Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage

Bee and butterfly records indicate diversity losses in western and southern North America, but extensive knowledge gaps remain

Pollinator losses threaten ecosystems and food security, diminishing gene flow and reproductive output for ecological communities and impacting ecosystem services broadly. For four focal families of bees and butterflies, we constructed over 1400 ensemble species distribution models over two time periods for North America. Models indicated disproportionally increased richness in eastern North America over time, with decreases in richness over time in the western US and southern Mexico. To further pinpoint geographic areas of vulnerability, we mapped records of potential pollinator species of conservation concern and found high concentrations of detections in the Great Lakes region, US East Coast, and southern Canada. Finally, we estimated asymptotic diversity indices for genera known to include species that visit flowers and may carry pollen for ecoregions across two time periods. Patterns of generic diversity through time mirrored those of species-level analyses, again indicating a decline in pollinators in the western U.S. Increases in generic diversity were observed in cooler and wetter ecoregions. Overall, changes in pollinator diversity appear to reflect changes in climate, though other factors such as land use change may also explain regional shifts. While statistical methods were employed to account for unequal sampling effort across regions and time, improved monitoring efforts with rigorous sampling designs would provide a deeper understanding of pollinator communities and their responses to ongoing environmental change.

Updated range map of an endangered salamander and congeneric competitor reveals different niche preferences

Estimating distributions for cryptic and highly range-restricted species induces unique challenges for species distribution modeling. In particular, bioclimatic covariates that are typically used to model species ranges at regional and continental scales may not show strong variation at scales of 100s and 10s of meters. This limits both the likelihood and usefulness of correlated occurrence to data typically used in distribution models. Here, we present analyses of species distributions, at 100 × 100 m resolution, for a highly range restricted salamander species (Shenandoah salamander, Plethodon shenandoah) and a closely related congener (red-backed salamander, Plethodon cinereus). We combined data across multiple survey types, account for seasonal variation in availability of our target species, and control for repeated surveys at locations- all typical challenges in range-scale monitoring datasets. We fit distribution models using generalized additive models that account for spatial covariates as well as unexplained spatial variation and spatial uncertainty. Our model accommodates different survey protocols using offsets and incorporates temporal variation in detection and availability resulting from survey-specific variation in temperature and precipitation. Our spatial random effect was crucial in identifying small-scale differences in the occurrence of each species and provides cell-specific estimates of uncertainty in the density of salamanders across the range. Counts of both species were seen to increase in the 3 days following a precipitation event. However, P. cinereus were observed even in extremely wet conditions, while surface activity of P. shenandoah was associated with a more narrow range. Our results demonstrate how a flexible analytical approach improves estimates of both distribution and uncertainty, and identify key abiotic relationships, even at small spatial scales and when scales of empirical data are mismatched. While our approach is especially valuable for species with small ranges, controlling for spatial autocorrelation, estimating spatial uncertainty, and incorporating survey-specific information in estimates can improve the reliability of distribution models in general.

Echinorhinus brucus (Bonnaterre, 1788) in the Caribbean Sea: A recurrent visitor, or are the artisanal fisheries exploiting deeper waters?

Documentation of Echinorhinus brucus, (Bonnaterre, 1788) in the western Atlantic primarily relies on chance observations. Georeferenced records in this area remain notably scarce. This study contributes the second Venezuelan and seventh Caribbean Sea specimens, increasing the western Atlantic count to 15 individuals. All specimens gathered here were sexually mature, with a slight dominance of females. Our bramble shark record appears to be driven more by the interplay of its biology and environmental factors than being a deliberate deep-sea fishery activity, which likely occurs in the Southern Caribbean area.

Climate change and ecosystem shifts in the southwestern United States

Climate change shifts ecosystems, altering their compositions and instigating transitions, making climate change the predominant driver of ecosystem instability. Land management agencies experience these climatic effects on ecosystems they administer yet lack applied information to inform mitigation. We address this gap, explaining ecosystem shifts by building relationships between the historical locations of 22 ecosystems (c. 2000) and abiotic data (1970-2000; bioclimate, terrain) within the southwestern United States using 'ensemble' machine learning models. These relationships identify the conditions required for establishing and maintaining southwestern ecosystems (i.e., ecosystem suitability). We projected these historical relationships to mid (2041-2060) and end-of-century (2081-2100) periods using CMIP6 generation BCC-CSM2-MR and GFDL-ESM4 climate models with SSP3-7.0 and SSP5-8.5 emission scenarios. This procedure reveals how ecosystems shift, as suitability typically increases in area (~ 50% (~ 40% SD)), elevation (12-15%) and northing (4-6%) by mid-century. We illustrate where and when ecosystems shift, by mapping suitability predictions temporally and within 52,565 properties (e.g., Federal, State, Tribal). All properties had ≥ 50% changes in suitability for ≥ 1 ecosystem within them, irrespective of size (≥ 16.7 km2). We integrated 9 climate models to quantify predictive uncertainty and exemplify its relevance. Agencies must manage ecosystem shifts transcending jurisdictions. Effective mitigation requires collective action heretofore rarely instituted. Our procedure supplies the climatic context to inform their decisions.

Shedding light on the effects of climate and anthropogenic pressures on the disappearance of Fagus sylvatica in the Italian lowlands: evidence from archaeo-anthracology and spatial analyses

Fagus sylvatica is one of the most representative trees of the European deciduous broadleaved forests, yet the impact of changing climatic conditions and anthropogenic pressures (anthromes) on its presence and distribution in the coastal and lowland areas of the Mediterranean Basin has long been overlooked. Here, we first analysed the local forest composition in two different time intervals (350-300 Before Current Era, BCE and 150-100 BCE) using charred wood remains from the Etruscan site of Cetamura (Tuscany, central Italy). Additionally, we reviewed all the relevant publications and the wood/charcoal data obtained from anthracological analysis in F. sylvatica, focusing on samples that date back to 4000 years before present, to better understand the drivers of beech presence and distribution during the Late Holocene (LH) in the Italian Peninsula. Then, we combined charcoal and spatial analyses to test the distribution of beech woodland at low elevation during LH in Italy and to evaluate the effect of climate change and/or anthrome on the disappearance of F. sylvatica from the lowlands. We collected 1383 charcoal fragments in Cetamura belonging to 21 woody taxa, with F. sylvatica being the most abundant species (28 %), followed by other broadleaved trees. We identified 25 sites in the Italian Peninsula with beech charcoals in the last 4000 years. Our spatial analyses showed a marked decrease in habitat suitability of F. sylvatica from LH to the present (ca. 48 %), particularly in the lowlands (0-300 m above sea level, a.s.l.) and in areas included between 300-600 m a.s.l. with a subsequent shift upwards of the beech woodland of ca. 200 m from the past to the present. In the lowland areas, where F. sylvatica has disappeared, anthrome alone and climate + anthorme had a main effect on beech distribution whitin 0-50 m a.s.l., while the climate from 50 to 300 m a.s.l. Furthermore, climate affect also the beech distrinution in the areas >300 m a.s.l., while climate + anthrome and antrhome alone were mainly focused on the lowland areas. Our results highlight the advantage of combining different approaches, such as charcoal analysis and spatial analyses, to explore biogeographic questions about the past and current distribution of F. sylvatica, with important implications for today's forest management and conservation policies.

Ecological niche model transferability of the white star apple (Chrysophyllum albidum G. Don) in the context of climate and global changes

