Tomato: a crop species amenable to improvement by cellular and molecular methods

Tomato is a crop plant with a relatively small DNA content per haploid genome and a well developed genetics. Plant regeneration from explants and protoplasts is feasable which led to the development of efficient transformation procedures. In view of the current data, the isolation of useful mutants at the cellular level probably will be of limited value in the genetic improvement of tomato. Protoplast fusion may lead to novel combinations of organelle and nuclear DNA (cybrids), whereas this technique also provides a means of introducing genetic information from alien species into tomato. Important developments have come from molecular approaches. Following the construction of an RFLP map, these RFLP markers can be used in tomato to tag quantitative traits bred in from related species. Both RFLP's and transposons are in the process of being used to clone desired genes for which no gene products are known. Cloned genes can be introduced and potentially improve specific properties of tomato especially those controlled by single genes. Recent results suggest that, in principle, phenotypic mutants can be created for cloned and characterized genes and will prove their value in further improving the cultivated tomato.

Clarity or confusion?: problems in attributing large-scale ecological changes to anthropogenic drivers

Ways of reducing the drivers of global biodiversity loss and degradation of ecosystem services are needed more than ever before. Policy options must be based on the best evidence of the role of multiple driving forces. Increasingly, a significant part of the evidence base comes from attributing signals of biological change detected in large-scale analytical surveys to a range of possible causal factors. We highlight a number of subtle difficulties that can beset the challenge of detecting such correlative relationships. These are as follows: (1) The Modifiable Area Unit Problem. (2) Incomplete explanatory variable data. (3) Lack of control over the replication and crossing of driving variables. In most cases these problems can be avoided by more careful specification of the scientific question and application of relatively new analytical techniques. Ignoring them can lead to mis-specification of hypothesised driver–state–impact relationships and flawed conclusions as to the most important causes of change