Place prioritization for biodiversity content

The prioritization of places on the basis of biodiversity content is part of any systematic biodiversity conservation planning process. The place prioritization procedure implemented in the ResNet software package is described. This procedure is primarily based on the principles of rarity and complementarity. Application of the procedure is demonstrated with two analyses, one data set consisting of the distributions of termite genera in Namibia, and the other consisting of the distributions of bird species in the Islas Malvinas/Falkland Islands. The attributes that data sets should have for the effective and reliable application of such procedures are discussed. The procedure used here is compared to some others that are also currently in use.     

Place prioritization for biodiversity conservation using probabilistic surrogate distribution data

We analyse optimal and heuristic place prioritization algorithms for biodiversity conservation area network design which can use probabilistic data on the distribution of surrogates for biodiversity. We show how an Expected Surrogate Set Covering Problem (ESSCP) and a Maximal Expected Surrogate Covering Problem (MESCP) can be linearized for computationally efficient solution. For the ESSCP, we study the performance of two optimization software packages (XPRESS and CPLEX) and five heuristic algorithms based on traditional measures of complementarity and rarity as well as the Shannon and Simpson indices of α‐diversity which are being used in this context for the first time. On small artificial data sets the optimal place prioritization algorithms often produced more economical solutions than the heuristic algorithms, though not always ones guaranteed to be optimal. However, with large data sets, the optimal algorithms often required long computation times and produced no better results than heuristic ones. Thus there is generally little reason to prefer optimal to heuristic algorithms with probabilistic data sets.     

Solving the maximum representation problem to prioritize areas for the conservation of terrestrial mammals at risk in Oaxaca

Oaxaca, located in south‐west México within the Mesoamerican biodiversity hotspot, holds exceptionally high biodiversity for several taxa, including mammals. It has four decreed natural protected areas (NPAs) covering 5% of its total area, but only three of these, covering only 0.2% of the area, are strictly protected as National Parks. The current study develops ecological niche models for 183 terrestrial mammals for use as biodiversity surrogates in a systematic conservation planning exercise. Forty‐five of these species were selected on the basis of their being either endangered or threatened or otherwise listed under the Mexican Red List or because they were endemic to either Oaxaca or to Mexico. The niche models were constructed with a machine‐learning algorithm (GARP, Genetic Algorithm for Rule‐Set Prediction) and refined by restricting each model to sites with suitable vegetation and habitat patches contiguous with known occurrences of the species. If the entire predicted geographical distribution of each of the 45 species listed above is put under protection, the entire state of Oaxaca gets included. Therefore, we imposed different constraints on the maximum area that can be put under protection (5–30% of the area of Oaxaca) and selected nominal conservation area networks based on different percentage representation targets for the species’ modelled distributions based on their conservation status (10–100%). The area selection utilized a rarity‐ and complementarity‐based algorithm (in the ResNet software package). The goal was to have as many as possible of the 45 species at risk meet their specified representation targets in the budgeted area. The methods developed here combine ecological niche modelling and area prioritization algorithms for integrated conservation planning in a protocol that is suitable for other highly biodiverse regions.     

Operationalizing biodiversity for conservation planning

Biodiversity has acquired such a general meaning that people now find it difficult to pin down a precise sense for planning and policy-making aimed at biodiversity conservation. Because biodiversity is rooted in place, the task of conserving biodiversity should target places for conservation action; and because all places contain biodiversity, but not all places can be targeted for action, places have to be prioritized. What is needed for this is a measure of the extent to which biodiversity varies from place to place. We do not need a precise measure of biodiversity to prioritize places. Relative estimates of similarity or difference can be derived using partial measures, or what have come to be called biodiversity surrogates. Biodiversity surrogates are supposed to stand in for general biodiversity in planning applications. We distinguish between true surrogates, those that might truly stand in for general biodiversity, and estimator surrogates, which have true surrogates as their target variable. For example, species richness has traditionally been the estimator surrogate for the true surrogate, species diversity. But species richness does not capture the differences in composition between places; the essence of biodiversity. Another measure, called complementarity, explicitly captures the differences between places as we iterate the process of place prioritization, starting with an initial place. The relative concept of biodiversity built into the definition of complementarity has the level of precision needed to undertake conservation planning.     

Conservation of Freshwater Biodiversity: a Comparison of Different Area Selection Methods

The biodiversity of freshwater systems is endangered, especially in Mediterranean semiarid areas such as the south east of the Iberian Peninsula, whose rich and endemic biota is threatened by the development of surrounding land-crop irrigation. For this reason, the prioritization of areas for biodiversity conservation is an urgent target. In this study we used data records of water beetles from a province of the southeast of Spain for assessing priority areas for freshwater biodiversity conservation. We compare the performance of various area-selection methods, ranging from scoring procedures to complementarity-based algorithms, which are based on different criteria such as richness, rarity and vulnerability. The complementarity approaches were more efficient than methods using scoring or richness and rarity hotspots for representing conservation targets in a given number of areas and for identifying the minimum set of areas containing all species at least once. Within these, the richness-based algorithm was more efficient than rarity-based algorithm. Crucial target habitats for aquatic biodiversity conservation in the area studied are streams at medium altitude, hypersaline streams, and endorreic and karstic complexes.     

Use of optimization algorithms to prioritize protected areas in Mazandaran Province of Iran

A systematic approach for prioritization of protected areas is the use of artificial intelligence. This approach employs computer algorithms based on an objective function to identify the best network of areas to be protected. Site selection algorithms are commonly used to identify areas of high conservation value. This study used three types of heuristic algorithms (simulated annealing, greedy, rarity) to prioritize areas for protection in Mazandaran Province of Iran using Marxan software. The goal was to select a conservation network with the smallest possible area in which maximum protection targets are achievable. The effects of spatial scale, algorithm, and zone compactness were also examined. We found that the existing network of protected areas is inadequate to achieve conservation targets. The algorithm results provided the best areas for supplementation of the current network. The simulated annealing algorithm provided the most plausible results for all scenarios. These results can be used to modify the existing boundaries of the protected areas network and introduce new sites for protection of plant and animal species.     

Distribution Patterns and Conservation Perspectives of the Endemic Flora of Peloponnese (Greece)

An inventory of the endemic vascular plants of the Peloponnese (395 species and subspecies) has been created based on literature, herbarium and field data. Endemics?? distribution patterns, altitudinal distribution and habitat specificity were investigated. A rarity score for each endemic has been calculated based on its population size, geographic range and habitat specificity. The main mountainous areas of the Peloponnese are largely congruent to the hotspots of endemism. Altitudinal range and niche breadth of the endemics were positively correlated to their range size. The elevational gradient of the endemic species richness showed a hump-shaped pattern, in contrast to the monotonically decreasing pattern of total species richness. Endemic species were found to support boundary theory, while total species richness distribution followed the Rapoport??s elevational rule. The elevational distribution of the average rarity score and the average weighted threat of the endemics resulted in low values for mid-elevation intervals and increased values for low and high altitude areas, indicating that conservation efforts should focus on the two extremes of the elevational gradient. Area prioritization methods were applied using a rarity/complementarity based algorithm with two species weighting schemes. Their results were largely congruent confirming the significance of the main mountainous areas for the conservation of the endemics. Spatial overlap among selected grid cells using the rarity/complementarity analysis and Natura 2000 network was found to be low. Our results revealed the conservation importance of at least one new area located on Kythera Island.     

Global diversity of land planarians (Platyhelminthes, Tricladida, Terricola): a new indicator-taxon in biodiversity and conservation studies

Biodiversity conservation requires prioritization of areas for in situ conservation. In that perspective, the present study documents the global diversity of a component of the soil macrofauna, the land planarians, and concerns an exploratory analysis of their possible role as indicators of biodiversity. Diversity is described by three quantitative methods: (1) hotspots of species richness, selecting areas richest in species, (2) hotspots of range-size rarity, identifying areas richest in narrowly endemic species, and (3) complementarity, prioritizing areas according to their greatest combined species richness. The biodiversity measures of species richness and range-size rarity show a great correspondence in the identification of hotspots of diversity; both measures identify the following seven areas as the most biodiverse for land planarians: Sao Paulo, Florianopolis, western Java, Tasmania, Sri Lanka, North Island/New Zealand, and Sydney. It is discussed to what extent the results for the land planarians correspond with those obtained in other studies that assessed biodiversity hotspots for taxa on a global scale. It is noteworthy that land planarians identify a few global hotspots of diversity that generally do not feature, or only have low rankings, in other studies: New Zealand, southeastern Australia, and Tasmania.     

Priority areas for anuran conservation using biogeographical data: a comparison of greedy, rarity, and simulated annealing algorithms to define reserve networks in cerrado.

Spatial patterns in biodiversity variation at a regional scale are rarely taken into account when a natural reserve is to be established, despite many available methods for determining them. In this paper, we used dimensions of occurrence of 105 species of Anura (Amphibia) in the cerrado region of central Brazil to create a regional system of potential areas that preserves all regional diversity, using three different algorithms to establish reserve networks: "greedy", rarity, and simulated annealing algorithms. These generated networks based on complementarity with 10, 12, and 8 regions, respectively, widely distributed in the biome, and encompassing various Brazilian states. Although the purpose of these algorithms is to find a small number of regions for which all species are represented at least once, the results showed that 67.6%, 76.2%, and 69.5% of the species were represented in two or more regions in the three networks. Simulated annealing produced the smallest network, but it left out three species (one endemic). On the other hand, while the greedy algorithm produce a smaller solution, the rarity-based algorithm ensured that more species were represented more than once, which can be advantageous because it takes into consideration the high levels of habitat loss in the cerrado. Although usually coarse, these macro-scale approaches can provide overall guidelines for conservation and are useful in determining the focus for more local and effective conservation efforts, which is especially important when dealing with a taxonomic group such as anurans, for which quick and drastic population declines have been reported throughout the world.     

Applying conservation reserve design strategies to define ecosystem monitoring priorities

In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long‐time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well‐known approaches for conservation design, the “minimum set” and the “maximal coverage” problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot‐by‐plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long‐term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range‐rarity‐richness was balanced in terms of complementarity and representativeness, whereas its richness‐corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision‐making.     

Multi-Action Planning for Threat Management: A Novel Approach for the Spatial Prioritization of Conservation Actions

Planning for the remediation of multiple threats is crucial to ensure the long term persistence of biodiversity. Limited conservation budgets require prioritizing which management actions to implement and where. Systematic conservation planning traditionally assumes that all the threats in priority sites are abated (fixed prioritization approach). However, abating only the threats affecting the species of conservation concerns may be more cost-effective. This requires prioritizing individual actions independently within the same site (independent prioritization approach), which has received limited attention so far. We developed an action prioritization algorithm that prioritizes multiple alternative actions within the same site. We used simulated annealing to find the combination of actions that remediate threats to species at the minimum cost. Our algorithm also accounts for the importance of selecting actions in sites connected through the river network (i.e., connectivity). We applied our algorithm to prioritize actions to address threats to freshwater fish species in the Mitchell River catchment, northern Australia. We compared how the efficiency of the independent and fixed prioritization approach varied as the importance of connectivity increased. Our independent prioritization approach delivered more efficient solutions than the fixed prioritization approach, particularly when the importance of achieving connectivity was high. By spatially prioritizing the specific actions necessary to remediate the threats affecting the target species, our approach can aid cost-effective habitat restoration and land-use planning. It is also particularly suited to solving resource allocation problems, where consideration of spatial design is important, such as prioritizing conservation efforts for highly mobile species, species facing climate change-driven range shifts, or minimizing the risk of threats spreading across different realms.     

Prioritizing species for conservation planning

The efforts to protect biological diversity must be prioritized because resources for nature conservation are limited. Conservation prioritization can be based on numerous criteria, from ecological integrity to species representation, but in this review I address only species-level prioritization. Criteria used for species prioritization range from aesthetical to evolutionary considerations, but I focus on the aspects that are biologically relevant. I distinguish between two main aspects of diversity that are used as objectives: Maintenance of biodiversity pattern, and maintenance of biodiversity process. I identify two additional criteria typically used in species prioritization that serve for achieving the objectives: The species’ need of protection, and cost and effectiveness of conservation actions. I discuss how these criteria could be combined with either of the objectives in a complementarity-based benefit function framework for conservation prioritization. But preserving evolutionary process versus current diversity pattern may turn out to be conflicting objectives that have to be traded-off with each other, if pursued simultaneously. Although many reasonable criteria and methods exist, species prioritization is hampered by uncertainties, most of which stem from the poor quality of data on what species exist, where they occur, and what are the costs and benefits of protecting them. Surrogate measures would be extremely useful but their performance is still largely unknown. Future challenges in species prioritization lie in finding ways to compensate for missing information.     

Identifying areas of high importance for orchid conservation in east Macedonia (NE Greece)

The establishment of a network of reserves is of fundamental importance to the loss of biodiversity. Seven different area selection methods for the establishment of a reserve network were applied in the present study: (a) 5% cut-off value of the grid cells with the highest species richness or conservation value, (b) complementarity analysis using as criteria species richness or conservation value or rarest species richness, and (c) mixed complementarity analysis using as criteria species richness or conservation value. These methods were applied in the orchid taxa of east Macedonia. The conservation values of taxa were estimated on the basis of regional rarity, broad-scale rarity, and species specialization. The spatial overlap between the resulting networks and the Natura 2000 network of the study area was assessed. Furthermore, the efficiency of the latter network to protect the orchid taxa of the study area was examined. Our results suggest that: (a) a multiscale estimation of rarity is necessary for the unbiased estimation of species conservation values; (b) species specialization adds valuable ecological information to the assessment of taxa conservation values; (c) complementarity and mixed complementarity analyses on species richness or conservation value safeguard all the taxa of the region; (d) complementarity analysis on the basis of the richness of the rarest species safeguards all the rarest taxa, but not the total number of the remaining taxa; (e) the 5% cut-off value on species richness or conservation value fails to protect all the taxa of the region, including a large number of the rarest taxa; and (f) the Natura 2000 network, despite its large coverage in the study area, fails to safeguard all the taxa, including some of the rarest.     

Using a goal programming approach to design and evaluate protected areas for the conservation of multiple dimensions of biodiversity

The decline and loss of biodiversity provoked by human activities have caused ecologists and conservationists to center their attention on the design of conservation priority areas (PAs), focusing mainly on species conservation in terms of richness, rarity and/or vulnerability. However, biodiversity has multiple dimensions, evolutionary processes have recently been labeled the ‘missing component’ of conservation strategies, and increasingly more authors are suggesting that the ecological, evolutionary and historical aspects of biodiversity are key components of conservation planning. In this study we develop a prioritization system to design conservation PAs using the wild terrestrial mammals of the Iberian Peninsula as an example. We aim to contribute to the design of more suitable PAs by integrating ecological components of biodiversity (species richness, vulnerability and rarity), evolutionary aspects (accumulated genetic diversification) and historical information relevant to the study area. After selecting a set of biodiversity indicators, we applied a multi-objective technique (extended goal programming) to construct a combined index, where values in the top 90th percentile were then used to select the PAs. According to our most efficient and satisfactory results, some areas highlighted for their conservation are currently categorized as PAs, however, we found that it would be necessary to reconsider their extent, especially in northern Spain, where the historical aspects of biodiversity (the missing component) are more widely present. The need to determine PAs is unquestionable. However, it should also be a priority to move towards a model of sustainable and fair development.     

Whether including exotic species alters conservation prioritization: a case study in the Min River in southeastern China

Conservation practices from the perspective of functional diversity (FD) and conservation prioritization need to account for the impacts of exotic species in freshwater ecosystems. This work first simulated the influence of exotic species on the values of FD in a schemed mechanistic model, and then a practical case study of conservation prioritization was performed in the Min River, the largest river in southeastern China, to discuss whether including exotic species alters prioritization. The mechanistic model revealed that exotic species significantly altered the expected FD if the number of exotic species occupied 2% of the community. Joint species distribution modelling indicated that the highest FD occurred in the west, northwest and north upstreams of the Min River. Values of FD in 64.69% of the basin decreased after the exotic species were removed from calculation. Conservation prioritization with the Zonation software proved that if first the habitats of exotic species were removed during prioritization, 62.75% of the highest prioritized areas were shifted, average species representation of the endemic species was improved and mean conservation efficiency was increased by 7.53%. Existence of exotic species will significantly alter the metrics of biodiversity and the solution for conservation prioritization, and negatively weighting exotic species in the scope of conservation prioritization is suggested to better protect endemic species. This work advocates a thorough estimate of the impacts of exotic species on FD and conservation prioritization, providing complementary evidence for conservation biology and valuable implications for local freshwater fish conservation.     

Area prioritization for biodiversity conservation in Québec on the basis of species distributions: a preliminary analysis

Results are presented which prioritize areas for potential protection in Québec on the basis of biodiversity considerations. These results are relevant to the ongoing public discussion in Québec about designating new parks and refuges so that the province may fulfil its obligations to Canada's Endangered Spaces Campaign. The prioritization algorithm used in this analysis is based on rarity and complementarity. It attempts to sample biodiversity in as area-efficient a way as possible. The biodiversity surrogates used here comprise a subset of 743 species for which data on spatial distributions are publicly available; the analysis begins with 394 species at risk. It is shown that: (i) the existing network of protected areas in Québec does a poor job of protecting these biodiversity surrogates; (ii) adding adjacent areas to this network will not be the optimal way of protecting these biodiversity surrogates; (iii) many of the areas that have highest priority are in southern Québec, which has a high human population density; (iv) because of (iii), designating parks may not be economically or sociologically feasible and more adaptive alternative conservation plans will have to be devised; (v) coastal areas, riparian habitats, and other wetlands should have high priority for protection but are currently very inadequately represented in the reserve network; (vi) there is some reason for concern about the clear-cut logging of boreal forests in northern Québec; and (vii) the islands, Île d'Anticosti and the Îles-de-la-Madeleine, emerge as being of very significant conservation value and plans for the protection of areas on them should be an immediate goal for biodiversity conservation in Québec.     

Conservation of Neotropical carnivores under different prioritization scenarios: mapping species traits to minimize conservation conflicts

Aim To define priority sets of ecoregions that should be sufficiently covered in a reserve system to represent all Neotropical carnivores (Mammalia: Carnivora) under three distinct conservation scenarios. Location The Neotropical region. Methods We used broad‐scale biogeographical data of species distribution to define priority sets of ecoregions for conservation of carnivores and mapped four species traits (phylogenetic diversity, body size, rarity and extinction risk), which were used as constraints in prioritization analyses, based on the complementarity concept. We proposed three scenarios: a very vulnerable one, one of species persistence and another of lower human impact. We used the simulated annealing algorithm to generate ecoregion‐irreplaceability pattern and to find the combinations of ecoregions in each conservation scenario. Results We found that only 8% of Neotropical ecoregions are needed to represent all 64 carnivore species at least once. Rain forest ecoregions harbour a greater amount of carnivore phylogenetic diversity, whereas the tropical Andes hold large‐bodied carnivores. Western and southern Neotropical ecoregions have more rare species as well as higher threat levels. In the lower human‐impact set, 12 ecoregions were needed to represent all species. These coincide only partially with those attained by other prioritization scenarios. In the very vulnerable and in the species persistence scenario, 14 and 12 ecoregions were represented, respectively, and the congruence between either one and the lower human‐impact set was fairly low. Shared ecoregions are located in Mexico, Costa Rica, northern Amazon and western Chile. Main conclusions Our results highlight areas of particular interest for the conservation of Neotropical carnivores. The inclusion of evolutionary and ecological traits in conservation assessments and planning helps to improve reserve networks and therefore to increase the effectiveness of proposed priority sets. We suggest that conservation action in the highlighted areas is likely to yield the best return of investments at the ecoregion scale.     

Complementarity as a biodiversity indicator strategy

Richness, rarity, endemism and complementarity of indicator taxon species are often used to select conservation areas, which are then assumed to represent most regional biodiversity. Assessments of the degree to which these indicator conservation areas coincide across different taxa have been conducted on a variety of vertebrate, invertebrate and plant groups at a national scale in Britain, Canada, USA and South Africa and at a regional scale in Cameroon, Uganda and the USA. A low degree of spatial overlap among and within these selected indicator conservation areas has been demonstrated. These results tend to suggest that indicator conservation areas display little congruence across different taxa. However, some of these studies demonstrate that many conservation areas for indicator taxa capture a high proportion of non-target species. Thus it appears that indicator conservation areas might sample overall biodiversity efficiently. These indicator conservation areas may, however, exclude species essential for effective conservation, e.g. rare, endemic or endangered species. The present study investigated the value of indicator taxa as biodiversity surrogates using spatial congruence and representativeness of different indicator priority conservation areas. The conservation status of species excluded by the indicator approaches is also assessed. Indicator priority conservation areas demonstrate high land area requirements in order to fully represent non-target species. These results suggest that efficient priority area selection techniques must reach a compromise between maximizing non-target species gains and minimizing land-use requirements. Reserve selection procedures using indicator-based complementarity appear to be approaches which best satisfy this trade-off.     

Global assessment of marine biodiversity potentially threatened by offshore hydrocarbon activities

Increasing global energy demands have led to the ongoing intensification of hydrocarbon extraction from marine areas. Hydrocarbon extractive activities pose threats to native marine biodiversity, such as noise, light, and chemical pollution, physical changes to the sea floor, invasive species, and greenhouse gas emissions. Here, we assessed at a global scale the spatial overlap between offshore hydrocarbon activities and marine biodiversity (>25,000 species, nine major ecosystems, and marine protected areas), and quantify the changes over time. We discovered that two‐thirds of global offshore hydrocarbon activities occur in areas within the top 10% for species richness, range rarity, and proportional range rarity values globally. Thus, while hydrocarbon activities are undertaken in less than one percent of the ocean's area, they overlap with approximately 85% of all assessed species. Of conservation concern, 4% of species with the largest proportion of their range overlapping hydrocarbon activities are range restricted, potentially increasing their vulnerability to localized threats such as oil spills. While hydrocarbon activities have extended to greater depths since the mid‐1990s, we found that the largest overlap is with coastal ecosystems, particularly estuaries, saltmarshes and mangroves. Furthermore, in most countries where offshore hydrocarbon exploration licensing blocks have been delineated, they do not overlap with marine protected areas (MPAs). Although this is positive in principle, many countries have far more licensing block areas than protected areas, and in some instances, MPA coverage is minimal. These findings suggest the need for marine spatial prioritization to help limit future spatial overlap between marine conservation priorities and hydrocarbon activities. Such prioritization can be informed by the spatial and quantitative baseline information provided here. In increasingly shared seascapes, prioritizing management actions that set both conservation and development targets could help minimize further declines of biodiversity and environmental changes at a global scale.     

Spatial conservation priorities are highly sensitive to choice of biodiversity surrogates and species distribution model type

Pressure to conserve biodiversity with limited resources has led to increasing use of species distribution models (SDMs) for spatial conservation prioritization. Published spatial prioritization exercises often focus on well‐studied groups, with data compiled from on‐line databases of ad‐hoc collections. Conservation plans generally aim to protect all components of biodiversity, and it is implied that the species used in prioritization act as surrogates. Here, we assess the sensitivity of spatial priorities to model and surrogate choice using a case study from a fragmented agricultural area of south eastern Australia that is poorly represented in the national reserve system. We model the distributions of 30 species of bird, microbat and bee using two types of SDM; generalised linear models based on systematic surveys that yield presence and absence observations, and MaxEnt models based on biodiversity database records. Eight prioritization scenarios were tested using Zonation software, and were based on either the presence–background or presence–absence SDMs and combinations of surrogacy among the three taxa. We found low correlations between SDMs generated for the same species using different modelling frameworks (μ = 0.18, n = 26). Area under the receiver operating characteristic curve (AUC) estimates generated by MaxEnt were optimistic; on average 1.36 times higher than when tested against the systematic survey data. Conservation priorities were sensitive to the choice of surrogate and type of data used to fit SDMs, and though bats and birds formed moderately good surrogates for each other, there was less compelling evidence of surrogacy for bees. Because valid surrogacy is unlikely with most existing data sets, investment in high quality data for less‐surveyed groups prior to planning should still be a priority. If this is not possible, then it is advisable to analyse the sensitivity of conservation plans to the assumed surrogacy and quality of data available.