Species distribution models for invasive Eurasian watermilfoil highlight the importance of data quality and limitations of discrimination accuracy metrics

AimAvailability of uniformly collected presence, absence, and abundance data remains a key challenge in species distribution modeling (SDM). For invasive species, abundance and impacts are highly variable across landscapes, and quality occurrence and abundance data are critical for predicting locations at high risk for invasion and impacts, respectively. We leverage a large aquatic vegetation dataset comprising point‐level survey data that includes information on the invasive plant Myriophyllum spicatum (Eurasian watermilfoil) to: (a) develop SDMs to predict invasion and impact from environmental variables based on presence–absence, presence‐only, and abundance data, and (b) compare evaluation metrics based on functional and discrimination accuracy for presence–absence and presence‐only SDMs.LocationMinnesota, USA.MethodsEurasian watermilfoil presence–absence and abundance information were gathered from 468 surveyed lakes, and 801 unsurveyed lakes were leveraged as pseudoabsences for presence‐only models. A Random Forest algorithm was used to model the distribution and abundance of Eurasian watermilfoil as a function of lake‐specific predictors, both with and without a spatial autocovariate. Occurrence‐based SDMs were evaluated using conventional discrimination accuracy metrics and functional accuracy metrics assessing correlation between predicted suitability and observed abundance.ResultsWater temperature degree days and maximum lake depth were two leading predictors influencing both invasion risk and abundance, but they were relatively less important for predicting abundance than other water quality measures. Road density was a strong predictor of Eurasian watermilfoil invasion risk but not abundance. Model evaluations highlighted significant differences: Presence–absence models had high functional accuracy despite low discrimination accuracy, whereas presence‐only models showed the opposite pattern.Main conclusionComplementing presence–absence data with abundance information offers a richer understanding of invasive Eurasian watermilfoil''s ecological niche and enables evaluation of the model''s functional accuracy. Conventional discrimination accuracy measures were misleading when models were developed using pseudoabsences. We thus caution against the overuse of presence‐only models and suggest directing more effort toward systematic monitoring programs that yield high‐quality data.     

Predicting range shifts of Davidia involucrata Ball. under future climate change

Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one‐third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high‐latitude regions. Similarly, at least one‐fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.     

Niche breadth and biodiversity change derived from marine Amphipoda species off Iceland

Understanding the ecological requirements and thresholds of individual species is crucial to better predict potential outcomes of climate change on species distribution. In particular, species optima and lower and upper limits along resource gradients require attention. Based on Huisman‐Olff‐Fresco (HOF) models, we determined species‐specific responses along gradients of nine environmental parameters including depth in order to estimate niche attributes of 30 deep‐sea benthic amphipods occurring around Iceland. We, furthermore, examined the relationships between niche breadth, occupancy, and geographic range assuming that species with a wider niche are spatially more widely dispersed and vice versa. Overall, our results reveal that species react very differently to environmental gradients, which is independent of the family affiliation of the respective species. We could infer a strong relationship between occupancy and geographic range and also relate this to differences in niche breadth; that is specialist species with a narrow niche had a more limited distribution and may thus be more threatened by changing environmental conditions than generalist species, which are more widespread. Given the preponderance of rare species in the deep sea, this implies that many species could be at risk. However, this must be carefully weighed against geographical data gaps in this area, given that many deep‐sea areas are severely undersampled and the true distribution of most species is unknown. After all, our results underline that an accurate taxonomic classification is of crucial importance, without which ecological niche properties cannot be determined and which is hence fundamental for the assessment and understanding of changes in biodiversity in the face of increasing human perturbations.     

Microbiome diversity and reproductive incompatibility induced by the prevalent endosymbiont Arsenophonus in two species of African cassava Bemisia tabaci whiteflies

