Conservation Projects (ConPro) data base from The Nature Conservancy and others about the protected areas with analyzed Conservation Action Plans (CAP) before 2009 (Appendix 1) and after 2009 (Appendix 2)

It is widely recognized that climate change poses significant challenges to the conservation of biodiversity. The need of dealing with relatively rapid and uncertain environmental change calls for the enhancement of adaptive capacity of both biodiversity and conservation management systems. Under the hypothesis that most of the conventional biodiversity conservation tools do not sufficiently stimulate a dynamic protected area management, which takes rapid environmental change into account, we evaluated almost 900 of The Nature Conservancy's site-based conservation action plans. These were elaborated before a so-called climate clinic in 2009, an intensive revision of existing plans and a climate change training of the planning teams. We also compare these results with plans elaborated after the climate clinic. Before 2009, 20% of the CAPs employed the term "climate change" in their description of the site viability, and 45% identified key ecological attributes that are related to climate. 8% of the conservation strategies were directly or indirectly related to climate change adaptation. After 2009, a significantly higher percentage of plans took climate change into account. Our data show that many planning teams face difficulties in integrating climate change in their management and planning. However, technical guidance and concrete training can facilitate management teams learning processes. Arising new tools of adaptive conservation management that explicitly incorporate options for handling future scenarios, vulnerability analyses and risk management into the management process have the potential of further making protected area management more proactive and robust against change.

Supplemental Data - Bioremediation of polluted air from an industrial plant using rotating biofilter reactor-based technology

Two microbial isolates (HDB, Hydrogen-Degrading Bacteria) obtained from industrial wastewater were inoculated into the rotating biofilter reactor 'Biowheel 2.0' and tested for the ability to purify gaseous flows containing benzene and non-methane volatile organic compounds (NMVOCs) released at an industrial plant. Different classes of gaseous flow were tested, namely 'cold box', 'in shell', and 'mix', all of them associated with the industrial process of 'mold-casting'. A significant increase in Removal Efficiency (RE) was recorded for benzene and NMVOCs in the inoculated 'Biowheel 2.0' biofilter, compared to uninoculated control. For each type of gaseous flow, odor impact was evaluated in the inlet and outlet flows at the industrial plant, using the test panel method and electronic nose technology. A significant drop in the amount of Olfactometric Units (O.U.) m-3 occurred in the gaseous flows treated with the bacterial consortium. The reported data demonstrate the ability of the consortium to degrade hydrocarbons, revealing its potential for bioremediation of polluted air emissions occurring at industrial plants.

Spectral reflectance library of selected biotic and abiotic coral reef features in Heron Reef

Underwater spectral reflectance was measured for selected biotic and abiotic coral reef features of Heron Reef from June 25-30, 2006. Spectral reflectance's of 105 different benthic types were obtained in-situ. An Ocean Optics USB2000 spectrometer was deployed in an custom made underwater housing with a 0.5 m fiber-optic probe mounted next to an artificial light source. Spectral readings were collected with the probe(bear fibre) about 5 cm from the target to ensure that the target would fill the field of view of the fiber optic (FOV diameter ~4.4 cm), as well as to reduce the attenuating effect of the intermediate water (Roelfsema et al., 2006). Spectral readings included for one target included: 1 reading of the covered spectral fibre to correct for instrument noise, 1 reading of spectralon panel mounted on divers wrist to measure incident ambient light, and 8 readings of the target. Spectral reflectance was calculated for each target by first subtracting the instrument noise reading from each other reading. The corrected target readings were then divided by the corrected spectralon reading resulting in spectral reflectance of each target reading. An average target spectral reflectance was calculated by averaging the eight individual spectral reflectance's of the target. If an individual target spectral reflectance was visual considered an outlier, it was not included in the average spectral reflectance calculation. See Roelfsema at al. (2006) for additional info on the methodology of underwater spectra collection.