A regression tree-based method for integrating land-cover and land-use data collected at multiple scales

As data sets of multiple types and scales proliferate, it will be increasingly important to be able to flexibly combine them in ways that retain relevant information. A case in point is Amazonia, a large, data-poor region where most whole-basin data sets are limited to understanding land cover interpreted through a variety of remote sensing techniques and sensors. A growing body of work, however, indicates that the future state of much of Amazonia depends on the land use to which converted areas are put, but land use in the tropics is difficult to assess from remotely sensed data alone. An earlier paper developed new snapshots of agricultural land use in this region using a statistical fusion of satellite data and agricultural census data, an underutilized ancillary data source available across Amazonia. The creation of these land-use maps, which have the spatial detail of a satellite image and the attribute information of an agricultural census, required the development of a new statistical technique for merging data sets at different scales and of fundamentally different data types. Here we describe and assess this nonlinear technique, which reinterprets existing land cover classifications by determining what categories are most highly related to the polygon land-use data across the study area. Although developed for this region, the technique appears to hold broad promise for the systematic fusion of multiple data sets that are closely related but of different origins. The figures in the printed version of this article appear in black and white. Color figures are available from the author upon request.     

Ecological-Economic Modeling for Biodiversity Management: Potential, Pitfalls, and Prospects

Abstract:  Ecologists and economists both use models to help develop strategies for biodiversity management. The practical use of disciplinary models, however, can be limited because ecological models tend not to address the socioeconomic dimension of biodiversity management, whereas economic models tend to neglect the ecological dimension. Given these shortcomings of disciplinary models, there is a necessity to combine ecological and economic knowledge into ecological-economic models. It is insufficient if scientists work separately in their own disciplines and combine their knowledge only when it comes to formulating management recommendations. Such an approach does not capture feedback loops between the ecological and the socioeconomic systems. Furthermore, each discipline poses the management problem in its own way and comes up with its own most appropriate solution. These disciplinary solutions, however, are likely to be so different that a combined solution considering aspects of both disciplines cannot be found. Preconditions for a successful model-based integration of ecology and economics include (1) an in-depth knowledge of the two disciplines, (2) the adequate identification and framing of the problem to be investigated, and (3) a common understanding between economists and ecologists of modeling and scale. To further advance ecological-economic modeling the development of common benchmarks, quality controls, and refereeing standards for ecological-economic models is desirable.     

Studying crop sequences with CarrotAge,a HMM-based data mining software

We have developed a knowledge discovery system based on high-order hidden Markov models for analyzing spatio-temporal data bases. This system, named CarrotAge , takes as input an array of discrete data – the rows represent the spatial sites and the columns the time slots – and builds a partition together with its a posteriori probability. CarrotAge has been developed for studying the cropping patterns of a territory. It uses therefore an agricultural drench database, named Ter-Uti , which records every year the land-use category of a set of sites regularly spaced. The results of CarrotAge are interpreted by agronomists and used in research works linking agricultural land use and water management. Moreover, CarrotAge can be used to find out and study crop sequences in large territories, that is a main question for agricultural and environmental research, as discussed in this paper.     

Utility of Mitochondrial DNA Barcodes in Species Conservation

Abstract:  Molecular tools are a standard part of many conservation studies and can be informative at many different levels of analysis, although there are inherent limitations and strengths of different genes or parts of genes to inform specific questions. Animal DNA barcodes, 600- to 800-base-pair segments of the mitochondrial gene cytochrome oxidase I, have been proposed as a means to quantify global biodiversity. Although mitochondrial (mt) DNA has a long history of use at the species level, recent analyses suggest that the use of a single gene, particularly mitochondrial, is unlikely to yield data that are balanced, universally acceptable, or sufficient in taxonomic scope to recognize many species lineages. Mitochondrial and nuclear genomes have different patterns of evolution and modes of inheritance, which can result in very different assessments of biodiversity. The ramifications of choosing a particular definition of species (species concept) need to be carefully considered because current efforts have designated DNA barcodes as the universal species concept without demonstrating its superiority over preexisting concepts. The results of such a barcoding paradigm may include a failure to recognize significant portions of biodiversity or nuclear/mitochondrial mixed lineages and could spuriously focus conservation resources on populations with relatively minor mtDNA divergence. DNA barcodes are most likely to provide potentially useful information for groups that are already well studied, and such taxa do not constitute the majority of biodiversity or those in most need of research attention. DNA barcode-length sequences are an important source of data but, when used alone or out of context, may offer only a fraction of the information needed to characterize species while taking resources from broader studies that could produce information essential to robust and informed conservation decisions.     

A Global Indicator for Biological Invasion

Abstract:  "Trends in invasive alien species" is one of only two indicators of threat to biodiversity that form part of the Convention on Biological Diversity's (CBD) framework for monitoring progress toward its "2010 target" (i.e., the commitment to achieve by 2010 a significant reduction in the current rate of biodiversity loss). To date, however, there is no fully developed indicator for invasive alien species (IAS) that combines trends, derived from a standard set of methods, across species groups, ecosystems, and regions. Here we provide a rationale for the form and characteristics of an indicator of trends in IAS that will meet the 2010 framework goal and targets for this indicator. We suggest single and composite indicators that include problem-status and management-status measures that are designed to be flexible, readily disaggregated, and as far as possible draw on existing data. The single indicators at national and global scales are number of IAS and numbers of operational management plans for IAS. Global trends in IAS are measured as the progress of nations toward the targets of stabilizing IAS numbers and the implementation of IAS management plans. The proposed global indicator thus represents a minimum information set that most directly addresses the indicator objective and simultaneously aims to maximize national participation. This global indicator now requires testing to assess its accuracy, sensitivity, and tractability. Although it may not be possible to achieve the desired objective for a global indicator of biological invasion by 2010 as comprehensively as desired, it seems possible to obtain trend estimates for a component of the taxa, ecosystems, and regions involved. Importantly, current indicator development initiatives will also contribute to developing the mechanisms necessary for monitoring global trends in IAS beyond 2010.     

The Effect of Incremental Reserve Design and Changing Reservation Goals on the Long-Term Efficiency of Reserve Systems

Abstract:  Selecting reserve areas based on percentages, such as 10% or 12% of a bioregion, is common in conservation planning despite widespread admission that such percentages are arbitrary and likely to be inadequate for the conservation of all biodiversity. Reserve systems based on these relatively low percentage targets are likely to require expansion in the future, resulting in the assembly of reserve systems over many years (incremental reserve design). How then will incremental reserve design, such as increasing percentage targets over time, affect the long-term efficiency of marine reserve systems? We used South Australia as a case study to investigate how changing percentage targets affects the contribution of individual planning units to efficient reserve design. Selection frequency counts provided a measure of a planning unit's conservation value. For the majority of planning units, changing targets led to a change in their conservation value indicating, for example, that planning units identified as high-value sites at a low-percentage conservation target may be of lesser importance when targets are increased. Despite the variability in the value of individual planning units at different targets, there was no loss in efficiency from incremental design of reserve systems based on systematic methods compared with purpose-built reserve systems (i.e., the system is assembled in a single iteration). The exception was when incrementally designed systems were based on South Australia's existing marine reserve system—a system developed in an ad hoc method. The result was reserve systems that were less efficient, less compact, and larger in size. This suggests that systematic approaches have an important role for efficient reserve design when there is uncertainty about the target level of reservation .