Chrysophyllum albidum is a forest food tree species of the Sapotaceae family bearing large berries of nutrition, sanitary, and commercial value in many African countries. Because of its socioeconomic importance, C. albidum is threatened at least by human pressure. However, we do not know to what extent climate change can impact its distribution or whether it is possible to introduce the species in other tropical regions. To resolve our concerns, we decided to model the spatial distribution of the species. We then used the SDM package for data modeling in R to compare the predictive performances of algorithms among the most commonly used: three machine learning algorithms (MaxEnt, boosted regression trees, and random forests) and three regression algorithms (generalized linear model, generalized additive models, and multivariate adaptive regression spline). We performed model transfers in tropical Asia and Latin America. At the scale of Africa, predictions with respect to Maxent under Africlim (scenarios RCP 4.5 and RCP 8.5, horizon 2055) and MIROCES2L (scenarios SSP245 and SSP585, horizon 2060) showed that the suitable areas of C. albidum, within threshold values of the most contributing variables to the models, will extend mostly in West, East, Central, and Southern Africa as well as in East Madagascar. As opposed to Maxent, in Africa, the predictions for the future of BRT and RF were unrealistic with respect to the known ecology of C. albidum. All the algorithms except Maxent (for tropical Asia only), were consistent in predicting a successful introduction of C. albidum in Latin America and tropical Asia, both at present and in the future. We therefore recommend the introduction and cultivation of Chrysophyllum albidum in the predicted suitable areas of Latin America and tropical Asia, along with vegetation inventories in order to discover likely, sister or vicarious species of Chrysophyllum albidum that can be new to Science. Africlim is more successful than MIROCES2L in predicting realistic suitable areas of Chrysophyllum albidum in Africa. We therefore recommend to the authors of Africlim an update of Africlim models to comply with the sixth Assessment Report (AR6) of IPCC.

How could climate change influence the distribution of the black soldier fly, Hermetiaillucens (Linnaeus) (Diptera, Stratiomyidae)?

The black soldier fly, Hermetiaillucens (Linnaeus, 1758), is a saprophagous species used to decompose organic matter. This study proposes a distribution model of H.illucens to illustrate its current and future distribution. The methodology includes data collection from the Global Biodiversity Information Facility (GBIF), complemented with iNaturalist, manual expert curation of occurrence records, six species distribution models algorithms and one ensemble model. The average temperature of the driest annual quarter and the precipitation of the coldest annual quarter were the key variables influencing the potential distribution of H.illucens. The distribution range is estimated to decrease progressively and their suitable habitats could change dramatically in the future due to global warming. On the other hand, current optimal habitats would become uninhabitable for the species, mainly at low latitudes. Under this scenario, the species is projected to move to higher latitudes and elevations in the future. The results of this study provide data on the distribution of H.illucens, facilitating its location, management and sustainable use in current and future scenarios.

Phylogeography and colonization pattern of subendemic round-leaved oxeye daisy from the Dinarides to the Carpathians

The Carpathians are an important biodiversity hotspot and a link between mountain ranges on the European continent. This study investigated the phylogeography of one the Carpathian subendemics, Leucanthemum rotundifolium, which is distributed throughout the range and in one isolated population outside it. Range-wide sampling was used to examine phylogeographic patterns by sequencing uniparentally inherited chloroplast markers that exemplify seed dispersal. Reconstruct Ancestral State in Phylogenies (RASP) software, Bayesian binary Markov Chain Monte Carlo (BBM) analysis, and ecological niche modeling based on concatenated results of five algorithms were used to infer migration routes and examine links with other species through phylogeny. The round-leaved oxeye daisy is an example of organisms that reached the Carpathians through a southern "Dacian" migration route, most probably through long-distance dispersal. Dating placed the events in the Pleistocene and supported migrations during cooler periods and stasis/isolation followed by separation in the interglacials. Haplotype diversification indicated that after L. rotundifolium reached the area around the Fagaras Mountains, several migration events occurred leading to colonization of the Southern Carpathians followed by migration to the Apuseni Mountains, the Eastern Carpathians, and finally the Western Carpathians. The results are consistent with previous phylogeographic studies in this region and indicate several novel patterns.

Climatic Suitability and Distribution Overlap of Sawflies (Hymenoptera: Diprionidae) and Threatened Populations of Pinaceae

Ecological Niche Models (ENM) are tools used to predict suitability, based on climatic variables selected and occurrence data of the target species, and characterize the environmental space. Sawflies (Hymenoptera: Diprionidae) are one of the main factors threatening forest health in Mexico, with cyclical population outbreaks and a wide range of hosts. In the present paper, we calculate the climatic niche in Mexico of three diprionids, Neodiprion abietis (Harris), N. omosus Smith, and Zadiprion rohweri (Middleton); the first and the latter with recent records in Mexico, and N. omosus with presence in Mexico and Guatemala; contrasting them against the distribution records of host species in the country. The climatic suitability of N. abietis was high in the Sierra Madre Occidental where its hosts, Pinus ponderosa, P. strobiformis, and P. menziesii are distributed. For N. omosus, the environmental suitability was projected towards the Southern Altiplano, where it coincides with a small presence of its hosts P. leiophylla and P. ayacahuite; however, it was possible to calculate its coincidence with more hosts in other biogeographic provinces. Pinaceae species considered under threat, Abies concolor, P. monophylla, and P. strobiformis, have populations within the environmental suitability of the sawflies.

Two Sides of the Same Desert: Floristic Connectivity and Isolation Along the Hyperarid Coast and Precordillera in Peru and Chile

In this study we aim at refining our understanding of the floristic connectivity of the loma- and precordillera floras of southern Peru and northern Chile and the parameters determining vegetation cover in this region. We used multivariate analyses to test for floristic- and environmental similarity across 53 precordillera and loma locations in Peru and Chile. We propose the use of predictive modeling in estimating the extent of desert vegetation as a complementary method to remote sensing. We created habitat suitability models for the vegetation on the coast and in the precordillera based on a combination of latent bioclimatic variables and additional environmental predictors using Maxent. We found Peruvian and Chilean lomas to be strongly floristically differentiated, as are the Chilean precordillera and lomas. Conversely, there is clear connectivity between both the Peruvian loma- and precordillera floras on the one hand and the Peruvian and Chilean precordillera floras on the other. Divergent environmental conditions were retrieved as separating the precordillera and lomas, while environmental conditions are not differentiated between Peruvian and Chilean lomas. Peruvian and Chilean precordilleras show a gradual change in environmental conditions. Habitat suitability models of vegetation cover retrieve a gap for the loma vegetation along the coast between Peru and Chile, while a continuous belt of suitable habitats is retrieved along the Andean precordillera. Unsuitable habitat for loma vegetation north and south of the Chilean and Peruvian border likely represents an ecogeographic barrier responsible for the floristic divergence of Chilean and Peruvian lomas. Conversely, environmental parameters change continuously along the precordilleras, explaining the moderate differentiation of the corresponding floras. Our results underscore the idea of the desert core acting as an ecogeographic barrier separating the coast from the precordillera in Chile, while it has a more limited isolating function in Peru. We also find extensive potentially suitable habitats for both loma- and precordillera vegetation so far undetected by methods of remote sensing.

Modeling of Valeriana wallichii Habitat Suitability and Niche Dynamics in the Himalayan Region under Anticipated Climate Change

An increase in atmospheric greenhouse gases necessitates the use of species distribution models (SDMs) in modeling suitable habitats and projecting the impact of climate change on the future range shifts of the species. The present study is based on the BIOMOD ensemble approach to map the currently suitable habitats and predict the impact of climate change on the niche shift of Valeriana wallichii. We also studied its niche dynamics using the ecospat package in R software. Values of the area under curve (AUC) and true skill statistics (TSS) were highly significant (>0.9), which shows that the model has run better. From 19 different bioclimatic variables, only 8 were retained after correlation, among which bio_17 (precipitation of driest quarter), bio_1 (annual mean temperature), and bio_12 (annual mean precipitation) received the highest gain. Under future climate change, the suitable habitats will be significantly contracted by −94% (under representative concentration pathway RCP 8.5 for 2070) and −80.22% (under RCP 8.5 for 2050). There is a slight increase in habitat suitability by +16.69% (RCP 4.5 for 2050) and +8.9% (RCP 8.5 for 2050) under future climate change scenarios. The equivalency and similarity tests of niche dynamics show that the habitat suitability for current and future climatic scenarios is comparable but not identical. Principal Component Analysis (PCA) analysis shows that climatic conditions will be severely affected between current and future scenarios. From this study, we conclude that the habitats of Valeriana wallichii are highly vulnerable to climate shifts. This study can be used to alleviate the threat to this plant by documenting the unexplored populations, restoring the degraded habitats through rewilding, and launching species recovery plans in the natural habitats.

