Land-cover change and human population trends in the greater Serengeti ecosystem from 1984–2003

The growth of human populations around protected areas accelerates land conversion and isolation, negatively impacting biodiversity and ecosystem function, and can be exacerbated by immigration. It is often assumed that immigration around protected areas is driven by attraction in the form of economic benefits, but in many cases, people may be pushed from their areas of origin toward protected areas. Mitigating the effects of immigration around protected areas necessitates understanding the actual mechanisms causing it, which can be aided by analysis of patterns of land-cover change. Our goal was to identify the reasons for human population growth and land-cover change around the protected areas in the greater Serengeti ecosystem (henceforth “the park”), and to relate agricultural conversion from 1984–2003 to trends in human demography. We found that conversion of natural habitats to agriculture was greatest closer to the park (up to 2.3% per year), coinciding with the highest rates of human population growth (3.5% per year). Agricultural conversion and population growth were greatest where there was less existing agriculture, and population density was lowest. Lack of unfarmed land farther from the park, coupled with greater poverty near the park, suggest that movement away from areas with high population densities and land scarcity was likely driving immigration near the park, where arable land was available. Our results are essential for conservation planning for one of Africa’s hallmark ecosystems, and should encourage further examination of population growth and land-cover trends near protected areas throughout the developing world.     

Natural outcrossing rate in Vernonia galamensis

Vernonia galamensis is a potential new industrial crop growing wild in Ethiopia. The seed oil is rich in vernolic acid, an epoxy fatty acid, which is of interest for oleochemical uses. Basic information on the reproductive system of Vernonia is still very limited. The amount of natural outcrossing was estimated at two locations in Ethiopia (Alemaya and Babile) using flower colour as a marker. Single plants with white flowers, which is a monogenic recessive trait, were planted in plots with normal pink flowers and the outcrossing rate was estimated from the frequency of pink‐flowered plants in the progeny of the white‐flowered plants. Estimates of the natural outcrossing rate ranged between individual plants from 3.5 to 16% at Alemaya and 2.5 to 12% at Babile. Vernonia galamensis can be classified as a mainly self‐pollinated species.     

N tracing models with a Monte Carlo optimization procedure provide new insights on gross N transformations in soils

¹⁵N tracing studies in combination with analyses via process-based models are the current “state-of-the-art” technique to quantify gross nitrogen (N) transformation rates in soils. A crucial component of this technique is the optimization algorithm which primarily decides how many model parameters can simultaneously be estimated. Recently, we published a Markov chain Monte Carlo (MCMC) method which has the potential to simultaneously estimate large number of parameters in ¹⁵N tracing models [Müller et al., 2007. Estimation of parameters in complex ¹⁵N tracing models by Monte Carlo sampling. Soil Biology & Biochemistry 39, 715-726].Here, we present the results of a reanalysis of datasets by Kirkham and Bartholomew [1954. Equations for following nutrient transformations in soil, utilizing tracer data. Soil Science Society of America Proceedings 18, 33-34], Myrold and Tiedje [1986. Simultaneous estimation of several nitrogen cycle rates using ¹⁵N: theory and application. Soil Biology & Biochemistry 18, 559-568] and Watson et al. [2000. Overestimation of gross N transformation rates in grassland soils due to non-uniform exploitation of applied and native pools. Soil Biology & Biochemistry 32, 2019-2030] using the MCMC technique. Analytical solutions such as the ones derived by Kirkham and Bartholomew [1954. Equations for following nutrient transformations in soil, utilizing tracer data. Soil Science Society of America Proceedings 18, 33-34] result in gross rates without uncertainties. We show that the analysis of the same data sets with the MCMC method provides standard deviations for gross N transformations. The standard deviations are further reduced if realistic data uncertainties are considered. Reanalyzing data by Myrold and Tiedje [1986. Simultaneous estimation of several nitrogen cycle rates using ¹⁵N: theory and application. Soil Biology & Biochemistry 18, 559-568] (Capac soil) resulted in a model fit similar to the one of the original analysis but with more precise estimates of gross N transformations. In addition, our analysis showed that small N transformations such as heterotrophic nitrification, which was neglected in the original analysis, could be quantified for this soil. Watson et al. [2000. Overestimation of gross N transformation rates in grassland soils due to non-uniform exploitation of applied and native pools. Soil Biology & Biochemistry 32, 2019-2030] provided evidence of a non-uniform exploitation of applied and native N that led to an overestimation of gross N transformations. Reanalyzing the data (CENIT soil, low N application) with the Müller et al. [2007. Estimation of parameters in complex ¹⁵N tracing models by Monte Carlo sampling. Soil Biology & Biochemistry 39, 715-726] model where oxidation was set to Michaelis-Menten kinetics resulted in a satisfactory fit between modeled and observed data, indicating that the observed artifact by Watson et al. [2000. Overestimation of gross N transformation rates in grassland soils due to non-uniform exploitation of applied and native pools. Soil Biology & Biochemistry 32, 2019-2030] was mainly due to inappropriate kinetic settings. Our study shows that the combination of a MCMC method with ¹⁵N tracing models is able to consider more complex and possibly more realistic models and kinetic settings to estimate gross N transformation rates and thus overcomes restriction of previous ¹⁵N tracing techniques.     

