Principal factors controlling the species richness of European fens differ between habitat specialists and matrix‐derived species

Aim

We present the first continental‐scale study of factors controlling the species richness of groundwater‐fed fens, comparing land snails, vascular plants and bryophytes. We separately analyse two ecologically distinct groups differing in conservation value and colonization/extinction dynamics, that is habitat specialists, and matrix‐derived species. Considering the island‐like nature of fen habitats, we hypothesize larger differences in the species richness–environment relationships between habitat specialists and matrix‐derived species than among the taxonomic entities.

Location

Seven European regions

Methods

Richness was counted at 373 well‐preserved fens with undisturbed hydrology using the same protocols. Relationships between the species richness and water pH, waterlogging, climate and geography were explored by GLMs.

Results

Land snail richness responded mainly to water pH, regardless of habitat specialization. Richness of vascular plant and bryophyte specialists was strongly driven by geographical location of the sites, while that of matrix‐derived species was driven by waterlogging and water pH. The richness of matrix‐derived species of all taxa significantly increased with the decreasing waterlogging. Residual richness of specialists of all taxa decreased towards southern Europe.

Main conclusions

In island‐like terrestrial habitats, differences between specialists and matrix‐derived species may outweigh differences among taxa, unless there is one strong physiological determinant of species richness such as pH in land snails. The richness of specialists seems to be strongly related to difficult‐to‐measure regional factors such as historical frequency and connectivity of fen habitats. The richness of matrix‐derived species depends mainly on local conditions, such as pH and waterlogging, determining the degree of habitat contrast against the surrounding matrix. Sufficient waterlogging maintains a high representation of habitat specialists in fen communities, and disturbance of water regime may cause the increase in the number of matrix‐derived species and potentially trigger successional shifts towards non‐fen communities.

     

Predicting distributions,habitat preferences and associated conservation implications for a genus of rare fishes,seahorses (Hippocampus spp.)

Aim

To identify useful sources of species data and appropriate habitat variables for species distribution modelling on rare species, with seahorses as an example, deriving ecological knowledge and spatially explicit maps to advance global seahorse conservation.

Location

The shallow seas.

Methods

We applied a typical species distribution model (SDM), maximum entropy, to examine the utility of (1) two versions of habitat variables (habitat occurrences vs. proximity to habitats) and (2) three sources of species data: quality research‐grade (RG) data, quality‐unknown citizen science (CS) and museum‐collection (MC) data. We used the best combinations of species data and habitat variables to predict distributions and estimate species–habitat relations and threatened status for seahorse species.

Results

We demonstrated that using “proximity to habitats” and integrating all species datasets (RG, CS and MC) derived models with the highest accuracies among all dataset variations. Based on this finding, we derived reliable models for 33 species. Our models suggested that only 0.4% of potential seahorse range was suitable to more than three species together; seahorse biogeographic epicentres were mainly in the Philippines; and proximity to sponges was an important habitat variable. We found that 12 “Data Deficient” species might be threatened based on our predictions according to IUCN criteria.

Main conclusions

We highlight that using proper habitat variables (e.g., proximity to habitats) is critical to determine distributions and key habitats for low‐mobility animals; collating and integrating quality‐unknown occurrences (e.g., CS and MC) with quality research data are meaningful for building SDMs for rare species. We encourage the application of SDMs to estimate area of occupancy for rare organisms to facilitate their conservation status assessment.

     

Identifying the factors that determine the severity and type of alien bird impacts

Aim

To identify traits related to the severity and type of environmental impacts generated by alien bird species, in order to improve our ability to predict which species may have the most damaging impacts.

Location

Global.

Methods

Information on traits hypothesized to influence the severity and type of alien bird impacts was collated for 113 bird species. These data were analysed using mixed effects models accounting for phylogenetic non‐independence of species.

Results

The severity and type of impacts generated by alien bird species are not randomly distributed with respect to their traits. Alien range size and habitat breadth were strongly associated with impact severity. Predation impacts were strongly associated with dietary preference, but also with alien range size, relative brain size and residence time. Impacts mediated by interactions with other alien species were related to alien range size and diet breadth.

