheless, the positive regression between intranest relatedness of recipient colonies and aggression in the multiple analysis supports earlier results that nestmate recognition is genetically influenced in F. pratensis and further indicates that foreign label rejection most likely explains our data.