Choice of shrinkage parameter and prediction of genomic breeding values in elite maize breeding populations

Genomic selection (GS) is a promising alternative to marker‐assisted selection particularly for quantitative traits. In this study, we examined the prediction accuracy of genomic breeding values by using ridge regression best linear unbiased prediction in combination with fivefold cross‐validation based on empirical data of a commercial maize breeding programme. The empirical data is composed of 930 testcross progenies derived from 11 segregating families evaluated at six environments for grain yield and grain moisture. Accuracy to predict genomic breeding values was affected by the choice of the shrinkage parameter λ², by unbalanced family size, by size of the training population and to a lower extent by the number of markers. Accuracy of genomic breeding values was high suggesting that the selection gain can be improved implementing GS in elite maize breeding programmes.     

Hybrid breeding for biomass yield in winter triticale: II. Combining ability and hybrid prediction

Accurate hybrid prediction and knowledge about the relative contribution of general (GCA) and specific combining ability (SCA) are of utmost importance for efficient hybrid breeding. We therefore evaluated 91 triticale single-cross hybrids in field trials at seven environments for plant height, heading time, fresh biomass, dry matter content and dry biomass. Fresh and dry biomass showed the highest proportion (23%) of variance due to SCA. Prediction accuracies based on GCA were slightly higher than based on mid-parent values. Utilizing parental kinship information yielded the highest prediction accuracies when both parental lines have been tested in other hybrid combinations, but still moderate-to-low prediction accuracies for two untested parents. Thus, hybrid prediction for biomass traits in triticale is currently promising based on mid-parent values as emphasized by our simulation study, but can be expected to shift to GCA-based prediction with an increasing importance of GCA due to selection in hybrid breeding. Moreover, the performance of potential hybrids between newly developed lines can be predicted with moderate accuracy using genomic relationship information.     

Selection for <Emphasis Type="Italic">Phytophthora</Emphasis> field resistance in the F<Subscript>2</Subscript> generation of organic outdoor tomatoes

Tomatoes are the most important vegetable, globally as well as in Germany. Outdoor tomato production is seriously impaired due to increasing infections with evolving late blight (Phytophthora infestans) populations. Within organic agriculture, research is being conducted to develop regionally adapted and open pollinated cultivars of outdoor tomatoes with late blight field resistance. In the present experiment, three crosses, including wild, cocktail, and beefsteak tomatoes, were selected for field resistance against late blight in F₂ at one location per cross. The comparison of positive and negative selection in F₃ revealed the selection of single F₂ plants to be efficient in all three crosses. F₂ selection has proved to be a robust and efficient tool for breeding programs. The correlated response to selection in other traits, including yield, fruit weight, days to maturity, harvest period, and plant height, depended on the cross. It was evident that selection for desired traits combined with field resistance against late blight is promising, even in wide crosses. The most undesired attribute of wild tomatoes is the formation of shoots on leaves and in inflorescences. No correlation was observed between field resistance and shoot formation, allowing the selection of genotypes with improved field resistance and yield, but without morphological disadvantages.     

Interlinked fast and slow positive feedback loops drive reliable cell decisions

Positive feedback is a ubiquitous signal transduction motif that allows systems to convert graded inputs into decisive, all-or-none outputs. Here we investigate why the positive feedback switches that regulate polarization of budding yeast, calcium signaling, Xenopus oocyte maturation, and various other processes use multiple interlinked loops rather than single positive feedback loops. Mathematical simulations revealed that linking fast and slow positive feedback loops creates a "dual-time" switch that is both rapidly inducible and resistant to noise in the upstream signaling system.     

Digestion and Assimilation of the Free-living Nematode Panagrellus redivivus Fed to First Feeding Coregonid Larvae: Evidence from Histological and Isotopic Studies

The free-living nematode Panagrellus redivivus is a potential source of live food for first feeding fish. The digestion and assimilation of nematodes by larval fish were investigated with the aid of a histological and stable isotope approach. Larvae of whitefish Coregonus lavaretus were reared for 8 d with nematodes and compared with an unfed control. Nematodes were readily ingested by 3-d-old larvae. Different stages of nematode digestion could be observed in transverse sections of fish larvae sampled on Day 6 at regular intervals after feeding. Nematodes were produced on corn medium. In this way nematodes with a stable carbon isotope signature clearly different from the isotopic pattern of the fish larvae could be obtained. Stable carbon isotope signatures for lipids and lipid-free matter of fish larvae sampled on Days 2 and 8 after first feeding were clearly influenced by the stable isotopic pattern of the nematodes. The high acceptance of the nematodes by Coregonus lavaretus larvae and the early onset of digestion and nutrient retention positively confirm the potential of PanagreUus redivivus as a live food for first feeding fish larvae.     

Genetic engineering of cereal crop plants: a review

Summary Many aspects of basic and applied problems in plant biology can be investigated by transformation techniques. In dicotyledonous species, the ability to generate transgenic plants provides the tools for an understanding of plant gene function and regulation as well as for the directed transfer of genes of agronomic interest.For many dicotyledonous plants Agrobacterium tumefaciens can be routinely used to introduce foreign DNA into their genome. However, cereals seem to be recalcitrant to Agrobacterium-mediated transformation.In cereals, many efforts have been made in recent years to establish reliable transformation techniques. Several transformation techniques have been developed but to date only three methods have been found to be suitable for obtaining transgenic cereals: transformation of totipotent protoplasts, particle bombardment of regenerable tissues and, more recently, tissue electroporation. The current state of transformation methods used for cereals will be reviewed.