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.

     

Environmental gradients shift the direction of the relationship between native and alien plant species richness

Aim

To assess how environmental, biotic and anthropogenic factors shape native–alien plant species richness relationships across a heterogeneous landscape.

Location

Banks Peninsula, New Zealand.

Methods

We integrated a comprehensive floristic survey of over 1200 systematically located 6 × 6 m plots, with corresponding climate, environmental and anthropogenic data. General linear models examined variation in native and alien plant species richness across the entire landscape, between native‐ and alien‐dominated plots, and within separate elevational bands.

Results

Across all plots, there was a significant negative correlation between native and alien species richness, but this relationship differed within subsets of the data: the correlation was positive in alien‐dominated plots but negative in native‐dominated plots. Within separate elevational bands, native and alien species richness were positively correlated at lower elevations, but negatively correlated at higher elevations. Alien species richness tended to be high across the elevation gradient but peaked in warmer, mid‐ to low‐elevation sites, while native species richness increased linearly with elevation. The negative relationship between native and alien species richness in native‐dominated communities reflected a land‐use gradient with low native and high alien richness in more heavily modified native‐dominated vegetation. In contrast, native and alien richness were positively correlated in very heavily modified alien‐dominated plots, most likely due to covariation along a gradient of management intensity.

Main conclusions

Both positive and negative native–alien richness relationships can occur across the same landscape, depending on the plant community and the underlying human and environmental gradients examined. Human habitat modification, which is often confounded with environmental variation, can result in high alien and low native species richness in areas still dominated by native species. In the most heavily human modified areas, dominated by alien species, both native and alien species may be responding to similar underlying gradients.

     

Regional distribution patterns can predict the local habitat specialization of arachnids in heterogeneous landscapes of the Atlantic Forest

Aim

This study formally evaluates the ability of three models to use geographical data on species distribution to predict the habitat use patterns of species in heterogeneous landscapes.

Location

Species and habitats in the Brazilian Atlantic Rain Forest were investigated.

Methods

Based on empirical data on harvestmen and scorpions, we estimated the strength of species association with preferred habitat and classified them as habitat generalists or habitat specialists. We compared these empirical results with predictions made using data on species range size (model 1), species occurrence in biomes (model 2) and species occurrence in habitats within the biomes (model 3).

Results

We used 1,278 records of eight harvestman and two scorpion species that had specific determination and enough sampling numbers to allow safe identification of habitat specialization. We observed the following: (1) the extension of species occurrence did not influence the strength of species–habitat association (estimated by IndVal), which led us to reject model 1; (2) species habitat specialization derived from occurrences in biomes was 60% coincident with the classification derived from empirical data. This value is not different enough from the value expected by chance for these data, which also led us to reject model 2; and (3) species classification derived from secondary data about the habitats used had a significant coincidence of 80% with the empirical classification, which led us to accept model 3.

Main conclusions

For correct classification of species habitat specialization using secondary distributional data, we recommend that future studies consider using the most accurate information available on the habitats used by species. Especially for megadiverse and understudied groups, information about habitats used is not easy to obtain, so it is important for researchers and institutions to register and disseminate this information, which could support many other studies.

     

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.

     

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.

     

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.

     

Gone with the forest: Assessing global woodpecker conservation from land use patterns

Aim

As a result of their ecological traits, woodpeckers (Picidae, Aves) are highly sensitive to forest cover change. We explored the current land cover in areas of high species richness of woodpeckers to determinate regions where urgent conservation actions are needed. In addition, we identified woodpecker species that are sensitive to forest loss and that have high levels of human habitat modification and low levels of protection (through protected areas) in their distribution ranges.

Location

Global.

Methods

We joined available range maps for all extant 254 woodpecker species with information of their conservation status and tolerances to human habitat modifications and generated a richness map of woodpecker species worldwide. Then, we associated this information (the richness pattern and individual species’ maps) with land cover and protected areas (PAs) maps.

Result

We found that the foremost woodpecker species richness hotspot is in Southeast Asia and is highly modified. At the second species richness hotspot in the eastern Andes, we observed a front of deforestation at its southern extreme and a greater deforested area in its northern extreme but most of its area remains with forest coverage. At the species level, 17 species that are sensitive to forest modification experience extensive deforestation and have low extents of PAs in their ranges.

Main conclusions

The most diverse woodpecker hotspots are mostly occupied by human‐modified landscapes, and a large portion of the species there avoids anthropogenic environments. The level of representation of woodpecker species in PAs is low as a global general pattern, although slightly better in Asia. Our global analysis of threats to woodpecker from land use patterns reiterates the urgent conservation needs for Southeast Asian forests. Finally, based on our results, we recommend a re‐evaluation for inclusion in the Red List of five woodpecker species.

     

Fishing pressure and species traits affect stream fish invasions both directly and indirectly

Aim

We sought to identify direct and indirect effects of factors contributing to establishment and spread of 272 stream fish species.

Location

Two hundred and ninety‐seven watersheds in the eastern United States.

Methods

We modelled two variables: (1) whether a species had become established outside its native range (establishment) and (2) the number of watersheds in which species established outside their native range (spread). We estimated these variables by comparing historical distributions to a rich data set of contemporary sampling. We calculated metrics of human use (indexing propagule pressure), and gathered species trait data from an open‐access database. We then used piecewise path analysis to estimate direct and indirect effects of human use, native range size and species traits on the two metrics of species introductions.

Results

We identified a hierarchical causal structure in which native range size and fishing pressure were important direct determinants of introductions. Species traits had some direct effects, but played a more indirect role. Native range size was significantly affected by thermal tolerance and diet breadth. Likewise, fishing pressure was significantly affected by life history strategy: larger‐bodied, longer‐living and more fecund species were positively associated with fishing pressure.

Main conclusions

Functional traits can confer an advantage to some species during the establishment phase, but human use is important for subsequent dispersal throughout the non‐native range. However, human use is non‐random, and is largely a function of species traits. Considering both direct and indirect effects of traits across stages of the invasion process can help to elucidate the full role of traits in species invasions.

     

Species richness and phylogenetic diversity of native and non‐native species respond differently to area and environmental factors

Aim

To test whether native and non‐native species have similar diversity–area relationships (species–area relationships [SARs] and phylogenetic diversity–area relationships [PDARs]) and whether they respond similarly to environmental variables.

Location

United States.

Methods

Using lists of native and non‐native species as well as environmental variables for >250 US national parks, we compared SARs and PDARs of native and non‐native species to test whether they respond similarly to environmental conditions. We then used multiple regressions involving climate, land cover and anthropogenic variables to further explore underlying predictors of diversity for plants and birds in US national parks.

Results

Native and non‐native species had different slopes for SARs and PDARs, with significantly higher slopes for native species. Corroborating this pattern, multiple regressions showed that native and non‐native diversity of plants and birds responded differently to a greater number of environmental variables than expected by chance. For native species richness, park area and longitude were the most important variables while the number of park visitors, temperature and the percentage of natural area were among the most important ones for non‐native species richness. Interestingly, the most important predictor of native and non‐native plant phylogenetic diversity, temperature, had positive effects on non‐native plants but negative effects on natives.

Main conclusions

SARs, PDARs and multiple regressions all suggest that native and non‐native plants and birds responded differently to environmental factors that influence their diversity. The agreement between diversity–area relationships and multiple regressions with environmental variables suggests that SARs and PDARs can be both used as quick proxies of overall responses of species to environmental conditions. However, more importantly, our results suggest that global change will have different effects on native and non‐native species, making it inappropriate to apply the large body of knowledge on native species to understand patterns of community assembly of non‐native species.

     

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.

     

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.

     

Land use legacy effects on woody vegetation in agricultural landscapes of south‐western Ethiopia

Aim

Past land use legacy effects—extinction debts and immigration credits—might be particularly pronounced in regions characterized by complex and dynamic landscape change. The aim of this study was to evaluate how current woody plant species distribution, composition and richness related to historical and present land uses.

Location

A smallholder farming landscape in south‐western Ethiopia.

Methods

We surveyed woody plants in 72 randomly selected 1‐ha sites in farmland and grouped them into forest specialist, generalist and pioneer species. First, we investigated woody plant composition and distribution using non‐metric multidimensional scaling. Second, we modelled species richness in response to historical and current distance from the forest edge. Third, we examined diameter class distributions of trees in recently converted vs. permanent farmland.

Results

Historical distance was a primary driver of woody plant composition and distribution. Generalist and pioneer species richness increased with historical distance. Forest specialists, however, did not respond to historical distance. Only few old individuals of forest specialist species remained in both recently converted and permanent farmlands.

Main conclusions

Our findings suggest that any possible extinction debt for forest specialist species in farmland at the landscape scale was rapidly paid off, possibly because farmers cleared large remnant trees. In contrast, we found substantial evidence of immigration credits in farmland for generalist and pioneer species. This suggests that long‐established farmland may have unrecognized conservation values, although apparently not for forest specialist species. We suggest that conservation policies in south‐western Ethiopia should recognize not only forests, but also the complementary value of the agricultural mosaic—similar to the case of European cultural landscapes. A possible future priority could be to better reintegrate forest species in the farmland mosaic.

     

In search of relevant predictors for marine species distribution modelling using the MarineSPEED benchmark dataset

Aim

Ideally, datasets for species distribution modelling (SDM) contain evenly sampled records covering the entire distribution of the species, confirmed absences and auxiliary ecophysiological data allowing informed decisions on relevant predictors. Unfortunately, these criteria are rarely met for marine organisms for which distributions are too often only scantly characterized and absences generally not recorded. Here, we investigate predictor relevance as a function of modelling algorithms and settings for a global dataset of marine species.

Location

Global marine.

Methods

We selected well‐studied and identifiable species from all major marine taxonomic groups. Distribution records were compiled from public sources (e.g., OBIS, GBIF, Reef Life Survey) and linked to environmental data from Bio‐ORACLE and MARSPEC. Using this dataset, predictor relevance was analysed under different variations of modelling algorithms, numbers of predictor variables, cross‐validation strategies, sampling bias mitigation methods, evaluation methods and ranking methods. SDMs for all combinations of predictors from eight correlation groups were fitted and ranked, from which the top five predictors were selected as the most relevant.

Results

We collected two million distribution records from 514 species across 18 phyla. Mean sea surface temperature and calcite are, respectively, the most relevant and irrelevant predictors. A less clear pattern was derived from the other predictors. The biggest differences in predictor relevance were induced by varying the number of predictors, the modelling algorithm and the sample selection bias correction. The distribution data and associated environmental data are made available through the R package marinespeed and at http://marinespeed.org .

Main conclusions

While temperature is a relevant predictor of global marine species distributions, considerable variation in predictor relevance is linked to the SDM set‐up. We promote the usage of a standardized benchmark dataset (MarineSPEED) for methodological SDM studies.

     

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.

     

Species–area curve and distance–decay relationships indicate habitat thresholds of ectomycorrhizal fungi in an old‐growth Pseudotsuga menziesii landscape

Aim

Ectomycorrhizal fungi (EMF) are a diverse and essential biota of forests that are vulnerable to species loss through reductions in late‐seral habitat. We examined how the spatial ecology of this biota, particularly distance–decay and species–area relationships, could better inform habitat thresholds for EMF conservation planning.

Location

Southeast Vancouver Island near Victoria, British Columbia, Canada.

Methods

Using a stratified sampling design, 11 plots (0.15 ha in size) were established at 0.05–17.5 km apart across 2,800 ha of mesic old‐growth Pseudotsuga menziesii var. menziesii and Tsuga heterophylla forests. EMF communities were compiled through molecular analysis of root tips and sporocarps.

Results

The EMF community was comprised of many Cortinarius, Piloderma, Russula and Tricholoma species typical of mesotrophic habitat. A total of 238 EMF species were observed, of which 86 species were detected only once. The ratio of average species richness per plot (84 taxa) to total richness was low at 0.35, and inherent stochasticity of the EMF community was estimated to be 31% community dissimilarity for species incidence. Distance decay of EMF communities was nonlinear, with an estimated slope break at 2.6 km, followed by a largely unchanging trend in β‐diversity. Accumulated species–area curves were fitted best by the cumulative Weibull sigmoid model, and the asymptote (367 species) at approx. 50 ha was consistent with nonparametric estimates of γ‐diversity (342–362 spp.).