Main conclusions

Widely distributed generalist alien birds have the most severe environmental impacts. This may be because these species have greater opportunity to cause environmental impacts through their sheer number and ubiquity, but this could also be because they are more likely to be identified and studied. Our study found little evidence for an effect of per capita impact on impact severity.

     

Impacts of past habitat loss and future climate change on the range dynamics of South African Proteaceae

Aim

To assess how habitat loss and climate change interact in affecting the range dynamics of species and to quantify how predicted range dynamics depend on demographic properties of species and the severity of environmental change.

Location

South African Cape Floristic Region.

Methods

We use data‐driven demographic models to assess the impacts of past habitat loss and future climate change on range size, range filing and abundances of eight species of woody plants (Proteaceae). The species‐specific models employ a hybrid approach that simulates population dynamics and long‐distance dispersal on top of expected spatio‐temporal dynamics of suitable habitat.

Results

Climate change was mainly predicted to reduce range size and range filling (because of a combination of strong habitat shifts with low migration ability). In contrast, habitat loss mostly decreased mean local abundance. For most species and response measures, the combination of habitat loss and climate change had the most severe effect. Yet, this combined effect was mostly smaller than expected from adding or multiplying effects of the individual environmental drivers. This seems to be because climate change shifts suitable habitats to regions less affected by habitat loss. Interspecific variation in range size responses depended mostly on the severity of environmental change, whereas responses in range filling and local abundance depended mostly on demographic properties of species. While most surviving populations concentrated in areas that remain climatically suitable, refugia for multiple species were overestimated by simply overlying habitat models and ignoring demography.

Main conclusions

Demographic models of range dynamics can simultaneously predict the response of range size, abundance and range filling to multiple drivers of environmental change. Demographic knowledge is particularly needed to predict abundance responses and to identify areas that can serve as biodiversity refugia under climate change. These findings highlight the need for data‐driven, demographic assessments in conservation biogeography.

     

Use of predictive habitat modelling to assess the distribution and extent of the current protection of ‘listed’ deep‐sea habitats

Aim

To demonstrate the application of predictive species distribution modelling methods to habitat mapping and assessment of percentage area‐based conservation targets.

Location

The NE Atlantic deep sea (UK and Irish extended continental shelf limits).

Methods

MaxEnt modelling of three listed habitats (Lophelia pertusa (Linnaeus, 1758) reef (LpReef), Pheronema carpenteri (WyvilleThomson, 1869) aggregations (PcAggs) and Syringammina fragilissima (Brady, 1883) aggregations (SfAggs)), with some pre‐selection of variables by generalized additive modelling. Models are validated using repeated 70/30 build/test data splits using AUC and threshold‐dependent assessment methods. Predicted distribution maps are used to assess the adequacy of existing area closures for the protection of listed habitats and to assess percentage representation of each community within existing MPA networks.

Results

Model performances are rated as fair (LpReef), excellent (PcAggs) and good (SfAggs). Current closures are focused on the protection of cold‐water coral reef and incidentally capture some SfAggs suitable environments, but largely fail to protect PcAggs. Considering the wider network of MPAs in the study region, approximately 23% (LpReef), 2% (PcAggs) and 6% (SfAggs) of the area predicted as suitable for each habitat respectively is contained within an MPA.

Main conclusions

To date, decisions on area closures for the protection of ‘listed’ deep‐sea habitats have been based on maps of recorded presence of species that are taken as being indicative of that habitat. Predictive habitat modelling may provide a useful method of better estimating the extent of listed habitats, providing direction for future MPA establishment and a means of assessing MPA network effectiveness against politically set percentage targets. Given the coarse resolution of the model, percentages should be taken as maximal figures, with habitat occurrence likely to be less prevalent in reality.

     

Multispecies assessment of core areas and connectivity of desert carnivores in central Iran

Aim

Central Iran is a priority area for biodiversity conservation, which is threatened by encroachment on core habitats and fragmentation by roads. The goal of this study was to identify core areas and connectivity corridors for a set of desert carnivores by predicting habitat suitability and calculating resistant kernel, factorial least‐cost path modelling and graph network indices.

