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Turbidity represents an obstacle to visual acuity underwater that might entail considerable consequences for multiple faunal traits. Morphology, especially eye size, could be adjusted to cope with reduced visibility in turbid water. Moreover, turbidity could interfere with colour signals or crypsis. Turbid water may simul-taneously impair the ability of prey and predators to detect each other, which may cause reduced speed, flight initiation distance, activity time, boldness, and exploratory behaviour by prey, In this work, we compared these traits in larvae of the newt Pleurodeles waltlfrom transparent and turbid ponds (around 100 and 300 FTU, respectively). Body size did not differ between pond types, but larvae from turbid ponds had smaller eyes, probably because visual acuity is structurally hindered by the environment. Colouration did not differ between transparent and turbid ponds on average, but it was more variable in larvae from transparent than turbid ponds, probably because transparent ponds trigger crypsis towards diverse background colours, whereas turbid ponds promote reduced pigmentation in all cases., In addition, behavioural traits were gauged in larvae from both types of ponds, in tests conducted in either transparent or turbid water. Speed was unaffected by turbidity, but larvae from turbid ponds increased their flight initiation distance when tested in transparent water. In all cases, larvae from transparent ponds were more active, and bolder in transparent water, and all larvae were more ex-ploratory when tested in transparent water (regardless of which pond type they came from)., Turbidity could trigger more cautious behaviours, probably because it makes predators harder to track. Alternatively, transparent water could stimulate a more expansive use of space through improved visibility, or it might encourage a more active search for shelter., These results shed light on the role of turbidity as a promotor of morphological and behavioural variability in amphibian larvae. These ecological consequences of water turbidity can be framed in terms of energy allocation and detectability in the context of predator–prey interactions.

[AIM]: Local suitability estimated with species distribution models (SDMs) could indicate the maximum abundance attainable by species. Often the abundance–suitability relationship is wedge-shaped because species do not reach their maximum potential in every suitable location. We explore how SDM performance, the amount of information lost when converting continuous abundance into presence–absence data and species prevalence influence the abundance–suitability relationship., [LOCATION] Undefined, [TIME PERIORD] Undefined, [MAJOR TAXA] Virtual species, [METHODS] Different abundance scenarios were simulated and converted into presence–absence maps. SDMs were parameterized using simulated predictors with different explanatory capacities. Quantile regressions were performed to characterize the abundance–suitability relationship. The strength of the wedge-shaped pattern was estimated using the difference in slopes between the 90th and 50th quantile lines, the goodness-of-fit of the 90th quantile regressions was calculated, and variation of both parameters was analysed as a function of SDM performance, prevalence and maximum abundance., [RESULTS] The degree of wedge shape was directly related to maximum abundance. It also depended on SDM quality; the higher the discrimination capacity, the less wedge-shaped the abundance–suitability relationship and higher the goodness-of-fit of the 90th quantile regressions. Prevalence exerted a significant effect on the shape of the relationship by influencing—together with maximum abundance—the extent of information loss., [MAIN CONCLUSIONS] SDMs cannot predict actual abundance even when the true determinants of abundance are included as predictors. Because presence–absence and abundance data are related but are different variables, wedge-shaped patterns are unavoidable. Discrimination capacity and prevalence affect the strength of the wedge-shaped pattern, so understanding their effects is necessary before any biological explanation is provided for the abundance–suitability relationship. Suitability maps derived from SDMs may transmit a false sense of precision at a local scale and should not be used as a perfect surrogate when abundance information is required.

[Aim]: Correlative species distribution models (SDMs) are subject to substantial spatio-temporal limitations when historical occurrence records of data-poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, offer a valuable contribution to underpin more physiologically informed predictions of biological invasions, the risk of which is often exacerbated by climate change. In this study we integrate physiological and human pressure data to address the uncertainties and limitations of correlative SDMs and to better understand, predict and manage biological invasions., [Location]: Western archipelagos of the Southern Ocean and martime Antarctica., [Taxon]: Eretmoptera murphyi (Chironomidae), invertebrates., [Methods]: Mahalanobis Distances were used for correlative SDM construction for a species with few records. A mechanistic SDM was built around different fitness components (larval survival and life stage progression) as a function of temperature. SDM predictions were combined with human activity levels in Antarctica to generate a site vulnerability index to the assess colonization risk of E. murphyi. Future scenarios of ecophysiological suitability were built around the warming trends in the region., [Results]: Both SDMs converge to predict high environmental suitability in the species' native and introduced ranges. However, the mechanistic model indicates a slightly larger invasive potential based on larval performance at different temperatures. Human activity levels across the Antarctic Peninsula play a key role in discerning site vulnerabilities. Niche suitability in Antarctica grows considerably under long-term climate scenarios, leading to a substantially higher invasive threat to the Antarctic ecosystems. In turn changing conditions result in growing physiological mismatches with the environment in the native range in South Georgia., [Main conclusions]: Long-term studies of invasion potential under climate benefit from integrating correlative predictions with physiological experiments, as the invasion potential varies depending on the area and the timescale examined. This study also highlights a conservation paradox whereby the accidental introduction of an insect represents a threat to the Antarctic ecoystems that contrasts with its endangered status at the native range.

Recently, the European Commission adopted a new strategy to halt the loss of biodiversity. Member states are expected to favor a more effective collection and redistribution of European Union (EU) funds under the current Multiannual Financial Framework for 2014–2020. Because of the large spatial variation in the distribution of biodiversity and conservation needs at the continental scale, EU instruments should ensure that countries with higher biodiversity values get more funds and resources for the conservation than other countries. Using linear regressions, we assessed the association between conservation investments and biodiversity values across member states, accounting for a variety of conservation investment indicators, taxonomic groups (including groups of plants, vertebrates, and invertebrates), and indicators of biodiversity value. In general, we found clear overall associations between conservation investments and biodiversity variables. However, some countries received more or less investment than would be expected based on biodiversity values in those countries. We also found that the extensive use of birds as unique indicators of conservation effectiveness may lead to biased decisions. Our results can inform future decisions regarding funding allocation and thus improve distribution of EU conservation funds.

[Aim]: While the contribution of abiotic factors to species distribution is well known, the geographic structure, if any, of biotic interactions within the species range is poorly understood. Most studies neglect biotic interactions when generating Species Distribution Models (SDMs) and projecting them, using future climatic scenarios, while others argue that biotic interactions may extend species tolerances to suboptimal abiotic conditions. Elucidating the extent to which biotic interactions play a role at a macro‐scale is challenging due to its inherent complexity. In this study, we characterized the independent contribution of prey abundance distributions on the Merlin's wintering distribution (Falco columbarius). Then, to examine the hypothesis that biotic interactions may counteract other suboptimal conditions, we tested for a differential importance of physical habitat characteristics and prey abundance distributions along the species’ wintering range., [Location]: Peninsular Spain., [Methods]: We modelled the Merlin's geographic distribution with Boosted Classification Trees as a function of environmental predictors (environmental model) and prey relative abundances (prey model), either separately or jointly (combined model). We tested whether the predictive success of environmental and prey models differ spatially., [Results]: Partialling out the variation into independent components we found that the prey abundance distributions explained the largest part of variation. Furthermore, the first four predictors with the highest contribution in our combined models were the abundances of prey species. Finally, our model predictions revealed a north‐to‐south increase in the importance of prey abundance distributions. Interestingly, our results suggest that biotic interactions can enable species to inhabit a wider range of suboptimal habitat conditions on range margins., [Main conclusions]: Relevant biotic interactions may not be always fully interchangeable with environmental surrogates. Abiotic factors and biotic interactions may shape species range limits and cores of distributions differently. Neglecting biotic interactions may compromise spatiotemporal transferability of SDMs, especially on species margins, and hence their applicability.

The Iberian Peninsula is a major European region of biodiversity, as it harbours more than 30% of European endemic species. Despite a number of studies having evaluated the ability of nature reserves to protect certain taxa, there is still a lack of knowledge on how Iberian endemic fauna are represented in these reserves. We detected biodiversity hotspots of Iberian endemicity and evaluated the effectiveness of the Natura 2000 network (N2000) in representing 249 endemic species from eight animal taxonomic groups (amphibians, mammals, freshwater fishes, reptiles, water beetles, butterflies, lacewings and dung beetles). We found that only the 10% of these Iberian endemic species are considered species of community interest (i.e. species included in the Annexes of the Habitats Directive). We conducted gap analyses and null models of representativeness in N2000. Generally, N2000 is effective in its representation of Iberian endemic fauna, although we detected species and few hotspots of endemism that were still not represented. It is necessary to declare a few new protected areas, thus enhancing N2000's effectiveness in the conservation of the Iberian endemic fauna. Although the aim of N2000 is to protect species listed in the Birds and Habitats Directives, the conservation status of endemic species from one of the most important areas of Europe in terms of biodiversity, could be also a concern for the European Union. Our results are useful in the context of the recent European Commission mandate calling for a ‘fitness check’ of the Birds and Habitats Directives. This approach could be also applicable to other regions with high value of endemicity.

The two non-native grasses that have established long-term populations in Antarctica (Poa pratensis and Poa annua) were studied from a global multidimensional thermal niche perspective to address the biological invasion risk to Antarctica. These two species exhibit contrasting introduction histories and reproductive strategies and represent two referential case studies of biological invasion processes. We used a multistep process with a range of species distribution modelling techniques (ecological niche factor analysis, multidimensional envelopes, distance/entropy algorithms) together with a suite of thermoclimatic variables, to characterize the potential ranges of these species. Their native bioclimatic thermal envelopes in Eurasia, together with the different naturalized populations across continents, were compared next. The potential niche of P. pratensis was wider at the cold extremes; however, P. annua life history attributes enable it to be a more successful colonizer. We observe that particularly cold summers are a key aspect of the unique Antarctic environment. In consequence, ruderals such as P. annua can quickly expand under such harsh conditions, whereas the more stress-tolerant P. pratensis endures and persist through steady growth. Compiled data on human pressure at the Antarctic Peninsula allowed us to provide site-specific biosecurity risk indicators. We conclude that several areas across the region are vulnerable to invasions from these and other similar species. This can only be visualized in species distribution models (SDMs) when accounting for founder populations that reveal nonanalogous conditions. Results reinforce the need for strict management practices to minimize introductions. Furthermore, our novel set of temperature-based bioclimatic GIS layers for ice-free terrestrial Antarctica provide a mechanism for regional and global species distribution models to be built for other potentially invasive species.

Modeling species' habitat requirements are crucial to assess impacts of global change, for conservation efforts and to test mechanisms driving species presence. While the influence of abiotic factors has been widely examined, the importance of biotic factors and biotic interactions, and the potential implications of local processes are not well understood. Testing their importance requires additional knowledge and analyses at local habitat scale. Here, we recorded the locations of species presence at the microhabitat scale and measured abiotic and biotic parameters in three different common lizard (Zootoca vivipara) populations using a standardized sampling protocol. Thereafter, space use models and cross-evaluations among populations were run to infer local processes and estimate the importance of biotic parameters, biotic interactions, sex, and age. Biotic parameters explained more variation than abiotic parameters, and intraspecific interactions significantly predicted the spatial distribution. Significant differences among populations in the relationship between abiotic parameters and lizard distribution, and the greater model transferability within populations than between populations are in line with effects predicted by local adaptation and/or phenotypic plasticity. These results underline the importance of including biotic parameters and biotic interactions in space use models at the population level. There were significant differences in space use between sexes, and between adults and yearlings, the latter showing no association with the measured parameters. Consequently, predictive habitat models at the population level taking into account different sexes and age classes are required to understand a specie's ecological requirements and to allow for precise conservation strategies. Our study therefore stresses that future predictive habitat models at the population level and their transferability should take these parameters into account.

© 2015 John Wiley & Sons Ltd. Aim: Quantifying species abundances is costly, especially when many species are involved. To overcome this problem, several studies have predicted local abundances (at the sample unit level) from species occurrence distribution models (SODMs), with differences in predictive performance among studies. Surprisingly, the ability of SODM to predict regional abundances of an entire area of interest has never been tested, despite the fact that it is an essential parameter for species conservation and management. We tested whether local and regional abundances of 21 terrestrial bird species could be predicted from SODMs in an exhaustively surveyed island, and examined the variation explained by species-specific traits. Location: La Palma Island, Canary Islands. Methods: We firstly assessed two types of algorithms representing the two main families of SODMs. We built models using presence/absence (boosted classification trees) and presence/background (MaxEnt) data as a function of relevant environmental predictors and tested their ability to predict the observed local abundances. The predicted probabilities of occurrence (Pi) were translated into animal numbers (n′) using the revisited equation ni′ = -ln(1-Pi), and we obtained regional abundances (for the whole island). Results: Predictive ability of presence/absence models was superior than that of MaxEnt. At the regional level, the observed average densities of all species were highly predictable from occurrence probabilities (R2 = 93.5%), without overall overestimation or underestimation. Interspecific variation in the accuracy of predicted regional density was largely explained (R2 = 73%), with habitat breath and variation in local abundance being the traits of greatest importance. Main conclusions: Despite uncertainties associated with local predictions and the idiosyncrasies of each species, our procedures enabled us to predict regional abundances in an unbiased way. Our approach provides