Using presence-absence data to establish reserve selection procedures that are robust to temporal species turnover

Utility of measuring abundance versus consistent occupancy in predicting biodiversity persistence

The primary goals of reserve selection are to represent all chosen units of biodiversity and to ensure their long-term persistence while minimizing costs. We considered two simple proxies of species persistence: a time series of point-count data to calculate abundance and a time series of presence-absence data to calculate permanence (a measure of consistent occupancy over time). Using two 10-year intervals of data from the North American Breeding Bird Survey, we compared the performance of each measure at predicting persistence 18 years later. For nonrare species, abundance and permanence predicted persistence similarly well. We performed complementarity-based reserve selections with data on species abundance and permanence (from 1970 to 1979) and then evaluated the effectiveness of the reserve networks at maintaining species populations and efficiency in land use (data from 1997 to 2006). Abundance proved a better predictor of future local persistence than permanence, which justifies the relatively larger financial and temporal costs of collecting a time series of point-count data to estimate abundance. If future extinction events were used as a measure of reserve-network effectiveness, the performance of abundance and permanence did not differ markedly. Nevertheless, when future abundance, which is a more sensitive measure of network effectiveness, was used, abundance was significantly better than permanence at selecting longer-term, high-quality, species-specific habitat but required larger reserves to do so.

Transaction costs economics of irreplaceability: ex ante and ex post evaluation of conservation networks' vulnerability to environmental shocks

The theoretical concept, "asset specificity," is applied to real data in the context of Danish nature conservation network planning in order to produce illustrative examples of an economic measure of the network's vulnerability to exogenous shocks to the species composition. Three different measures of asset specificity are quantified from the shadow value of eliminating a key species from the individual grid cells. This represents a novel approach and a different interpretation of the term, as it is conventionally used as a qualitative indicator in the transaction cost economics literature. Apart from supplementing existing cost measures with an indicator of risk associated with investments in protected areas, this study demonstrates how the estimation and interpretation of various asset specificity measures for geographical areas may qualify policy makers' choice of policy instrument in conservation planning. This differs from the more intuitive approach of basing policy instrument choice solely on the rarity of the species in a given area.

Value for money: protecting endangered species on Danish heathland

Biodiversity policies in the European Union (EU) are mainly implemented through the Birds and Habitats Directives as well as the establishment of Natura 2000, a network of protected areas throughout the EU. Considerable resources must be allocated for fulfilling the Directives and the question of optimal allocation is as important as it is difficult. In general, economic evaluations of conservation targets at most consider the costs and seldom the welfare economic benefits. In the present study, we use welfare economic benefit estimates concerning the willingness-to-pay for preserving endangered species and for the aggregate area of heathland preserved in Denmark. Similarly, we obtain estimates of the welfare economic cost of habitat restoration and maintenance. Combining these welfare economic measures with expected species coverage, we are able to estimate the potential welfare economic contribution of a conservation network. We compare three simple nonprobabilistic strategies likely to be used in day-to-day policy implementation: i) a maximum selected area strategy, ii) a hotspot selection strategy, and iii) a minimizing cost strategy, and two more advanced and informed probabilistic strategies: i) a maximum expected coverage strategy and ii) a strategy for maximum expected welfare economic gain. We show that the welfare economic performance of the strategies differ considerably. The comparison between the expected coverage and expected welfare shows that for the case considered, one may identify an optimal protection level above which additional coverage only comes at increasing welfare economic loss.

Tradeoffs of different types of species occurrence data for use in systematic conservation planning

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.

Abundance, spatial variance and occupancy: arthropod species distribution in the Azores

1. The positive abundance-occupancy and abundance-variance relationships are two of the most widely documented patterns in population and community ecology. 2. Recently, a general model has been proposed linking the mean abundance, the spatial variance in abundance, and the occupancy of species. A striking feature of this model is that it consists explicitly of the three variables abundance, variance and occupancy, and no extra parameters are involved. However, little is known about how well the model performs. 3. Here, we show that the abundance-variance-occupancy model fits extremely well to data on the abundance, variance and occupancy of a large number of arthropod species in natural forest patches in the Azores, at three spatial extents, and distinguishing between species of different colonization status. Indeed, virtually all variation about the bivariate abundance-occupancy and abundance-variance relationships is effectively explained by the third missing variable (variance in abundance in the case of the abundance-occupancy relationship, and occupancy in the case of the abundance-variance relationship). 4. Introduced species tend to exhibit lower densities, less spatial variance in these densities, and occupy fewer sites than native and endemic species. None the less, they all lie on the same bivariate abundance-occupancy and abundance-variance, and trivariate abundance-variance-occupancy, relationships. 5. Density, spatial variance in density, and occupancy appear to be all the things one needs to know to describe much of the spatial distribution of species.

Terrestrial avifauna of the Gippsland Plain and Strzelecki Ranges, Victoria, Australia: insights from Atlas data

The rate and spatial scale at which natural environments are being modified by human land-uses mean that a regional or national perspective is necessary to understand the status of the native biota. Here, we outline a landscape-based approach for using data from the ‘New Atlas of Australian Birds’ to examine the distribution and status of avifauna at a regional scale. We use data from two bioregions in south-east Australia – the Gippsland Plain and the Strzelecki Ranges (collectively termed the greater Gippsland Plains) – to demonstrate this approach. Records were compiled for 57 landscape units, each 10′ latitude by 10′ longitude (~270 km2) across the study region. A total of 165 terrestrial bird species was recorded from 1870 ‘area searches’, with a further 24 species added from incidental observations and other surveys. Of these, 108 species were considered ‘typical’ of the greater Gippsland Plain in that they currently or historically occur regularly in the study region. An index of species ‘occurrence’, combining reporting rate and breadth of distribution, was used to identify rare, common, widespread and restricted species. Ordination of the dataset highlighted assemblages of birds that had similar spatial distributions. A complementarity analysis identified a subset of 14 landscape units that together contained records from at least three different landscape units for each of the 108 ‘typical’ species. When compared with the 40 most common ‘typical’ species, the 40 least common species were more likely to be forest specialists, nest on the ground and, owing to the prevalence of raptors in the least common group, take prey on the wing. The future status of the terrestrial avifauna of the greater Gippsland Plains will depend on the extent to which effective restoration actions can be undertaken to ensure adequate representation of habitats for all species, especially for the large number of species of conservation concern.

Explaining the excess of rare species in natural species abundance distributions

The observation that a few species in ecological communities are exceptionally abundant, whereas most are rare, prompted the development of species abundance models. Nevertheless, despite the large literature on the commonness and rarity of species inspired by these pioneering studies, some widespread empirical patterns of species abundance resist easy explanation. Notable among these is the observation that in large assemblages there are more rare species than the log normal model predicts. Here we use a long-term (21-year) data set, from an estuarine fish community, to show how an ecological community can be separated into two components. Core species, which are persistent, abundant and biologically associated with estuarine habitats, are log normally distributed. Occasional species occur infrequently in the record, are typically low in abundance and have different habitat requirements; they follow a log series distribution. These distributions are overlaid, producing the negative skew that characterizes real data sets.