Nitrogen transfer within and between plants through common mycorrhizal networks (CMNs)

Mycorthizae play a critical role in nutrient capture from soils. Arbuscular mycorrhizae (AM) and ectomycorrhizae (EM) are the most important mycorrhizae in agricultural and natural ecosystems. AM and EM fungi use inorganic NH4+ and NO3-, and most EM fungi are capable of using organic nitrogen. The heavier stable isotope N-15 is discriminated against during biogeochemical and biochemical processes. Differences in N-15 (atom%) or delta(15)N (parts per thousand) provide nitrogen movement information in an experimental system. A range of 20 to 50% of one-way N-transfer has been observed from legumes to nonlegumes. Mycorrhizal fungal mycelia can extend from one plant's roots to another plant's roots to form common mycorrhizal networks (CMNs). Individual species, genera, even families of plants can be interconnected by CMNs. They are capable of facilitating nutrient uptake and flux. Nutrients such as carbon, nitrogen and phosphorus and other elements may then move via either AM or EM networks from plant to plant. Both N-15 labeling and N-15 natural abundance techniques have been employed to trace N movement between plants interconnected by AM or EM networks. Fine mesh (25similar to45 mum) has been used to separate root systems and allow only hyphal penetration and linkages but no root contact between plants. In many studies, nitrogen from N-2-fixing mycorrhizal plants transferred to non-N-2-fixing mycorrhizal plants (one-way N-transfer). In a few studies, N is also transferred from non-N-2-fixing mycorrhizal plants to N-2-fixing mycorrhizal plants (two-way N-transfer). There is controversy about whether N-transfer is direct through CMNs, or indirect through the soil. The lack of convincing data underlines the need for creative, careful experimental manipulations. Nitrogen is crucial to productivity in most terrestrial ecosystems, and there are potential benefits of management in soil-plant systems to enhance N-transfer. Thus, two-way N-transfer warrants further investigation with many species and under field conditions.

Survey-gap analysis in expeditionary research: where do we go from here?

Research expeditions into remote areas to collect biological specimens provide vital information for understanding biodiversity. However, major expeditions to little-known areas are expensive and time consuming, time is short, and well-trained people are difficult to find. In addition, processing the collections and obtaining accurate identifications takes time and money. In order to get the maximum return for the investment, we need to determine the location of the collecting expeditions carefully. In this study we used environmental variables and information on existing collecting localities to help determine the sites of future expeditions. Results from other studies were used to aid in the selection of the environmental variables, including variables relating to temperature, rainfall, lithology and distance between sites. A survey gap analysis tool based on 'ED complementarity' was employed to select the sites that would most likely contribute the most new taxa. The tool does not evaluate how well collected a previously visited site survey site might be; however, collecting effort was estimated based on species accumulation curves. We used the number of collections and/or number of species at each collecting site to eliminate those we deemed poorly collected. Plants, birds, and insects from Guyana were examined using the survey gap analysis tool, and sites for future collecting expeditions were determined. The south-east section of Guyana had virtually no collecting information available. It has been inaccessible for many years for political reasons and as a result, eight of the first ten sites selected were in that area. In order to evaluate the remainder of the country, and because there are no immediate plans by the Government of Guyana to open that area to exploration, that section of the country was not included in the remainder of the study. The range of the ED complementarity values dropped sharply after the first ten sites were selected. For plants, the group for which we had the most records, areas selected included several localities in the Pakaraima Mountains, the border with the south-east, and one site in the north-west. For birds, a moderately collected group, the strongest need was in the north-west followed by the east. Insects had the smallest data set and the largest range of ED complementarity values; the results gave strong emphasis to the southern parts of the country, but most of the locations appeared to be equidistant from one another, most likely because of insufficient data. Results demonstrate that the use of a survey gap analysis tool designed to solve a locational problem using continuous environmental data can help maximize our resources for gathering new information on biodiversity. (c) 2005 The Linnean Society of London.

Heuristic algorithm for computing reversal distance with multigene families via binary integer programming

Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE