High focus on threatened species and habitats may undermine biodiversity conservation: Evidence from the northern Baltic Sea

Conservation policies and environmental impact assessments commonly target threatened species and habitats. Nevertheless, macroecological research provides reasons why also common species should be considered. We investigate the consequences of focussing solely on legally protected species and habitats in a spatial conservation planning context using a comprehensive, benthic marine data set from the northern Baltic Sea. Using spatial prioritization and surrogacy analysis, we show that the common approach in conservation planning, where legally listed threatened species and habitats are the focus of conservation efforts, could lead to poor outcomes for common species (and therefore biodiversity as a whole), allowing them to decline in the future. If conservation efforts were aimed solely at threatened species, common species would experience a loss of 62% coverage. In contrast, if conservation plans were based only on common species, threatened species would suffer a loss of 1%. Threatened species are rare and their ecological niches distinct, making them poor surrogates for biodiversity. The best results are achieved by unified planning for all species and habitats. The minimal step towards acknowledging common species in conservation planning would be the inclusion of the richness of common species, complemented by information on indicator species or species of high importance for ecosystem functioning. The trade-off between planning for rare and common species should be evaluated, to minimize losses to biodiversity.     

Birds as surrogates for biodiversity: An analysis of a data set from southern Québec

Surrogacy analysis consists of determining a set of biotic or environmental parameters which can be rapidly assessed in the field and reliably used to prioritize places for biodiversity conservation. Whether adequate surrogate sets exist remains an open and relatively unexplored question though its solution is central to the aims of conservation biology. This paper analyses the surrogacy problem by prioritizing places using surrogate lists and comparing these results with those obtained by using more comprehensive species lists. More specifically, it explores (i) the possibility of using bird distributions, which are often easily available, as surrogates for species at risk (endangered and threatened species), which are presumed to be an important component of biodiversity; and (ii) the methodological question of how spatial scale influences surrogate success. The data set analysed, from southern Québec, is one of the most complete biotic data sets available at the regional scale. Contrary to some previous analyses, the results obtained suggest that the surrogacy problem is potentially solvable.     

Effectiveness of Biodiversity Surrogates for Conservation Planning: Different Measures of Effectiveness Generate a Kaleidoscope of Variation

Conservation planners represent many aspects of biodiversity by using surrogates with spatial distributions readily observed or quantified, but tests of their effectiveness have produced varied and conflicting results. We identified four factors likely to have a strong influence on the apparent effectiveness of surrogates: (1) the choice of surrogate; (2) differences among study regions, which might be large and unquantified (3) the test method, that is, how effectiveness is quantified, and (4) the test features that the surrogates are intended to represent. Analysis of an unusually rich dataset enabled us, for the first time, to disentangle these factors and to compare their individual and interacting influences. Using two data-rich regions, we estimated effectiveness using five alternative methods: two forms of incidental representation, two forms of species accumulation index and irreplaceability correlation, to assess the performance of ‘forest ecosystems’ and ‘environmental units’ as surrogates for six groups of threatened species—the test features—mammals, birds, reptiles, frogs, plants and all of these combined. Four methods tested the effectiveness of the surrogates by selecting areas for conservation of the surrogates then estimating how effective those areas were at representing test features. One method measured the spatial match between conservation priorities for surrogates and test features. For methods that selected conservation areas, we measured effectiveness using two analytical approaches: (1) when representation targets for the surrogates were achieved (incidental representation), or (2) progressively as areas were selected (species accumulation index). We estimated the spatial correlation of conservation priorities using an index known as summed irreplaceability. In general, the effectiveness of surrogates for our taxa (mostly threatened species) was low, although environmental units tended to be more effective than forest ecosystems. The surrogates were most effective for plants and mammals and least effective for frogs and reptiles. The five testing methods differed in their rankings of effectiveness of the two surrogates in relation to different groups of test features. There were differences between study areas in terms of the effectiveness of surrogates for different test feature groups. Overall, the effectiveness of the surrogates was sensitive to all four factors. This indicates the need for caution in generalizing surrogacy tests.     

Biogeographical concordance and efficiency of taxon indicators for establishing conservation priority in a tropical rainforest biota

Prioritizing areas for conservation requires the use of surrogates for assessing overall patterns of biodiversity. Effective surrogates will reflect general biogeographical patterns and the evolutionary processes that have given rise to these and their efficiency is likely to be influenced by several factors, including the spatial scale of species turnover and the overall congruence of the biogeographical history. We examine patterns of surrogacy for insects, snails, one family of plants and vertebrates from rainforests of northeast Queensland, an area characterized by high endemicity and an underlying history of climate-induced vicariance. Nearly all taxa provided some level of prediction of the conservation values for others. However, despite an overall correlation of the patterns of species richness and complementarity, the efficiency of surrogacy was highly asymmetric; snails and insects were strong predictors of conservation priorities for vertebrates, but not vice versa. These results confirm predictions that taxon surrogates can be effective in highly diverse tropical systems where there is a strong history of vicariant biogeography, but also indicate that correlated patterns for species richness and/or complementarity do not guarantee that one taxon will be efficient as a surrogate for another. In our case, the highly diverse and narrowly distributed invertebrates were more efficient as predictors than the less diverse and more broadly distributed vertebrates.     

Measuring the effectiveness of regional conservation assessments at representing biodiversity surrogates at a local scale: A case study in Réunion Island (Indian Ocean)

In a context of scarce financial and human resources, the allocation of conservation efforts needs to be optimized. Our analysis attempts to draw conclusions on the integration of regional and local conservation assessments, specifically, with regard to the acquisition of fine‐scale data to complement the regional assessment. This study undertaken in Réunion Island (Indian Ocean) assessed how biodiversity surrogates targeted at a regional scale represented other biodiversity surrogates at a local scale. Biodiversity surrogates at both scales consisted of species, habitats and processes. Habitats and processes at regional scale were defined using a coarser scale of thematic resolution than at local scale. The surrogacy was tested in terms of incidental representation of local‐scale features in the regional assessments, and correlation of irreplaceability values between scales. Near‐minimum sets and irreplaceability values were generated using MARXAN software. Our results revealed that conservation targets for processes at local scale were never met incidentally, while threatened species and fragmented habitats were also usually under‐represented. More specifically, requiring only 12% of the local planning domain, the application of species as surrogates at regional scale was the least effective option at representing biodiversity features at local scale. In contrast, habitats at a coarse scale of thematic resolution achieved a significant proportion of conservation targets incidentally (67%) and their irreplaceability values were well correlated with the irreplaceability values of surrogates at local scale. The results highlighted that all three types of biodiversity surrogates are complementary for assessing overall biodiversity. Because of the cost of data acquisition, we recommended that the most efficient strategy to develop nested regional/local conservation plans is to apply habitats and processes at a coarse scale of thematic resolution at regional scale, and threatened species and degraded habitats at local scale, with their fine‐scale mapping limited to highly transformed areas.     

A test for assessment of saproxylic beetle biodiversity using subsets of “monitoring species”

In European forests, large scale biodiversity monitoring networks need to be implemented – networks which include components such as taxonomical groups that are at risk and that depend directly on forest stand structure. In this context, monitoring the species-rich group of saproxylic beetles is challenging. In the absence of sufficient resources to comprehensively survey a particular group, surrogates of species richness can be meaningful tools in biodiversity evaluations. In search of restricted subsets of species to use as surrogates of saproxylic beetle richness, we led a case study in Western Europe.Beetle data were compiled from 67 biodiversity surveys and ecological studies carried out from 1999 to 2010 with standardised trapping methods in France and Belgium. This large-scale dataset contains 642 forest plots, 1521 traps and 856 species. Twenty-two simplified species subsets were identified as potential surrogates, as well as the number of genera, a higher taxonomic level, taking into account, for each surrogate, the effort required for species identification, the practical monitoring experience necessary, the species conservation potential or the frequency of species occurrence. The performance of each surrogate was analyzed based on the following parameters: overall surrogacy (correlation between subset richness and total species richness), surrogacy vs. identification cost balance, surrogacy variation over a wide range of ecological conditions (forest type, altitude, latitude and bio-geographical area) and consistency with spatial scale. Ecological representativeness and ability to monitor rare species were supplementary criteria used to assess surrogate performance.The subsets consisting of the identifiable (or only easy-to-identify species) could easily be applied in practice and appear to be the best performing subsets, from a global point of view.The number of genera showed good prediction at the trap level and its surrogacy did not vary across wide environmental gradients. However, the subset of easy-to-identify species and the genus number were highly sensitive to spatial scale, which limits their use in large-scale studies. The number of rare species or the species richness of single beetle families (even the best single-family subset, the Cerambycidae) was very weak surrogates for total species richness. Conversely, the German list of monitoring species had high surrogacy, low identification costs and was not strongly influenced by the main geographical parameters, even with our French and Belgian data.In European-wide monitoring networks, such internationally validated subsets could be very useful with regard to the timing and cost-efficiency of field inventories.     

Incorporating evolutionary processes into conservation planning using species distribution data: a case study with the western Mediterranean herpetofauna

Aim To incorporate evolutionary processes into conservation planning using species distribution patterns and environmental gradients as surrogates for genetic diversity. Location Western Mediterranean Basin. Methods Distributions of 154 herpetological species were predicted using maximum entropy models, and groups of significantly co‐occurring species (biotic elements) were identified. Environmental gradients were characterized for the complete area and for the area covered by each biotic element, by performing a principal component analysis on the data matrix composed of nine environmental variables. The first two principal component analysis axes were classified into four categories each, and those categories were combined with each other resulting in an environmental classification with 16 categories. To identify priority conservation areas, biotic elements and environmental categories were used as surrogates for the neutral and adaptive components of genetic diversity, respectively. Priority areas for conservation were identified under three scenarios: (1) setting targets for species only; (2) setting targets for species and for each environmental category of the overall area; and (3) setting targets for each species and for each environmental category within each biotic element. Results Nine biotic elements were identified – four for the amphibians and five for the reptiles. Priority areas identified in the three scenarios were similar in terms of amount of area selected, but exhibited low spatial agreement. Main conclusions Prioritization exercises that integrate surrogates for evolutionary processes can deliver spatial priorities that are fairly different to those where only species representation is considered. While new methods are emerging to incorporate molecular data in conservation prioritization, it is unlikely to be enough data for enough taxa for this to be feasible in many regions. We develop an approach using surrogates for both the neutral and adaptive components of genetic diversity that may enhance biodiversity persistence and representation when molecular data are not available or geographically comprehensive.     

Scale dependency of two endangered charismatic species as biodiversity surrogates

Charismatic megafauna have been used as icons and financial drivers of conservation efforts worldwide given that they are useful surrogates for biodiversity in general. However, tests of this premise have been constrained by data limitations, especially at large scales. Here we overcome this problem by combining large-scale citizen-sourced data with intensive expert observations of two endangered charismatic species, Blakiston’s fish owl (forest specialist) and the red-crowned crane (wetland specialist). We constructed large-scale maps of species richness for 52 forest and 23 grassland/wetland bird species using hierarchical community modeling and citizen-sourced data at 1, 2, 5, and 10-km grid resolutions. We compared the species richness of forest and grassland/wetland birds between the breeding and non-breeding sites of the two charismatic birds at each of the four spatial resolutions, and then assessed the scale dependency of the biodiversity surrogates. Regardless of the habitat amounts, owl and crane breeding sites had higher forest and grassland/wetland bird species richness, respectively. However, this surrogacy was more effective at finer scales (1–2-km resolutions), which corresponds to the charismatic species’ home range sizes (up to 9.4 ± 2.0 km² for fish owls, and 3–4 km² for cranes). Species richness showed the highest spatial variations at 1–2-km resolutions. We suggest that the agreement of functional scales between surrogate species and broader biodiversity is essential for successful surrogacy, and that habitat conservation and restoration targeting multiple charismatic species with different specialties can complement to biodiversity conservation.     

Dynamic species co‐occurrence networks require dynamic biodiversity surrogates

In conservation it is inevitable that surrogates be selected to represent the occurrence of hard‐to‐find species and find priority locations for management. However, species co‐occurrence can vary over time. Here we demonstrate how temporal dynamics in species co‐occurrence influence the ability of managers to choose the best surrogate species. We develop an efficient optimisation formulation that selects the optimal set of complementary surrogate species from any co‐occurrence network. We apply it to two Australian datasets on successional bird responses to disturbances of revegetation and fire. We discover that a surprisingly small number of species are required to represent the majority of species co‐occurrences at any one time. Because co‐occurrence patterns are temporally dynamic, the optimal set of surrogates, and the number of surrogates required to achieve a desired surrogacy power, depend on sampling effort and the successional state of a system. Overlap in optimal sets of surrogates for representing 70% of co‐occurring species ranges from zero to 57% depending on when the surrogacy decision is made. Surrogate sets representing early successional communities over‐estimate the power of surrogacy decisions at later times. Our results show that in dynamic systems, optimal surrogates might be selected in different ways: 1) use short‐term monitoring to choose a larger number of static less‐informative surrogates; 2) use long‐term monitoring to choose a smaller number of static high‐power surrogates that may poorly represent early successional co‐occurrence; 3) develop adaptive surrogate selection frameworks with high short‐term and long‐term surrogacy power that update surrogate sets and capture temporal dynamics in species co‐occurrence. Our results suggest vigilance is needed when selecting surrogates for other co‐occurring species in dynamic landscapes, as selected surrogates from one time may have reduced effectiveness at a different time. Ultimately, decisions that fail to acknowledge dynamic species co‐occurrence will lead to uninformative or redundant surrogates.     

Improving biodiversity surrogates for conservation assessment: A test of methods and the value of targeted biological surveys

Aim

Conservation assessment and planning across extensive regions rely on the use of mapped or modelled surrogates because direct field‐based inventories of biodiversity rarely provide complete spatial coverage. Surrogates are assumed to represent spatial patterns in the distribution of biodiversity, yet the validity of this assumption is rarely evaluated. Here, we use data from new biological surveys targeting poorly known taxonomic groups across sparsely surveyed landscapes to test: (1) the performance of established and novel surrogates; and (2) the value of targeted survey data in further improving surrogate effectiveness.

Location

Continental Australia.

Methods

Surrogates were derived from either mapped land classifications (bioregions, vegetation types), or models of spatial turnover in biodiversity composition. Models were derived by linking best‐available biological observations to high‐resolution mapped climate, terrain and soil attributes using generalized dissimilarity modelling (GDM). The performance of surrogates was evaluated using survey data for eight biological groups collected as part of the Bush Blitz programme ( http://bushblitz.org ). For the GDM‐based surrogates, within‐ and cross‐taxon performance was first evaluated for models fitted to biological data available prior to Bush Blitz, and then for models enhanced through the addition of the Bush Blitz data.

Results

All of the tested surrogates performed significantly better than random across all eight biological groups. GDM‐based surrogates performed over 10% better on average than the best performing combination of mapped land classifications. The addition of Bush Blitz targeted data in GDM‐based surrogates led to further improvements in surrogate performance.

Main conclusions

Our results support continued investment in targeted biological survey programmes to enhance the performance of surrogates and ensure that surrogates represent a wider breadth of biodiversity. The strong performance of compositional turnover modelling, relative to mapped land classifications, suggests that this surrogate strategy deserves greater consideration in future conservation assessments and has potential for use in continental‐scale monitoring of biodiversity.

     

Monitoring marine macroalgae: the influence of spatial scale on the usefulness of biodiversity surrogates

Aim To examine the influence of spatial scale on the usefulness of commonly employed biodiversity surrogates in subtidal macroalgae assemblages. Location South‐west Australia. Methods The relationship between biodiversity surrogates and univariate and multivariate species‐level patterns was tested at multiple spatial scales, ranging from metres (between quadrats) to hundreds of kilometres (between regions), using samples collected from almost 2000 km of temperate coastline that represented almost 300 species. Biodiversity surrogates included commonly used cost‐effective alternatives to species‐level sampling, such as those derived from functional groups and from taxonomic aggregation. Results Overall, surrogates derived from taxonomic aggregation to genus or family level correlated strongly with species‐level patterns, although the family‐level surrogate was a less effective predictor of species richness at large spatial scales. Surrogates derived from aggregation to coarser taxonomic levels and functional groups performed poorly, while the effectiveness of a surrogate measure derived from canopy‐forming species improved with increasing spatial scale. Main conclusions A critical, but rarely examined, assumption of biodiversity surrogates is that the relationship between surrogate and species‐level patterns is consistent in both space and time, and across a range of spatial and temporal scales. As the performance of all surrogates was, to some degree, scale‐dependent, this work empirically demonstrated the need to consider the spatial extent and design of any biodiversity monitoring programme when choosing cost‐effective alternatives to species‐level data collection.     

Effectiveness of biological surrogates for predicting patterns of marine biodiversity: a global meta-analysis

The use of biological surrogates as proxies for biodiversity patterns is gaining popularity, particularly in marine systems where field surveys can be expensive and species richness high. Yet, uncertainty regarding their applicability remains because of inconsistency of definitions, a lack of standard methods for estimating effectiveness, and variable spatial scales considered. We present a Bayesian meta-analysis of the effectiveness of biological surrogates in marine ecosystems. Surrogate effectiveness was defined both as the proportion of surrogacy tests where predictions based on surrogates were better than random (i.e., low probability of making a Type I error; P) and as the predictability of targets using surrogates (R(2)). A total of 264 published surrogacy tests combined with prior probabilities elicited from eight international experts demonstrated that the habitat, spatial scale, type of surrogate and statistical method used all influenced surrogate effectiveness, at least according to either P or R(2). The type of surrogate used (higher-taxa, cross-taxa or subset taxa) was the best predictor of P, with the higher-taxa surrogates outperforming all others. The marine habitat was the best predictor of R(2), with particularly low predictability in tropical reefs. Surrogate effectiveness was greatest for higher-taxa surrogates at a <10-km spatial scale, in low-complexity marine habitats such as soft bottoms, and using multivariate-based methods. Comparisons with terrestrial studies in terms of the methods used to study surrogates revealed that marine applications still ignore some problems with several widely used statistical approaches to surrogacy. Our study provides a benchmark for the reliable use of biological surrogates in marine ecosystems, and highlights directions for future development of biological surrogates in predicting biodiversity.     

Annelids, arthropods or molluscs are suitable as surrogate taxa for selecting conservation reserves in estuaries

The urgent need to conserve aquatic biodiversity and the lack of spatial data on biodiversity has motivated conservation planners and researchers to search for more readily obtainable information that could be used as proxies or surrogates. The surrogate taxon approach shows promise in some aquatic environments (e.g. intertidal) but not others (e.g. coral reefs, temperate rocky reefs). Estuaries are transitional environments at the land–sea junction with a unique biodiversity, but are the most threatened of aquatic environments because of high levels of human use. The comparatively small numbers of conservation reserves means that estuarine biodiversity is poorly protected. Selecting additional conservation reserves within estuaries would be facilitated by the identification of a suitable surrogate that could be used in conservation planning. In one estuary in Southeast Australia, we evaluated separately the effectiveness of annelids, arthropods, and molluscs as surrogates for predicting the species richness, abundance, assemblage variation, and summed irreplaceability of other species and for coincidentally representing other species in networks of conservation reserves selected for each surrogate. Spatial patterns in the species richness and assemblage variation (but not summed irreplaceability) of each surrogate were significantly correlated with the spatial patterns of other species. The total abundance of annelids and the total abundance of arthropods were each significantly correlated with the total abundances of other species. Networks of conservation reserves selected to represent each surrogate performed significantly better than random selection in representing other species. The greatest number of non-surrogate species was coincidentally included in reserves selected for the group of mollusc species. We conclude that annelids and arthropods are effective surrogate taxa for identifying spatial variation in several measures of conservation value (species richness, abundance, assemblage variation) in estuaries. We also conclude that spatial data on annelids, arthropods or molluscs can be used to select networks of conservation reserves in estuaries. The demonstrated effectiveness of these surrogates should facilitate future conservation planning within estuaries.     

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.     

Limited transferability of stream‐fish distribution models among river catchments: reasons and implications

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Species prioritization for monitoring and management in regional multiple species conservation plans

Successful conservation plans are not solely achieved by acquiring optimally designed reserves. Ongoing monitoring and management of the biodiversity in those reserves is an equally important, but often neglected or poorly executed, part of the conservation process. In this paper we address one of the first and most important steps in designing a monitoring program – deciding what to monitor. We present a strategy for prioritizing species for monitoring and management in multispecies conservation plans. We use existing assessments of threatened status, and the degree and spatial and temporal extent of known threats to link the prioritization of species to the overarching goals and objectives of the conservation plan. We consider both broad and localized spatial scales to capture the regional conservation context and the practicalities of local management and monitoring constraints. Spatial scales that are commensurate with available data are selected. We demonstrate the utility of this strategy through application to a set of 85 plants and animals in an established multispecies conservation plan in San Diego County, California, USA. We use the prioritization to identify the most prominent risk factors and the habitats associated with the most threats to species. The protocol highlighted priorities that had not previously been identified and were not necessarily intuitive without systematic application of the criteria; many high‐priority species have received no monitoring attention to date, and lower‐priority species have. We recommend that in the absence of clear focal species, monitoring threats in highly impacted habitats may be a way to circumvent the need to monitor all the targeted species.     

Assessing extinction-risk of endangered plants using species distribution models: a case study of habitat depletion caused by the spread of greenhouses

The species distribution models (SDMs) are useful tools for investigating rare and endangered species as well as the environmental variables affecting them. In this paper, we propose the application of SDMs to assess the extinction-risk of plant species in relation to the spread of greenhouses in a Mediterranean landscape, where habitat depletion is one of the main causes of biodiversity loss. For this purpose, presence records of the model species (Linaria nigricans, a endemic and threatened species) and the greenhouses, a dataset of environmental variables, and different only presence-based modelling algorithms (Bioclim, Domain, GARP, MaxEnt and ENFA) were used to build SDMs for L. nigricans as well as for greenhouses. To evaluate the models a modified approach of the area-under-curve ROC was applied. Combining the most accurate models, we generated an extinction-risk model of L. nigricans populations, which enabled us to assess the sustainability of the most threatened populations. Our results show that is possible to model greenhouses spreading as a “biological invasion”. The procedure explained and used in this work is quite novel, and offers an objective spatial criterion intended for the management of natural resources and for the conservation of the biodiversity in areas threatened by habitat depletion processes as particular as greenhouses expansion.     

A Statistical Comparison between Less and Common Applied Models to Estimate Geographical Distribution of Endangered Species (<Emphasis Type="Italic">Felis margarita</Emphasis>) in Central Iran

Species distribution in space is important in habitat conservation and biodiversity protection, so gaining knowledge about species range would be worthwhile to rescue endangered species and plan conservation policy. This study evaluates and compares the performance of an array of Species Distribution Models (SDMs), namely RF, SVM, MaxEnt, GLMNET, and MARS, in predicting rare sand cat distribution across a large unprotected sand dune area in central Iran. Due to absence of reliable data and difficulties in recording the species itself, the SDMs were challenged by limited data including 55 absence (background) and 40 presence points as well as nine climatic and geological parameters that influence on species distribution, including humidity, maximum, minimum and mean temperature, precipitation, amount of sunshine, ground water level, aspect, and DEM. Moreover, each model was replicated 20 times and the statistics including TSS, AUC, COR and Deviance were computed. Then, based on computed statistics, the model performances were evaluated by TUKEY and ANOVA. Finally, ensemble map was obtained by weighted approach using AUC. The results of this study showed that complex machine learning methods, like SVM, RF, and MaxEnt are more outperformed to predict the distribution of rare species.     

Choice of baseline climate data impacts projected species' responses to climate change

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species‐climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040–2069, 2070–2099), using downscaled climate projections, and calculated species turnover and changes in species‐specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species‐specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site‐level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses.