Contrasting pathways of environmental or biotic degradation and their corresponding risk classifications under criteria C and D.

<p>(a) initially widespread and benign degradation, later increasing in severity. (b) severity and extent of degradation increase at similar rates. (c) localised but severe degradation, later becoming more widespread. Ecosystems that just fail to meet the thresholds for Vulnerable status (e.g. extremely severe (>80%) decline in environmental quality over 20–30% of distribution, or severe (>30%) decline over 70–80% of distribution) may be assigned Near Threatened (NT) status.</p

Protocol for assessing the risk of collapse of an ecosystem using proposed Red List criteria v2.0 (see <b>Table 3</b><b>)</b>

<p>.</p

Number of ecosystems assessed for each criterion and number for which each criterion determined overall status.

<p>Number of ecosystems assessed for each criterion and number for which each criterion determined overall status.</p

Examples of biotic variables potentially suitable for assessing the severity of disruption to biotic interactions under criterion D.

<p>Examples of biotic variables potentially suitable for assessing the severity of disruption to biotic interactions under criterion D.</p

Probability density functions for the population and ecosystem variables that measure proximity to the thresholds that define species extinction (A, B) and ecosystem collapse (C, D).

<p>The probability density functions represent uncertainty in the measurement of the variables. For species, the population threshold that defines extinction is known with certainty (e.g. zero abundance of a species, defined by the vertical line in A and B). In A, the estimated population is definitely greater than the extinction threshold, so there is no doubt that the species is extant. Alternatively, the probability that the abundance is above the threshold (the area under the curve) might be less than one (B), in which case the species could be extinct or extant. The shaded area is the probability that the species remains extant. For ecosystems, the x-axis could represent spatial distribution, number of species, water quality, etc. In contrast to species, uncertainty about the definition of ecosystem collapse leads to a range of possible values for this threshold (dashed box in C and D). The ecosystem variable is above this upper bound in some cases (C), so there is no doubt that the ecosystem persists. Alternatively, probable values for the ecosystem variable might intersect the uncertain threshold (D), in which case the ecosystem may be collapsed or not. In this case, there is some probability that the ecosystem parameter is above the upper bound of the threshold (shaded dark grey), which places a lower bound on the probability that the ecosystem persists (i.e. that it has not collapsed). There is an additional probability (pale grey) that the ecosystem parameter is above the threshold that depends on the amount of uncertainty in the threshold (i.e. width of the box). The sum of these two probabilities places an upper bound on the probability ecosystem persists. With further deterioration (E), the lower bound on the probability of ecosystem persistence is zero (no dark shading) and the upper bound is the pale shaded area.</p

Time scales for assessment of change under criteria A, C and D.

<p>Time scales for assessment of change under criteria A, C and D.</p

Biotic and abiotic variables for assessing functional decline in the Aral Sea ecosystem, their reference values when the ecosystem was in a functional state (between 1911 and 1960) and bounded thresholds that define the collapsed state, assuming collapse occurred between 1976 and 1989.

<p>Data from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062111#pone.0062111-Micklin1" target="_blank">[78]</a>. Further details in Appendix 2.5).</p

Assessing the Cost of Global Biodiversity and Conservation Knowledge

<div><p>Knowledge products comprise assessments of authoritative information supported by standards, governance, quality control, data, tools, and capacity building mechanisms. Considerable resources are dedicated to developing and maintaining knowledge products for biodiversity conservation, and they are widely used to inform policy and advise decision makers and practitioners. However, the financial cost of delivering this information is largely undocumented. We evaluated the costs and funding sources for developing and maintaining four global biodiversity and conservation knowledge products: The IUCN Red List of Threatened Species, the IUCN Red List of Ecosystems, Protected Planet, and the World Database of Key Biodiversity Areas. These are secondary data sets, built on primary data collected by extensive networks of expert contributors worldwide. We estimate that US$160 million (range: US$116–204 million), plus 293 person-years of volunteer time (range: 278–308 person-years) valued at US$14 million (range US$12–16 million), were invested in these four knowledge products between 1979 and 2013. More than half of this financing was provided through philanthropy, and nearly three-quarters was spent on personnel costs. The estimated annual cost of maintaining data and platforms for three of these knowledge products (excluding the IUCN Red List of Ecosystems for which annual costs were not possible to estimate for 2013) is US$6.5 million in total (range: US$6.2–6.7 million). We estimated that an additional US$114 million will be needed to reach pre-defined baselines of data coverage for all the four knowledge products, and that once achieved, annual maintenance costs will be approximately US$12 million. These costs are much lower than those to maintain many other, similarly important, global knowledge products. Ensuring that biodiversity and conservation knowledge products are sufficiently up to date, comprehensive and accurate is fundamental to inform decision-making for biodiversity conservation and sustainable development. Thus, the development and implementation of plans for sustainable long-term financing for them is critical.</p></div

Examples of variables potentially suitable for assessing the severity of environmental degradation under criterion C.

<p>Examples of variables potentially suitable for assessing the severity of environmental degradation under criterion C.</p

IUCN Red List criteria for ecosystems, version 2.0.

<p>These supercede an earlier set of four criteria <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062111#pone.0062111-Rodriguez1" target="_blank">[12]</a>. Refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062111#pone.0062111.s001" target="_blank">Appendix S1</a> for definitions of terms.</p>*<p>see text for guidance on selection of variable appropriate to the characteristic native biota of the ecosystem.</p>**<p>see text and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062111#pone-0062111-g006" target="_blank">Fig. 6</a> for explanation of relative severity of decline.</p