Main conclusions

Old‐growth forests host an impressive amount of EMF diversity, and many of the Ramaria, Inocybe and Russula species are likely to be endemic to the Pacific Northwest. Both niche‐ and neutral‐based processes influenced EMF community composition, resulting in a minimum threshold of 50 ha (1.8% of the sample area) for capturing γ‐diversity. These spatial patterns will help design and evaluate conservation efforts, such as retention forestry, to sustain fully diverse EMF communities over managed landscapes.

     

Chasing a changing climate: Reproductive and dispersal traits predict how sessile species respond to global warming

Aim

Studies of species' range shifts have become increasingly relevant for understanding ecology and biogeography in the face of accelerated global change. The combination of limited mobility and imperilled status places some species at a potentially greater risk of range loss, extirpation or extinction due to climate change. To assess the ability of organisms with limited movement and dispersal capabilities to track shifts associated with climate change, we evaluated reproductive and dispersal traits of freshwater mussels (Unionida), sessile invertebrates that require species‐specific fish for larval dispersal.

Location

North American Atlantic Slope rivers.

Methods

To understand how unionid mussels may cope with and adapt to current and future warming trends, we identified mechanisms that facilitated their colonization of the northern Atlantic Slope river basins in North America after the Last Glacial Maximum. We compiled species occurrence and life history trait information for each of 55 species, and then selected life history traits for which ample data were available (larval brooding duration, host fish specificity, host infection strategy, and body size) and analysed whether the trait state for each was related to mussel distribution in Atlantic Slope rivers.

Results

Brooding duration (p < .01) and host fish specificity (p = .02) were significantly related to mussel species distribution. Long‐term brooders were more likely than short‐term brooders to colonize formerly glaciated rivers, as were host generalists compared to specialists. Body size and host infection strategy were not predictive of movement into formerly glaciated rivers (p > .10).

Main conclusions

Our results are potentially applicable to many species for which life history traits have not been well‐documented, because reproductive and dispersal traits in unionid mussels typically follow phylogenetic relationships. These findings may help resource managers prioritize species according to climate change vulnerability and predict which species might become further imperilled with climate warming. Finally, we suggest that similar trait‐based decision support frameworks may be applicable for other movement limited taxa.

     

Assessing habitat loss and fragmentation and their effects on population viability of forest specialist birds: Linking biogeographical and population approaches

Aim

Biogeographic approaches usually have been developed apart from population ecology, resulting in predictive models without key parameters needed to account for reproductive and behavioural limitations on dispersal. Our aim was to incorporate fully spatially explicit population traits into a classic species distribution model (SDM) using Geographic Information Systems (GIS), aiming at conservation purposes.

Location

Southern South America.

Methods

Our analysis incorporates the effects of habitat loss and fragmentation on population viability and therefore provides insights into how much spatially explicit population traits can improve the SDM prediction of habitable habitat. We utilized a well‐studied focal endemic bird of South American temperate rainforests (Scelorchilus rubecula). First, at a large scale, we assessed the historical extent habitat based on climate envelopes in an SDM. Second, we used a land cover change analysis at a regional scale to account for recent habitat loss and fragmentation. Third, we used empirically derived criteria to predict population responses to fragmented forest landscapes to identify actual losses of habitat and population. Then we selected three sites of high conservation value in southern Chile and applied our population model. Finally, we discuss the degree to which spatially explicit population traits can improve the SDM output without intervening in the modelling process itself.

Results

We found a historical habitat loss of 39.12% and an additional forest cover loss of 3.03% during 2000–2014; the latter occurred with a high degree of fragmentation, reducing the overall estimation of (1) carrying capacity by ?82.4%, ?33.1% and ?45.1% and (2) estimated number of pairs on viable populations by ?84.1%, ?33.0% and ?54.6% on the three selected sites.

Main conclusion

We conclude that our approach sharpened the SDM prediction on environmental suitability by 54.4%, adjusting the habitable area by adding population parameters through GIS, and allowing to incorporate other phenomena as fragmentation and habitat loss.

     

At the landscape level,birds respond strongly to habitat amount but weakly to fragmentation

Aim

It is usually thought that habitat fragmentation acts negatively on species survival, and consequently, on biodiversity. Recent literature challenges whether habitat fragmentation per se affects species richness, beyond the effect of habitat area. Theoretical studies have suggested that fragmentation may matter most when the amount of available habitat is small or at intermediate levels. However, a recent review suggests that the effect of fragmentation on species richness is usually positive. Here, we dissect the richness–fragmentation relationship. What is the effect size? Does it depend upon the amount of habitat cover? How do individual species respond to fragmentation?

Methods

Applying a macroecological approach, we empirically related avian richness and the probability of occurrence (p_occ) of individual species to fragmentation (number of patches), after controlling for habitat amount in 991 landscapes, each 100‐km², in southern Ontario, Canada.

Results

Species richness was strongly related to total habitat amount, but habitat fragmentation had no detectable additional effect. Individual species’ p_occ related strongly to habitat amount. For some species, p_occ also related secondarily to habitat fragmentation within landscapes. Logistic models revealed that p_occ related significantly negatively to fragmentation after controlling for habitat amount for only ~13% of forest‐ and 18% of open‐habitat species bird species. However, p_occ related significantly positively to fragmentation for even greater proportions of species, including some red‐listed species. Fragmentation effects were not stronger at low or intermediate levels of habitat amount within landscapes.

Conclusion

In earlier studies, negative effects of isolation were observed at the patch level in experimental manipulations. However, at the landscape level, avian species richness in southern Ontario apparently responds primarily to habitat amount and negligibly to fragmentation. We argue that the evidence is inconsistent with the hypothesis that reducing habitat fragmentation per se would be an effective conservation strategy for birds at the landscape level.

     

Invasion lags: The stories we tell ourselves and our inability to infer process from pattern

Aim

Many alien species experience a lag phase between arriving in a region and becoming invasive, which can provide a valuable window of opportunity for management. Our ability to predict which species are experiencing lags has major implications for management decisions that are worth billions of dollars and that may determine the survival of some native species. To date, timing and causes of lag and release have been identified post hoc, based on historical narratives.

Location

Global.

Methods

We use a simple but realistic simulation of population spread over a fragmented landscape. To break the invasion lag, we introduce a sudden, discrete change in dispersal.

Results

We show that the ability to predict invasion lags is minimal even under controlled circumstances. We also show a non‐negligible risk of falsely attributing lag breaks to mechanisms based on invasion trajectories and coincidences in timing.

Main conclusions

We suggest that post hoc narratives may lead us to erroneously believe we can predict lags and that a precautionary approach is the only sound management practice for most alien species.

     

Predicted effects of climate change on potential sources of non‐indigenous marine species

Aim

We compare the present‐day global ocean climate with future climatologies based on Intergovernmental Panel on Climate Change (IPCC) models and examine whether changes in global ocean climate will affect the environmental similarity of New Zealand's (NZ) coastal environments to those of the rest of the world. Our underlying rationale is that environmental changes to source and recipient regions may result in changes to the risk of non‐indigenous species survival and establishment.

Location

Coastlines of global continents and islands.

Methods

We determined the environmental similarity (Euclidean distance) between global coastlines and north‐east NZ for 2005 and 2050 using data on coastal seawater surface temperature and salinity. Anticipated climate models from the SRES A1B scenario family were used to derive coastal climatologies for 2050.

Results

During the next decades, most global regions will experience an increase in coastal seawater surface temperatures and a decline or increase in salinity. This will result in changes in the similarity of other coastal environments to north‐east NZ's coastal areas. Global regions that presently have high environmental similarity to north‐east NZ will variously retain this level of similarity, become more similar or decrease in environmental similarity. Some regions that presently have a low level of similarity will become more similar to NZ. Our models predict a widespread decrease in the seasonal variation in environmental similarity to NZ.

Main conclusions

Anticipated changes in the global ocean climate have the potential to change the risk of survival and establishment of non‐indigenous marine species arriving to NZ from some global regions. Predicted changes to global human transport networks over the coming decades highlight the importance of incorporating climate change into conservation planning and modelling.