Landsats Aff

Bio-D – Solvency – Vegetation

Remote sensing of vegetation allows understanding of ecosystem function
Kerr and Ostrovsky 3 (Jeremy T., and Marsha, both from the Dept. of Biology at U Ottawa, TRENDS in Ecology and Evolution Vol.18 No.6 June, p. 299-305, http://mysite.science.uottawa.ca/jkerr/pdf/tree2003.pdf, accessed 7-6-11, JMB)

Unlike field-based measurements of ecosystem function, which cannot easily be converted to estimates of function across entire ecosystems, remote sensing can provide simultaneous estimates of ecosystem function over wide areas. Remote sensing of vegetation offers promising and urgently needed measurements of ecosystem function at spatial scales that are most comparable to the extents of human-caused environmental change (Box 2). Net primary productivity (NPP) represents one aspect of integrated ecosystem function for which the normalized difference vegetation index (NDVI, Box 1) is used, particularly when refined with meteorological and soil data [16]. NDVI also correlates strongly with absorbed photosynthetically active radiation (APAR), which has helped lead to its common use as an estimator of aboveground NPP [17,18]. Similar to NPP, NDVI is sensitive to changes in both temperature and precipitation [16,19].

Bio-D – Solvency – Wildlife Reserves

Remote sensing key to maintaining wildlife reserves
Gillespie et al 8 (Thomas W., Giles M. Foody, Duccio Rocchini, Ana Paula Giorgi, Sassan Saatchi, California Center for Population Research, UCLA, December, Progress in Physical Geography; 32; 203, http://escholarship.org/uc/item/6rb716b0#page-1, accessed 7-6-11, JMB)

Remote sensing may also be valuable after the establishment of reserves, not least because competing pressures, such as those associated with economic development and population growth, place great stress on reserves and the surrounding lands (Nagendra eial.. 2004). The spatial coverage provided by remote sensing offers, however, the potential to monitor the effectiveness of protected areas, allowing comparisons of changes inside and outside of reserves to be evaluated (Southworth et at.. 2006; Wright ei al.. 2007). The ability to monitor the areas outside formally protected reserves is also attractive as these may have a major role to play in conserving biodiversity (Putz ei al., 2001). For example, even relatively severely logged forest outside a reserve may represent a significant resource for biodiversity conservation {Cannon ei al., 1998) and secondary forests are an often overlooked resource that may be managed to help reduce pressures elsewhere (Bawa and Seidler. 1998). Thus, actions inside and outside the protected areas are important, supporting the view that biodiversity conservation activities should be undertaken at the level or scale of the landscape (Nagendra and Gadgil. 1999b; Margules and Pressey. 2000; Potvin et al., 2000; Hannah era/.. 2002). This activity may benefit from remote sensing as its synoptic overview provides information on the entire landscape.

Bio-D – Solvency – Assessment

Remote sensing key to overall bio-d assessment
Gillespie et al 8 (Thomas W., Giles M. Foody, Duccio Rocchini, Ana Paula Giorgi, Sassan Saatchi, California Center for Population Research, UCLA, December, Progress in Physical Geography; 32; 203, http://escholarship.org/uc/item/6rb716b0#page-1, accessed 7-6-11, JMB)

Remote sensing may be a useful component to general biodiversity assessments, especially in providing data at appropriate spatial and temporal scales. For example, the biodiversity intactness index was proposed recently as a general indicator of the overall state of biodiversity to aid monitoring and dec is ion-ma king (Scholes and Biggs. 2005). Although there are concerns for its use. notably with the impacts of land degradation, remote sensing may be an important source of data for its derivation (Rouget et al., 2006).

Bio-D – Solvency/IL – Coral Reefs

Coral reefs in danger now – key to global bio-d – new data from Landsat key to manage them
Knudby 7 (Anders, Ellsworth LeDrew and Candace Newman, Dept. of Geography at U Waterloo, Progress in Physical Geography 31(4) pp. 421-434, EBSCO, JMB)

I Introduction Coral reefs are the most biodiverse marine ecosystems on the planet, estimated to harbour nearly one million species globally (Reaka-Kudla. 1997: 93). They can be places of extraordinary beauty, and are essential to the livelihoods of people who depend on them for food, coastal protection, tourism-based income and more (Birkeland, 1997: 2). However, the health of coral reefs is declining at a global scale (Wilkinson, 2004: 7), and the threats that have precipitated this decline range from overfishing, nutrient enrichment and coral diseases at the local scale to worldwide ocean warming, acidification, and sea-level rise. Most of these threats are expected to worsen their impact in the coming decades (Hoegh-Guldberg. 1999: Kleypasera/., 1999; Pittock, 1999), leaving an uncertain future for coral reefs. The decline of coral reefs, both past and projected, is of much more than academic interest: it is a serious threat to global biodiversity, an important part of our natural heritage. Because of the complexity of coral reef ecosystems and the multitude of threats, identification of the important threats and the necessary management for a given reef is difficult. Nevertheless, the global area of coral reef under some form of management is growing, and so is the need for information on which to base management measures (Wilkinson, 2004:!}. A manager of a protected area needs assessments of various aspects of reef health, which provide both a basis from which zonation plans and management regulations can be developed, and a baseline from which changes can be assessed. Reef health is an intangible concept, and is typically mapped and monitored using a number of proxies. Live coral cover is often used for practical reasons (Mumby etai., 2004b), and so is diversity or abundance of ecologically important or vulnerable species (Hodgson et ai, 2004). However, owing to the difficulties and expense associated with conducting extensive field surveys under water, spatially distributed data of the appropriate type and detail are rarely available. Remote sensing technologies have therefore been used to map coral reefs since the early days of Landsat (Smith et a/., 1975), and research into the use of remote sensing technology continues with the advent of new sensors and data processing methods (Kutser et ai., 2006). Classification of broad substrate types is now routinely possible in clear and shallow water, and water depth can be derived from a variety of data sources with varying accuracy. The interference of the water column, however, continues to pose problems for classification accuracy, and so do the similarities in spectral signatures between important substrate types. New technologies show promise for mapping aspects of coral reef health beyond substrate types, including water quality and reef structural complexity, thus providing complementary information for mapping of coral reef biodiversity. In this paper we aim to review coral reef biodiversity and its spatial distribution, the influence of habitat characteristics on biodiversity, and remote sensing approaches to mapping coral reef habitats, with a focus on mapping habitat variables known to influence biodiversity.