Spatial prioritization of conservation management

Abstract

We develop a high-resolution conservation prioritization analysis for New Zealand's rivers and streams that simultaneously consider both the present state (representation) of ecosystems, and the prioritization of management actions designed to mitigate ongoing human impacts on their expected future state (retention). As input we used information about the geographic distributions of river ecosystem groups and their compositional similarity, species richness, present condition as compared to their estimated pristine state, and upstream and downstream connectivity. Candidate management actions included riparian planting, establishment of wetlands on tile-drain outflows, and use of riparian buffer strips in plantation forests. The analysis, carried out at a 1-ha resolution for a study area of 22,000 km 2 in Southland, New Zealand, demonstrates a credible range of options for management intervention, particularly in lowland streams under serious threat from agricultural intensification. The proposed analysis can be replicated elsewhere for terrestrial, freshwater, or marine systems using publicly available software.

The history and future of fungi as biodiversity surrogates in forests

“…Therefore, in the lack of high resolution high coverage data on biodiversity, conservation decisions are usually based on some proxies of the conservation value of relevant areas. In an optimal planning situation, these proxies, preferably containing data on several different species groups (Westgate et al 2014), are downloaded in spatial conservation planning software and the decision is based on a systematic analysis involving factors like habitat quality, connectivity, complementarity and cost efficiency (Teeffelen et al 2006;Moilanen et al 2011). However, often the information needed for such an analysis is fragmentary or lacking, or time constraints are too strict for such a holistic approach.…”

Open data and the future of conservation biology

“…Sophisticated conservation planning modelling frameworks (such as MARXAN, Possingham et al 2000;Zonation, Moilanen et al 2005; or MARXAN with Zones, Watts et al 2009) have ex tended traditional prioritization methods by implementing multi-objective planning, addressing species-specific connectivity patterns and considering various socioeconomic factors while attempting to quantitatively maximize biodiversity representation targets (e.g. Beger et al 2010, Moilanen et al 2011. Such spatial conservation planning tools are open to the public, with software packages including manuals, tutorials and data for testing.…”

Clear consideration of costs, condition and conservation benefits yields better planning outcomes

“…Furthermore, combining multiple types of costs (such as condition as a cost proxy and monetary costs) into an analysis is only feasible where each cost has the same unit of measurement (Ban and Klein, 2009). There is currently limited scope to comprehensively incorporate estimates of both condition and cost in a spatial prioritisation exercise (but see Moilanen et al, 2011). and Klein et al (2013) are two studies that simultaneously consider estimates of condition alongside monetary costs, but they focus only on minimising selection of sites in poor condition, which may not always be the desired conservation objective.…”

“…The focus of conservation planning is shifting from solely prioritising for protected areas, and towards new objectives of identifying areas for targeted management to ameliorate negative impacts and to improve ecosystem health (Budiharta et al, 2014;Moilanen et al, 2011;Wilson et al, 2010). This includes targeting control of invasive species (Auerbach et al, 2014;Evans et al, 2011), reduction of poaching (Plumptre et al, 2014), or management of fire (Richards et al, 1999;Wilson et al, 2007).…”