A minimum of 13 diverse whitefly species belonging to the Bemisia tabaci (B. tabaci) species complex are known to infest cassava crops in sub‐Saharan Africa (SSA), designated as SSA1‐13. Of these, the SSA1 and SSA2 are the predominant species colonizing cassava crops in East Africa. The SSA species of B. tabaci harbor diverse bacterial endosymbionts, many of which are known to manipulate insect reproduction. One such symbiont, Arsenophonus, is known to drive its spread by inducing reproductive incompatibility in its insect host and are abundant in SSA species of B. tabaci. However, whether Arsenophonus affects the reproduction of SSA species is unknown. In this study, we investigated both the reproductive compatibility between Arsenophonus infected and uninfected whiteflies by inter‐/intraspecific crossing experiments involving the sub‐group three haplotypes of the SSA1 (SSA1‐SG3), SSA2 species, and their microbial diversity. The number of eggs, nymphs, progenies produced, hatching rate, and survival rate were recorded for each cross. In intra‐specific crossing trials, both male and female progenies were produced and thus demonstrated no reproductive incompatibility. However, the total number of eggs laid, nymphs hatched, and the emerged females were low in the intra‐species crosses of SSA1‐SG3A+, indicating the negative effect of Arsenophonus on whitefly fitness. In contrast, the inter‐species crosses between the SSA1‐SG3 and SSA2 produced no female progeny and thus demonstrated reproductive incompatibility. The relative frequency of other bacteria colonizing the whiteflies was also investigated using Illumina sequencing of 16S rDNA and diversity indices were recorded. Overall, SSA1‐SG3 and SSA2 harbored high microbial diversity with more than 137 bacteria discovered. These results described for the first time the microbiome diversity and the reproductive behaviors of intra‐/inter‐species of Arsenophonus in whitefly reproduction, which is crucial for understanding the invasion abilities of cassava whiteflies.     

Seed dispersal by wind decreases when plants are water‐stressed,potentially counteracting species coexistence and niche evolution

Hydrology is a major environmental factor determining plant fitness, and hydrological niche segregation (HNS) has been widely used to explain species coexistence. Nevertheless, the distribution of plant species along hydrological gradients does not only depend on their hydrological niches but also depend on their seed dispersal, with dispersal either weakening or reinforcing the effects of HNS on coexistence. However, it is poorly understood how seed dispersal responds to hydrological conditions. To close this gap, we conducted a common‐garden experiment exposing five wind‐dispersed plant species (Bellis perennis, Chenopodium album, Crepis sancta, Hypochaeris glabra, and Hypochaeris radicata) to different hydrological conditions. We quantified the effects of hydrological conditions on seed production and dispersal traits, and simulated seed dispersal distances with a mechanistic dispersal model. We found species‐specific responses of seed production, seed dispersal traits, and predicted dispersal distances to hydrological conditions. Despite these species‐specific responses, there was a general positive relationship between seed production and dispersal distance: Plants growing in favorable hydrological conditions not only produce more seeds but also disperse them over longer distances. This arises mostly because plants growing in favorable environments grow taller and thus disperse their seeds over longer distances. We postulate that the positive relationship between seed production and dispersal may reduce the concentration of each species to the environments favorable for it, thus counteracting species coexistence. Moreover, the resulting asymmetrical gene flow from favorable to stressful habitats may slow down the microevolution of hydrological niches, causing evolutionary niche conservatism. Accounting for context‐dependent seed dispersal should thus improve ecological and evolutionary models for the spatial dynamics of plant populations and communities.     

Past,present, and future predictions on the suitable habitat of the Slender racer (Orientocoluber spinalis) using species distribution models

Species distribution models (SDMs) across past, present, and future timelines provide insights into the current distribution of these species and their reaction to climate change. Specifically, if a species is threatened or not well‐known, the information may be critical to understand that species. In this study, we computed SDMs for Orientocoluber spinalis, a monotypic snake genus found in central and northeast Asia, across the past (last interglacial, last glacial maximum, and mid‐Holocene), present, and future (2070s). The goal of the study was to understand the shifts in distribution across time, and the climatic factors primarily affecting the distribution of the species. We found the suitable habitat of O. spinalis to be persistently located in cold‐dry winter and hot summer climatic areas where annual mean temperature, isothermality, and annual mean precipitation were important for suitable habitat conditions. Since the last glacial maximum, the suitable habitat of the species has consistently shifted northward. Despite the increase in suitable habitat, the rapid alterations in weather regimes because of climate change in the near future are likely to greatly threaten the southern populations of O. spinalis, especially in South Korea and China. To cope with such potential future threats, understanding the ecological requirements of the species and developing conservation plans are urgently needed.     

Niche partitioning in a sympatric cryptic species complex

Competition theory states that multiple species should not be able to occupy the same niche indefinitely. Morphologically, similar species are expected to be ecologically alike and exhibit little niche differentiation, which makes it difficult to explain the co‐occurrence of cryptic species. Here, we investigated interspecific niche differentiation within a complex of cryptic bumblebee species that co‐occur extensively in the United Kingdom. We compared the interspecific variation along different niche dimensions, to determine how they partition a niche to avoid competitive exclusion. We studied the species B. cryptarum, B. lucorum, and B. magnus at a single location in the northwest of Scotland throughout the flight season. Using mitochondrial DNA for species identification, we investigated differences in phenology, response to weather variables and forage use. We also estimated niche region and niche overlap between different castes of the three species. Our results show varying levels of niche partitioning between the bumblebee species along three niche dimensions. The species had contrasting phenologies: The phenology of B. magnus was delayed relative to the other two species, while B. cryptarum had a relatively extended phenology, with workers and males more common than B. lucorum early and late in the season. We found divergent thermal specialisation: In contrast to B. cryptarum and B. magnus, B. lucorum worker activity was skewed toward warmer, sunnier conditions, leading to interspecific temporal variation. Furthermore, the three species differentially exploited the available forage plants: In particular, unlike the other two species, B. magnus fed predominantly on species of heather. The results suggest that ecological divergence in different niche dimensions and spatio‐temporal heterogeneity in the environment may contribute to the persistence of cryptic species in sympatry. Furthermore, our study suggests that cryptic species provide distinct and unique ecosystem services, demonstrating that morphological similarity does not necessarily equate to ecological equivalence.     

Effects of grain size and niche breadth on species distribution modeling

Scale is a vital component to consider in ecological research, and spatial resolution or grain size is one of its key facets. Species distribution models (SDMs) are prime examples of ecological research in which grain size is an important component. Despite this, SDMs rarely explicitly examine the effects of varying the grain size of the predictors for species with different niche breadths. To investigate the effect of grain size and niche breadth on SDMs, we simulated four virtual species with different grain sizes/niche breadths using three environmental predictors (elevation, aspect, and percent forest) across two real landscapes of differing heterogeneity in predictor values. We aggregated these predictors to seven different grain sizes and modeled the distribution of each of our simulated species using MaxEnt and GLM techniques at each grain size. We examined model accuracy using the AUC statistic, Pearson's correlations of predicted suitability with the true suitability, and the binary area of presence determined from suitability above the maximum true skill statistic (TSS) threshold. Habitat specialists were more accurately modeled than generalist species, and the models constructed at the grain size from which a species was derived generally performed the best. The accuracy of models in the homogenous landscape deteriorated with increasing grain size to a greater degree than models in the heterogenous landscape. Variable effects on the model varied with grain size, with elevation increasing in importance as grain size increased while aspect lost importance. The area of predicted presence was drastically affected by grain size, with larger grain sizes over predicting this value by up to a factor of 14. Our results have implications for species distribution modeling and conservation planning, and we suggest more studies include analysis of grain size as part of their protocol.     

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large‐scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (~9%) compared to the contribution of each predictor set individually (~20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo‐climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.     

Mapping suitable great ape habitat in and around the Lobéké National Park,South‐East Cameroon

As a result of extensive data collection efforts over the last 20–30 years, there is quite a good understanding of the large‐scale geographic distribution and range limits of African great apes. However, as human activities increasingly fragment great ape spatial distribution, a better understanding of what constitutes suitable great ape habitat is needed to inform conservation and resource extraction management. Chimpanzees (Pan troglodytes troglodytes) and gorillas (Gorilla gorilla gorilla) inhabit the Lobéké National Park and its surrounding forest management units (FMUs) in South‐East Cameroon. Both park and neighboring forestry concessions require reliable evidence on key factors driving great ape distribution for their management plans, yet this information is largely missing and incomplete. This study aimed at mapping great ape habitat suitability in the area and at identifying the most influential predictors among three predictor categories, including landscape predictors (dense forest, swampy forest, distance to water bodies, and topography), human disturbance predictors (hunting, deforestation, distance to roads, and population density), and bioclimatic predictor (annual precipitation). We found that about 63% of highly to moderately suitable chimpanzee habitat occurred within the Lobéké National Park, while only 8.4% of similar habitat conditions occurred within FMUs. For gorillas, highly and moderately suitable habitats occurred within the Lobéké National Park and its surrounding FMUs (82.6% and 65.5%, respectively). Key determinants of suitable chimpanzee habitat were hunting pressure and dense forest, with species occurrence probability optimal at relatively lower hunting rates and at relatively high‐dense forest areas. Key determinants of suitable gorilla habitat were hunting pressure, dense forests, swampy forests, and slope, with species occurrence probability optimal at relatively high‐dense and swampy forest areas and at areas with mild slopes. Our findings show differential response of the two ape species to forestry activities in the study area, thus aligning with previous studies.     

Integrating dynamic environmental predictors and species occurrences: Toward true dynamic species distribution models

While biological distributions are not static and change/evolve through space and time, nonstationarity of climatic and land‐use conditions is frequently neglected in species distribution models. Even recent techniques accounting for spatiotemporal variation of species occurrence basically consider the environmental predictors as static; specifically, in most studies using species distribution models, predictor values are averaged over a 50‐ or 30‐year time period. This could lead to a strong bias due to monthly/annual variation between the climatic conditions in which species' locations were recorded and those used to develop species distribution models or even a complete mismatch if locations have been recorded more recently. Moreover, the impact of land‐use change has only recently begun to be fully explored in species distribution models, but again without considering year‐specific values. Excluding dynamic climate and land‐use predictors could provide misleading estimation of species distribution. In recent years, however, open‐access spatially explicit databases that provide high‐resolution monthly and annual variation in climate (for the period 1901–2016) and land‐use (for the period 1992–2015) conditions at a global scale have become available. Combining species locations collected in a given month of a given year with the relative climatic and land‐use predictors derived from these datasets would thus lead to the development of true dynamic species distribution models (D‐SDMs), improving predictive accuracy and avoiding mismatch between species locations and predictor variables. Thus, we strongly encourage modelers to develop D‐SDMs using month‐ and year‐specific climatic data as well as year‐specific land‐use data that match the period in which species data were collected.     

Alien Invasive Slider Turtle in Unpredicted Habitat: A Matter of Niche Shift or of Predictors Studied?

Background

Species Distribution Models (SDMs) aim on the characterization of a species'' ecological niche and project it into geographic space. The result is a map of the species'' potential distribution, which is, for instance, helpful to predict the capability of alien invasive species. With regard to alien invasive species, recently several authors observed a mismatch between potential distributions of native and invasive ranges derived from SDMs and, as an explanation, ecological niche shift during biological invasion has been suggested. We studied the physiologically well known Slider turtle from North America which today is widely distributed over the globe and address the issue of ecological niche shift versus choice of ecological predictors used for model building, i.e., by deriving SDMs using multiple sets of climatic predictor.

Principal Findings

In one SDM, predictors were used aiming to mirror the physiological limits of the Slider turtle. It was compared to numerous other models based on various sets of ecological predictors or predictors aiming at comprehensiveness. The SDM focusing on the study species'' physiological limits depicts the target species'' worldwide potential distribution better than any of the other approaches.

Conclusion

These results suggest that a natural history-driven understanding is crucial in developing statistical models of ecological niches (as SDMs) while “comprehensive” or “standard” sets of ecological predictors may be of limited use.     

Trophic niche overlap between round sardinella (Sardinella aurita) and sympatric pelagic fish species in the Western Mediterranean

The northward expansion of round sardinella (Sardinella aurita) in the Mediterranean Sea, together with declines and fluctuations in biomass and landings of European sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus) observed in recent decades, may suggest potential inter‐specific competition in the pelagic domain. The coexistence of sympatric zooplanktivorous fish species might therefore be exposed in part to trophic niche overlap and competition for food. Combining visual diet characterization under the microscope with DNA metabarcoding from stomach contents of fish collected in spring results show that predation on relatively large krill is equally important for sardinella than for the other two niche overlapping species. Furthermore, an important overlap is found in their isotopic niche, especially with anchovy, using nitrogen (δ¹⁵N) and carbon (δ¹³C) stable isotopes in muscle tissue. In fact, the three fish species are able to feed effectively in the whole prey size spectrum available during the sampled season, from the smallest diatoms and copepods to the larger prey (i.e., decapods and euphausiids), including fish larvae. Moreover, effective predation upon other large prey like siphonophores, which is observed only when multi‐proxy analyses in stomach contents are applied, might also be relevant in the diet of sardinella. The overlapping diet composition in spring, together with the effective use of food resource by sardinella, can be of special interest in potential future scenarios with warmer water temperature leading to lower zooplankton and/or higher jellyfish availability, where sardinella may take advantage over other species due to its feeding plasticity.     

The living heart: Climate gradients predict desert mountain endemism

Mountain regions are centers of biodiversity endemism at a global scale but the role of arid‐zone mountain ranges in shaping biodiversity patterns is poorly understood. Focusing on three guilds of taxa from a desert upland refugium in Australia, we sought to determine: (a) the relative extent to which climate, terrain or geological substrate predict endemism, and (b) whether patterns of endemism are complimentary across broad taxonomic guilds. We mapped regional endemism for plants, land snails, and vertebrates using combined Species Distribution Models (SDMs) for all endemic taxa (n = 82). We then modelled predictors of endemism using Generalised Additive Models (GAMs) and geology, terrain, and climate variables. We tested for the presence of inter‐ and intraguild hotspots of endemism. Many individual plant and land snail taxa were tightly linked with geology, corresponding to small distributions. Conversely, most vertebrate taxa were not constrained to specific geological substrates and occurred over larger areas. However, across all three guilds climate was the strongest predictor of regional endemism, particularly for plants wherein discrete hotspots of endemism were buffered from extreme summer temperatures. Land snail and vertebrate endemism peaked in areas with highest precipitation in the driest times of the year. Hotspots of endemism within each guild poorly predicted endemism in other guilds. We found an overarching signal that climatic gradients play a dominant role in the persistence of endemic taxa in an arid‐zone mountain range system. An association with higher rainfall and cooler temperatures indicates that continuing trends toward hotter and drier climates may lead to range contractions in this, and potentially other, arid‐zone mountain biotas. Contrasting patterns of endemism across guilds highlight the need to couple comprehensive regional planning for the protection of climate refugia, with targeted management of more localized and habitat specialist taxa.     

Modelling the niche space of desert annuals needs to include positive interactions

The niche is a necessary consideration when estimating habitable area and geographic range of a species. Modellers often examine the fundamental niche and the environmental requirements for plant species, ignoring interactions among species. In deserts, positive plant interactions are important drivers of biodiversity and structure communities through many mechanistic pathways including modifying environmental conditions. Thus, we tested the hypothesis that desert shrubs increase the geographical extent of some annual species because, through modifying the microclimate, they match the niche requirements of beneficiary species. We used the database of the Global Biodiversity Information Facility to construct MaxEnt species distribution models (SDM) with and without reported benefactor species within the Mojave Desert in California. We chose 20 annual species to be modeled including 10 species that had been previously reported in the literature as being facilitated (beneficiary) and 10 that had no record of being facilitated (unreported). Beneficiary annuals co‐occurred significantly more with benefactor shrubs than the unreported annual species. The inclusion of shrubs into SDMs significantly improved model predictability and geographic range for all the beneficiary annual species, but not for the unreported annual species. Thus, positive interactions are species specific and it is possible to determine annual species dependency on benefactor shrubs at the regional scale. The co‐occurrence of benefactor shrubs and annual species can be used as a proxy for facilitation and recent developments in SDM techniques encourage the inclusion of biotic interactions. Species distribution models should include estimates of facilitation because biotic interactions determine the niche of species and can have implications with a changing climate.     

Genetic structure and life history are key factors in species distribution models of spiny lobsters

AimWe incorporated genetic structure and life history phase in species distribution models (SDMs) constructed for a widespread spiny lobster, to reveal local adaptations specific to individual subspecies and predict future range shifts under the RCP 8.5 climate change scenario.LocationIndo‐West Pacific.MethodsMaxEnt was used to construct present‐day SDMs for the spiny lobster Panulirus homarus and individually for the three genetically distinct subspecies of which it comprises. SDMs incorporated both sea surface and benthic (seafloor) climate layers to recreate discrete influences of these habitats during the drifting larval and benthic juvenile and adult life history phases. Principle component analysis (PCA) was used to infer environmental variables to which individual subspecies were adapted. SDM projections of present‐day habitat suitability were compared with predictions for the year 2,100, under the RCP 8.5 climate change scenario.ResultsIn the PCA, salinity best explained P. h. megasculptus habitat suitability, compared with current velocity in P. h. rubellus and sea surface temperature in P. h. homarus. Drifting and benthic life history phases were adapted to different combinations of sea surface and benthic environmental variables considered. Highly suitable habitats for benthic phases were spatially enveloped within more extensive sea surface habitats suitable for drifting larvae. SDMs predicted that present‐day highly suitable habitats for P. homarus will decrease by the year 2,100.Main conclusionsIncorporating genetic structure in SDMs showed that individual spiny lobster subspecies had unique adaptations, which could not be resolved in species‐level models. The use of sea surface and benthic climate layers revealed the relative importance of environmental variables during drifting and benthic life history phases. SDMs that included genetic structure and life history were more informative in predictive models of climate change effects.     

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.

     

Phenological segregation suggests speciation by time in the planktonic diatom Pseudo‐nitzschia allochrona sp. nov.

The processes leading to the emergence of new species are poorly understood in marine plankton, where weak physical barriers and homogeneous environmental conditions limit spatial and ecological segregation. Here, we combine molecular and ecological information from a long‐term time series and propose Pseudo‐nitzschia allochrona, a new cryptic planktonic diatom, as a possible case of speciation by temporal segregation. The new species differs in several genetic markers (18S, 28S and ITS rDNA fragments and rbcL) from its closest relatives, which are morphologically very similar or identical, and is reproductively isolated from its sibling species P. arenysensis. Data from a long‐term plankton time series show P. allochrona invariably occurring in summer–autumn in the Gulf of Naples, where its closely related species P. arenysensis, P. delicatissima, and P. dolorosa are instead found in winter–spring. Temperature and nutrients are the main factors associated with the occurrence of P. allochrona, which could have evolved in sympatry by switching its phenology and occupying a new ecological niche. This case of possible speciation by time shows the relevance of combining ecological time series with molecular information to shed light on the eco‐evolutionary dynamics of marine microorganisms.     

Terrestrial or marine species distribution model: Why not both? A case study with seabirds

Species reliant on both the terrestrial and marine realms present a challenge for conventional species distribution models (SDMs). For such species, standard single‐realm SDMs may omit key information that could result in decreased model accuracy and performance. Existing approaches to habitat suitability modeling typically do not effectively combine information from multiple realms; this methodological gap can ultimately hamper management efforts for groups such as seabirds, seals, and turtles. This study, for the first time, jointly incorporates both terrestrial information and marine information into a single species distribution model framework. We do this by sampling nearby marine conditions for a given terrestrial point and vice versa using parameters set by each species’ mean maximum foraging distance and then use standard SDM methods to generate habitat suitability predictions; therefore, our method does not rely on post hoc combination of several different models. Using three seabird species with very different ecologies, we investigate whether this new multi‐realm approach can improve our ability to identify suitable habitats for these species. Results show that incorporating terrestrial information into marine SDMs, or vice versa, generally improves model performance, sometimes drastically. However, there is considerable variability between species in the level of improvement as well as in the particular method that produces the most improvement. Our approach provides a repeatable and transparent method to combine information from multiple ecological realms in a single SDM framework. Important advantages over existing solutions include the opportunity to, firstly, easily combine terrestrial and marine information for species that forage large distances inland or out to sea and, secondly, consider interactions between terrestrial and marine variables.     

Population dynamics of the glacial relict amphipods in a subarctic lake: role of density‐dependent and density‐independent factors

Relative role of intrinsic density‐dependent factors (such as inter‐ and intraspecific competition, predation) and extrinsic density‐independent factors (environmental changes) in population dynamics is a key issue in ecology. Density‐dependent mechanisms are considered as important drivers of population dynamics in many vertebrate and insect species; however, their influence on the population dynamics of freshwater invertebrates is not clearly understood. In this study, I examined interannual variations in the abundance of the glacial relict amphipod Monoporeia affinis in a small subarctic lake based on long‐term (2002–2019) monitoring data. The results suggest that the population dynamics of amphipods in the lake is influenced by the combined effects of both intrinsic and extrinsic factors. The reproductive success of amphipod cohorts was inversely related to its initial abundance, indicating it is influenced by density‐dependent factors. M. affinis recruitment was negatively correlated with population density and near‐bottom temperature but positively correlated with food availability, which is defined as the concentration of chlorophyll a. Multiple regression with chlorophyll, temperature, and abundance of parent cohort as independent factors explained about 80% of the variation in the reproductive success of amphipods. The negative correlation between amphipod recruitment and water temperature indicates that the current climate conditions adversely affect the populations of glacial relict amphipods even in cold‐water lakes of the subarctic zone. Results of this study can be useful in environmental assessments to separate population oscillations connected with density‐dependent mechanisms from human‐mediated changes.