Location

Iran.

Methods

We used an ensemble model (EM) of habitat suitability methods to predict the potential habitats of leopard, cheetah, caracal, wild cat, sand cat and grey wolf and used resistant kernel and factorial least‐cost path modelling to identify important core habitats and corridors between patches. We also used a graph network analysis to quantify the importance of each core patch to landscape connectivity.

Results

Potential habitats of the studied carnivores appeared to be strongly influenced by prey density, annual precipitation, topographical roughness, shrubland density and anthropogenic factors. Most of the core patches were covered by protected areas and no‐hunting areas. This may be attributed to the relatively high resistance outside protected areas leading to isolated occupied patches. Patch importance to connectivity was significantly correlated with patch extent, density of dispersing individuals and probability of occurrence in the core patch.

Main conclusions

Our findings revealed that prey abundance in core habitat is critically important, and has higher influence than habitat area per se. In addition, our analysis provided the first map of landscape connectivity for multiple species in Iran and revealed that conserving these species requires integrated landscape‐level management to reduce mortality risk and protect core areas and linkages among them. These results will assist the development of multispecies conservation strategies to protect core areas for carnivores.

     

Moving from representation to persistence: The capacity of Australia's National Reserve System to support viable populations of mammals

Aim

Species require sufficiently large and connected areas of suitable habitat to support populations that can persist through change. With extensive alteration of unprotected natural habitat, there is increasing risk that protected areas (PAs) will be too small and isolated to support viable populations in the long term. Consequently, this study addresses the urgent need to assess the capacity of PA estates to facilitate species persistence.

Location

Australia.

Methods

We undertake the first assessment of the capacity of the Australian National Reserve System (NRS) to protect 90 mammal species in the long term, given the size and distribution of individual PAs across the landscape relative to species’ habitat and minimum viable area (MVA) requirements and dispersal capabilities.

Results

While all mammal ranges are represented within the NRS, the conservation capacity declined notably when we refined measures of representation within PAs to include species’ habitat and area requirements. The NRS could not support any viable populations for between three and seven species, depending on the MVA threshold used, and could support less than 10 viable populations for up to a third of the species. Planning and managing PAs for persistence emerged as most important for species with large MVA requirements and limited dispersal capabilities.

Main conclusions

The key species characteristics we identify can help managers recognize species at risk within the current PA estate and guide the types of strategies that would best reduce this risk. We reveal that current representation‐based assessments of PA progress are likely to overestimate the long‐term success of PA estates, obscuring vulnerabilities for many species. It is important that conservation planners and managers are realistic and explicit regarding the role played by different sizes and distributions of PAs, and careful in assuming that the representation of a species within a PA equates to its long‐term conservation.

     

The importance of water‐retaining features for biodiversity on artificial intertidal coastal defence structures

Aim

Artificial coastal defence structures are proliferating in response to rising and stormier seas. These structures provide habitat for many species but generally support lower biodiversity than natural habitats. This is primarily due to the absence of environmental heterogeneity and water‐retaining features on artificial structures. We compared the epibiotic communities associated with artificial coastal defence structures and natural habitats to ask the following questions: (1) is species richness on emergent substrata greater in natural than artificial habitats and is the magnitude of this difference greater at mid than upper tidal levels; (2) is species richness greater in rock pools than emergent substrata and is the magnitude of this difference greater in artificial than natural habitats; and (3) in artificial habitats, is species richness in rock pools greater at mid than upper tidal levels?

Location

British Isles.

Methods

Standard non‐destructive random sampling compared the effect of habitat type and tidal height on epibiota on natural rocky shores and artificial coastal defence structures.

Results

Natural emergent substrata supported greater species richness than artificial substrata. Species richness was greater at mid than upper tidal levels, particularly in artificial habitats. Rock pools supported greater species richness than emergent substrata, and this difference was more pronounced in artificial than natural habitats. Rock pools in artificial habitats supported greater species richness at mid than upper tidal levels.

Main conclusions

Artificial structures support lower biodiversity than natural habitats. This is primarily due to the lack of habitat heterogeneity in artificial habitats. Artificial structures can be modified to provide rock pools that promote biodiversity. The effect of rock pool creation will be more pronounced at mid than upper tidal levels. The challenge now is to establish at what tidal height the effect of pools becomes negligible and to determine the rock pool dimensions for optimum habitat enhancement.

     

Modelling the distribution and compositional variation of plant communities at the continental scale

Aim

We investigate whether (1) environmental predictors allow to delineate the distribution of discrete community types at the continental scale and (2) how data completeness influences model generalization in relation to the compositional variation of the modelled entities.

Location

Europe.

Methods

We used comprehensive datasets of two community types of conservation concern in Europe: acidophilous beech forests and base‐rich fens. We computed community distribution models (CDMs) calibrated with environmental predictors to predict the occurrence of both community types, evaluating geographical transferability, interpolation and extrapolation under different scenarios of sampling bias. We used generalized dissimilarity modelling (GDM) to assess the role of geographical and environmental drivers in compositional variation within the predicted distributions.

Results

For the two community types, CDMs computed for the whole study area provided good performance when evaluated by random cross‐validation and external validation. Geographical transferability provided lower but relatively good performance, while model extrapolation performed poorly when compared with interpolation. Generalized dissimilarity modelling showed a predominant effect of geographical distance on compositional variation, complemented with the environmental predictors that also influenced habitat suitability.

Main conclusions

Correlative approaches typically used for modelling the distribution of individual species are also useful for delineating the potential area of occupancy of community types at the continental scale, when using consistent definitions of the modelled entity and high data completeness. The combination of CDMs with GDM further improves the understanding of diversity patterns of plant communities, providing spatially explicit information for mapping vegetation diversity and related habitat types at large scales.

     

Managing sun bears in a changing tropical landscape

Aim

Across the tropics, large‐bodied mammal species are threatened by rapid and widespread forest habitat conversion by either commercial logging or agricultural expansion. How such species use these habitats is an important area of research for guiding their future management. The tropical forest‐dwelling sun bear, Helarctos malayanus, is the least known of the eight bear species. Consequently, the IUCN/SSC Bear Specialist Group ranks research on this species as a top priority. This study aims to investigate landscape variables that influence sun bear habitat use in forests under varying levels of degradation and protection.

Location

A 20,998 km² Sumatra forest landscape covering Kerinci Seblat National Park (KSNP), Batang Hari Protection Forest (BHPF) and neighbouring logging and agricultural concessions.

Methods

An occupancy‐based sampling technique using detection/non‐detection data with 10 landscape covariates was applied in six study areas that operated a total of 125 camera traps. The potential differences between habitat use (ψ) of sun bears were first modelled with broad‐scale covariates of study area, land‐use types and forest type. Sun bear habitat use was then investigated with the finer‐scale landscape features associated within these areas.

Results

From 10,935 trap nights, sun bears were recorded at altitudes ranging from 365 to 1791 m. At a broad‐scale, habitat use increased with protection status, being highest in KSNP (0.688 ± 0.092, ± SE) and BHPF (0.621 ± 0.110) compared to production (0.418 ± 0.121) and convertible (0.286 ± 0.122) forests. Within these areas, sun bears showed a preference for forest that was further from public roads and villages and at a lower elevation.

Main conclusions

The habitat suitability model identified several high‐quality habitat patches outside of the priority conservation areas for immediate protection. Consequently, conservation management strategies should emphasize the importance of high conservation value forests and prohibit further conversion of threatened lowland forests.

     

Combined exposure to hydroelectric expansion,climate change and forest loss jeopardies amphibians in the Brazilian Amazon

Aim

Human‐driven impacts constantly threat amphibians, even in largely protected regions such as the Amazon. The Brazilian Amazon is home to a great diversity of amphibians, several of them currently threatened with extinction. We investigated how climate change, deforestation and establishment of hydroelectric dams could affect the geographic distribution of Amazonian amphibians by 2030 and midcentury.

Location

The Brazilian Amazon.

Methods

We overlapped the geographic distribution of 255 species with the location of hydroelectric dams, models of deforestation and climate change scenarios for the future.

Results

We found that nearly 67% of all species and 54% of species with high degree of endemism within the Legal Brazilian Amazon would lose habitats due to the hydroelectric overlapping. In addition, deforestation is also a potential threat to amphibians, but had a smaller impact compared to the likely changes in climate. The largest potential range loss would be caused by the likely increase in temperature. We found that five amphibian families would have at least half of the species with over 50% of potential distribution range within the Legal Brazilian Amazon limits threatened by climate change between 2030 and 2050.

Main conclusions

Amphibians in the Amazon are highly vulnerable to climate change, which may cause, directly or indirectly, deleterious biological changes for the group. Under modelled scenarios, the Brazilian Government needs to plan for the development of the Amazon prioritizing landscape changes of low environmental impact and economic development to ensure that such changes do not cause major impacts on amphibian species while reducing the emission of greenhouse gases.

     

Does local habitat fragmentation affect large‐scale distributions? The case of a specialist grassland bird

Aim

Although the negative effects of habitat fragmentation have been widely documented at the landscape scale, much less is known about its impacts on species distributions at the biogeographical scale. We hypothesize that fragmentation influences the large‐scale distribution of area‐ and edge‐sensitive species by limiting their occurrence in regions with fragmented habitats , despite otherwise favourable environmental conditions. We test this hypothesis by assessing the interplay of climate and landscape factors influencing the distribution of the calandra lark, a grassland specialist that is highly sensitive to habitat fragmentation.

Location

Iberia Peninsula, Europe.

Methods

Ecological niche modelling was used to investigate the relative influence of climate/topography, landscape fragmentation and spatial structure on calandra lark distribution. Modelling assumed explicitly a hierarchically structured effect among explanatory variables, with climate/topography operating at broader spatial scales than landscape variables. An eigenvector‐based spatial filtering approach was used to cancel bias introduced by spatial autocorrelation. The information theoretic approach was used in model selection, and variation partitioning was used to isolate the unique and shared effects of sets of explanatory variables.

Results

Climate and topography were the most influential variables shaping the distribution of calandra lark, but incorporating landscape metrics contributed significantly to model improvement. The probability of calandra lark occurrence increased with total habitat area and declined with the number of patches and edge density. Variation partitioning showed a strong overlap between variation explained by climate/topography and landscape variables. After accounting for spatial structure in species distribution, the explanatory power of environmental variables remained largely unchanged.

Main conclusions

We have shown here that landscape fragmentation can influence species distributions at the biogeographical scale. Incorporating fragmentation metrics into large‐scale ecological niche models may contribute for a better understanding of mechanism driving species distributions and for improving predictive modelling of range shifts associated with land use and climate changes.

     

Ecological traits modulate bird species responses to forest fragmentation in an Amazonian anthropogenic archipelago

Aim

We assessed patterns of avian species loss and the role of morpho‐ecological traits in explaining species vulnerability to forest fragmentation in an anthropogenic island system. We also contrasted observed and detectability‐corrected estimates of island occupancy, which are often used to infer species vulnerability.

Location

Tucuruí Hydroelectric Reservoir, eastern Brazilian Amazonia.

Methods

We surveyed forest birds within 36 islands (3.4–2,551.5 ha) after 22 years of post‐isolation history. We applied species–area relationships to assess differential patterns of species loss among three data sets: all species, forest specialists and habitat generalists. After controlling for phylogenetic non‐independence, we used observed and detectability‐corrected estimates of island occupancy separately to build competing models as a function of species traits. The magnitude of the difference between these estimates of island occupancy was contrasted against species detectability.

Results

The rate of species loss as a function of island area reduction was higher for forest specialists than for habitat generalists. Accounting for the area effect, forest fragmentation did not affect the overall number of species regardless of the data set. Only the interactive model including natural abundance, habitat breadth and geographic range size was strongly supported for both estimates of island occupancy. For 30 species with detection probabilities below 30%, detectability‐corrected estimates were at least tenfold higher than those observed. Conversely, differences between estimates were negligible or non‐existent for all 31 species with detection probabilities exceeding 45.5%.

Main conclusions

Predicted decay of avian species richness induced by forest loss is affected by the degree of habitat specialisation of the species under consideration, and may be unrelated to forest fragmentation per se. Natural abundance was the main predictor of species island occupancy, although habitat breadth and geographic range size also played a role. We caution against using occupancy models for low‐detectability species, because overestimates of island occupancy reduce the power of species‐level predictions of vulnerability.

     

Integrating multiple data sources for assessing blue whale abundance and distribution in Chilean Northern Patagonia

Aim

Species distribution models are useful tools for depicting important habitat, assessing abundance and orienting conservation efforts. For small populations in poorly studied ecosystems, available data are often scarce and patchy. To overcome this limitation, we aim to evaluate the use of different data types within a hierarchical Bayesian framework with the goal of modelling the abundance and distribution of a small and highly migratory population of blue whale (BW, Balaenoptera musculus) summering in Chilean Northern Patagonian (CNP).

Location

CNP, Eastern South Pacific (ESP).

Methods

We constructed a Bayesian hierarchical species distribution Model (HSDM), combining a binomial N‐mixture model used to model BW groups counts in line‐transect data (2009, 2012 and 2014) with a logistic regression for modelling presence‐availability data (2009–2016), allowing both models to share covariate parameters for borrowing strength in estimations.

Results

Distance to areas of high chlorophyll‐a concentration during spring before summering season (AHCC‐s) was the most important and consistent explanatory variable for assessing BW abundance and distribution in CNP. Incorporating accessorial presence‐only data reduced uncertainty in parameters estimation when comparing with a model using only line‐transect data, although other covariates of secondary importance failed to be retained in this model.

Main conclusions

Our results remark the capability of HSDM for integrating different data types providing a potential powerful tool when data are limited and heterogeneous. Results indicate that AHCC‐s, and possibly thermal fronts, could modulate BW abundance and distribution patterns in CNP. Preliminary model‐based delimitations of possible priority conservation areas for BW in CNP overlap with highly used vessel navigation routes and areas destined to aquaculture.

     

Refuges and risks: Evaluating the benefits of an expanded MPA network for mobile apex predators

Aim

Concurrently, assessing the effectiveness of marine protected areas and evaluating the degree of risk from humans to key species provide valuable information that can be integrated into conservation management planning. Tiger sharks (Galeocerdo cuvier) are a wide‐ranging ecologically important species subject to various threats. The aim of this study was to identify “hotspots” of tiger shark habitat use in relation to protected areas and potential risks from fishing.

Location

Southwest Indian Ocean, east coast of South Africa and Mozambique.

Methods

Satellite tags were fitted to 26 tiger sharks. A subset of 19 sharks with an average period at liberty of 197 (SD = 110) days were analysed using hotspot analysis to identify areas of core habitat use. The spatial and temporal overlap of significant hotspots with current and planned marine protected areas as well as risks from fishing and culling was then calculated.

Results

There was a 5.97% spatial overlap between tiger shark hotspots and marine protected areas, which would increase significantly (p < .05) to 24.36% with the expansion of planned protected areas in South Africa and could be as high as 41.43% if Mozambique similarly expanded neighbouring protected area boundaries. Tiger sharks remained largely coastal, but only showed a spatial overlap of 5.12% with shark culling nets in South Africa. Only three sharks undertook open ocean migrations during which they were more likely to interact with longline fisheries in the region.

Main conclusions

This study demonstrates how spatial information can be used to assess the overlap between marine protected areas and the core habitats of top marine predators and highlights how congruent transnational conservation management can improve the effectiveness of protected areas. Core habitat use of marine apex predators may also be indicative of productive habitats, and therefore, predators such as tiger sharks could act as surrogate species for identifying key habitats to prioritize for conservation planning.

     

Old‐growth forests buffer climate‐sensitive bird populations from warming

Aim

Habitat loss and climate change constitute two of the greatest threats to biodiversity worldwide, and theory predicts that these factors may act synergistically to affect population trajectories. Recent evidence indicates that structurally complex old‐growth forest can be cooler than other forest types during spring and summer months, thereby offering potential to buffer populations from negative effects of warming. Old growth may also have higher food and nest‐site availability for certain species, which could have disproportionate fitness benefits as species approach their thermal limits.

Location

Pacific Northwestern United States.

Methods

We predicted that negative effects of climate change on 30‐year population trends of old‐growth‐associated birds should be dampened in landscapes with high proportions of old‐growth forest. We modelled population trends from Breeding Bird Survey data for 13 species as a function of temperature change and proportion old‐growth forest.

Results

We found a significant negative effect of summer warming on only two species. However, in both of these species, this relationship between warming and population decline was not only reduced but reversed, in old‐growth‐dominated landscapes. Across all 13 species, evidence for a buffering effect of old‐growth forest increased with the degree to which species were negatively influenced by summer warming.

Main conclusions

These findings suggest that old‐growth forests may buffer the negative effects of climate change for those species that are most sensitive to temperature increases. Our study highlights a mechanism whereby management strategies to curb degradation and loss of old‐growth forests—in addition to protecting habitat—could enhance biodiversity persistence in the face of climate warming.

     

Climate versus weather extremes: Temporal predictor resolution matters for future rather than current regional species distribution models

Aim

Climate is considered a major driver of species distributions. Long‐term climatic means are commonly used as predictors in correlative species distribution models (SDMs). However, this coarse temporal resolution does not reflect local conditions that populations experience, such as short‐term weather extremes, which may have a strong impact on population dynamics and local distributions. We here compare the performance of climate‐ and weather‐based predictors in regional SDMs and their influence on future predictions, which are increasingly used in conservation planning.

Location

South‐western Germany.

Methods

We built different SDMs for 20 Orthoptera species based on three predictor sets at a regional scale for current and future climate scenarios. We calculated standard bioclimatic variables and yearly and seasonal sets of climate change indicating variables of weather extremes. As the impact of extreme events may be stronger for habitat specialists than for generalists, we distinguished species’ degrees of specialization. We computed linear mixed‐effects models to identify significant effects of algorithm, predictor set and specialization on model performance and calculated correlations and geographical niche overlap between spatial predictions.

Results

Current predictions were rather similar among all predictor sets, but highly variable for future climate scenarios. Bioclimatic and seasonal weather predictors performed slightly better than yearly weather predictors, though performance differences were minor. We found no evidence that specialists are more sensitive to weather extremes than generalists.

Main conclusions

For future projections of species distributions, SDM predictor selection should not solely be based on current performances and predictions. As long‐term climate and short‐term weather predictors represent different environmental drivers of a species’ distribution, we argue to interpret diverging future projections as complements. Even if similar current performances and predictions might imply their equivalency, favouring one predictor set neglects important aspects of future distributions and might mislead conservation decisions based on them.

     

Ecological correlates of mammal β‐diversity in Amazonian land‐bridge islands: from small‐ to large‐bodied species

Aim

Mega hydroelectric dams have become one of the main drivers of biodiversity loss in the lowland tropics. In these reservoirs, vertebrate studies have focused on local (α) diversity measures, whereas between‐site (β) diversity remains poorly assessed despite its pivotal importance in understanding how species diversity is structured and maintained. Here, we unravel the patterns and ecological correlates of mammal β‐diversity, including both small (SM) and midsized to large mammal species (LM) across 23 islands and two continuous forest sites within a mega hydroelectric reservoir.

Location

Balbina Hydroelectric Dam, Central Brazilian Amazonia.

Methods

Small mammals were sampled using live and pitfall traps (48,350 trap‐nights), and larger mammals using camera traps (8,160 trap‐nights). β‐diversity was examined for each group using multiplicative diversity decomposition of Hill numbers, which considers the importance of rare, common and dominant species, and tested to what extent those were related to a set of environmental characteristics measured at different spatial scales.

Results

β‐diversity for both mammal groups was higher when considering species presence–absence. When considering species abundance, β‐diversity was significantly higher for SM than for LM assemblages. Habitat variables, such as differences in tree species richness and percentage of old‐growth trees, were strong correlates of β‐diversity for both SMs and LMs. Conversely, β‐diversity was weakly related to patch and landscape characteristics, except for LMs, for which β‐diversity was correlated with differences in island sizes.

Main conclusions

The lower β‐diversity of LMs between smaller islands suggests subtractive homogenization of this group. Although island size plays a major role in structuring mammal α‐diversity in several land‐bridge islands, local vegetation characteristics were additional key factors determining β‐diversity for both mammal groups. Maintaining the integrity of vegetation characteristics and preventing the formation of a large set of small islands within reservoirs should be considered in long‐term management plans in both existing and planned hydropower development in lowland tropical forests.

     

Small variations in climate and soil conditions may have greater influence on multitaxon species occurrences than past and present human activities in temperate mountain forests

Aim

Human activity is known to greatly influence species occurrences. In forest ecosystems, biodiversity is often believed to be influenced by two habitat characteristics: (1) forest continuity, related to a minimum length of time in a wooded state since a threshold date; and (2) stand maturity, related to the availability of late‐developmental‐forest attributes. In a context of ongoing global biodiversity loss, qualifying the effect of past and present human activity on forest ecosystems while taking into account variations in abiotic factors is of primary importance for conservation.

Location

Temperate mountain forests in the Northern Alps.

Method

Based upon a sampling design crossing forest continuity (ancient vs. Recent) and stand maturity (mature vs. overmature), and while controlling for the effect of two major environmental factors, soil and climate, we explored the individual response of saproxylic beetle, springtail, herbaceous plant and epiphytic macrolichen species to past and present human activity.

Results

Forest continuity influenced the occurrence of relatively few species, indicating that past land use had almost no legacy effect on the species occurring in the study forests today. In contrast, stand maturity had an overall positive effect on species occurrences. However, our results showed that species occurrences were more obviously influenced by abiotic conditions. Indeed, beyond the effect of continuity and maturity factors, the probability of presence of numerous species was best explained by climate and soil.

Main conclusions

Overall, we show that species occurrence was more influenced by stand maturity than by forest continuity, but also that site‐specific characteristics were of great importance in explaining the probability of presence for numerous species. In the ecological context of alpine forests, these findings emphasize the need to better control for climatic and edaphic conditions in order to (1) improve accuracy in predicting species occurrence and (2) better design areas of conservation interest.

     

When is a native species invasive? Incursion of a novel predatory marsupial detected using molecular and historical data

Aim

Range expansions facilitated by humans or in response to local biotic or abiotic stressors provide the opportunity for species to occupy novel environments. Classifying the status of newly expanded populations can be difficult, particularly when the timing and nature of the range expansion are unclear. Should native species in new habitats be considered invasive pests or actively conserved? Here, we present an analytical framework applied to an Australian marsupial, the sugar glider (Petaurus breviceps), a species that preys upon on an endangered parrot in Tasmania, and whose provenance was uncertain.

Location

Tasmania, Australia.

Methods

We conducted an extensive search of historical records for sugar glider occurrences in Tasmania. Source material included museum collection data, early European expedition logs, community observation records, and peer‐reviewed and grey literature. To determine the provenance of the Tasmanian population, we sequenced two mitochondrial genes and one nuclear gene in Tasmanian animals (n = 27) and in individuals across the species' native range. We then estimated divergence times between Tasmania and southern Australian populations using phylogenetic and Bayesian analyses.

Results

We found no historical evidence of sugar gliders occurring in Tasmania prior to 1835. All Tasmanian individuals (n = 27) were genetically identical at the three genes surveyed here with those individuals being 0.125% divergent from individuals from a population in Victoria. Bayesian analysis of divergence between Tasmanian individuals and southern Australian individuals suggested a recent introduction of sugar gliders into Tasmania from southern Australia.

Main conclusions

Molecular and historical data demonstrate that Tasmanian sugar gliders are a recent, post‐European, anthropogenic introduction from mainland Victoria. This result has implications for the management of the species in relation to their impact on an endangered parrot. The analytical framework outlined here can assist environmental managers with the complex task of assessing the status of recently expanded or introduced native species.