Economic and climate change pressures on biodiversity in southern Mediterranean coastal areas. MEDPRO Technical Report No. 24/February 2013

This paper establishes and measures key biodiversity and ecosystem health indicators and the number of world heritage sites in coastal areas at global level. It then estimates – econometrically – the indicators’ influence on the provision of tourism values through the marine ecosystem function as a harbour of biodiversity, and as a provider of amenity values and marine cultural identity. The report then focuses on the MEDPRO region, providing some estimates of the potential impact of climate change on these services for a given temperature increase scenario. Finally, the effect on ecosystemrelated tourism is computed for the four MEDPRO social economic scenarios. The analysis is enriched by some quantification of the potential costs of adaptation.

Shrubland ecosystem genetics and biodiversity : proceedings : Provo, UT, June 13-15, 2000 /

Papers from the 11th Wildland Shrub Symposium, held at the Bringham Young University Conference Center, Provo, Utah, June 13-15, 2000.

Linking ecosystems and biodiversity.

Shipping list no.: 92-240-P.

Aquaculture's Potential Impacts on Conservation of Wild Stocks and Biodiversity

Anderson theorizes that development of the aquaculture of a fish species (also captured in an open-access fishery) favours the conservation of its wild stocks, if competitive market conditions prevail. However, his theory is subject to significant limitations. While this is less so within his model, it is particularly so in an extended one outlined here. These other models allow for the possibility that aquaculture development can impact negatively on wild stocks thereby shifting the supply curve of the capture fishery, or raise the demand for the fish species subject both to aquaculture and capture. Such development can threaten wild fish stocks and their biodiversity. While aquaculture development could in principle have no impact on the biodiversity of wild stocks or even raise aquatic biodiversity overall, its impact in the long-term probably will be one of reducing aquatic diversity both in the wild and overall. The development of aquaculture does not automatically ensure long-term sustainability of fish and other aquatic supplies.

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.

Characterizing a tropical deforestation wave: a dynamic spatial analysis of a deforestation hotspot in the Colombian Amazon

Tropical deforestation is the major contemporary threat to global biodiversity, because a diminishing extent of tropical forests supports the majority of the Earth's biodiversity. Forest clearing is often spatially concentrated in regions where human land use pressures, either planned or unplanned, increase the likelihood of deforestation. However, it is not a random process, but often moves in waves originating from settled areas. We investigate the spatial dynamics of land cover change in a tropical deforestation hotspot in the Colombian Amazon. We apply a forest cover zoning approach which permitted: calculation of colonization speed; comparative spatial analysis of patterns of deforestation and regeneration; analysis of spatial patterns of mature and recently regenerated forests; and the identification of local-level hotspots experiencing the fastest deforestation or regeneration. The colonization frontline moved at an average of 0.84 km yr(-1) from 1989 to 2002, resulting in the clearing of 3400 ha yr(-1) of forests beyond the 90% forest cover line. The dynamics of forest clearing varied across the colonization front according to the amount of forest in the landscape, but was spatially concentrated in well-defined 'local hotspots' of deforestation and forest regeneration. Behind the deforestation front, the transformed landscape mosaic is composed of cropping and grazing lands interspersed with mature forest fragments and patches of recently regenerated forests. We discuss the implications of the patterns of forest loss and fragmentation for biodiversity conservation within a framework of dynamic conservation planning.

Ecological-economic modeling for biodiversity management: Potential, pitfalls, and prospects

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.