'Fly to a Safer North': Distributional Shifts of the Orchid Ophrys insectifera L. Due to Climate Change

Numerous orchid species around the world have already been affected by the ongoing climate change, displaying phenological alterations and considerable changes to their distributions. The fly orchid (Ophrys insectifera L.) is a well-known and distinctive Ophrys species in Europe, with a broad distribution across the continent. This study explores the effects of climate change on the range of O. insectifera, using a species distribution models (SDMs) framework that encompasses different climatic models and scenarios for the near- and long-term future. The species' environmentally suitable area is projected to shift northwards (as expected) but downhill (contrary to usual expectations) in the future. In addition, an overall range contraction is predicted under all investigated combinations of climatic models and scenarios. While this is moderate overall, it includes some regions of severe loss and other areas with major gains. Specifically, O. insectifera is projected to experience major area loss in its southern reaches (the Balkans, Italy and Spain), while it will expand its northern limits to North Europe, with the UK, Scandinavia, and the Baltic countries exhibiting the largest gains.

The contribution of roadsides to connect grassland habitat patches for butterflies in landscapes of contrasting permeability

Roadsides, in particular those being species-rich and of conservation value, are considered to improve landscape permeability by providing corridors among habitat patches and by facilitating species' dispersal. However, little is known about the potential connectivity offered by such high-value roadsides. Using circuit theory, we modelled connectivity provided by high-value roadsides in landscapes with low or high permeability in south-central Sweden, with 'permeability' being measured by the area of semi-natural grasslands. We modelled structural connectivity and, for habitat generalists and specialists, potential functional connectivity focusing on butterflies. We further assessed in which landscapes grassland connectivity is best enhanced through measures for expanding the area of high-value roadsides. Structural connectivity provided by high-value roadsides resulted in similar patterns to those of a functional approach, in which we modelled habitat generalists. In landscapes with low permeability, all target species showed higher movements within compared to between grasslands using high-value roadsides. In landscapes with high permeability, grassland generalists and specialists showed the same patterns, whereas for habitat generalists, connectivity provided by high-value roadsides and grasslands was similar. Increasing the ratio of high-value roadsides can thus enhance structural and functional connectivity in landscapes with low permeability. In contrast, in landscapes with high permeability, roadsides only supported movement of specialised species. Continuous segments of high-value roadsides are most efficient to increase connectivity for specialists, whereas generalists can utilize also short segments of high-value roadsides acting as stepping-stones. Thus, land management should focus on the preservation and restoration of existing semi-natural grasslands. Management for enhancing grassland connectivity through high-value roadsides should aim at maintaining and creating high-value roadside vegetation, preferably in long continuous segments, especially in landscapes with low permeability.

Maxent Modeling for Identifying the Nature Reserve of Cistanche deserticola Ma under Effects of the Host (Haloxylon Bunge) Forest and Climate Changes in Xinjiang, China

Cistanche deserticola Ma is a traditional Chinese medicinal plant exclusively parasitizing on the roots of Haloxylon ammodendron (C. A. Mey.) Bunge and H. Persicum Bunge ex Boiss and the primary cultivated crop of the desert economy. Its wild resources became scarce due to over-exploitation and poaching for economic benefits. To protect the biological diversity of the desert Haloxylon–Cistanche community forest, the optimal combination of desert ecology and economy industry, and their future survival, this paper examines the conservation areas of wild C. deserticola from the perspective of hosts’ effects and climate changes. To identify conservation areas, the potential distributions generated by MaxEnt in two strategies (AH: abiotic and hosts factors; HO: hosts factors only) compare the model’s performance, the niche range overlap, and the changing trend in climate changes. The results show the following: (1) The HO strategy is more suitable for prediction and identifying the core conservation areas in hosts and climate changes (indirectly affected by host distributions) for C. deserticola. (2) The low-suitable habitat and the medium-suitable habitat are both sensitive to the climate changes; the reduction reaches 48.2% (SSP585, 2081–2100) and 26.6%(SSP370, 2081–2100), respectively. The highly suitable habitat is always in growth, with growth reaching 27.3% (SSP585, 2081–2100). (3) Core conservation areas and agriculture and education areas are 317,315.118 km2 and 319,489.874 km2, respectively. This study developed a predictive model for Maxent under climate change scenarios by limiting host and abiotic factors and inverted the natural habitat of C. deserticola to provide scientific zoning for biodiversity conservation in desert Haloxylon–Cistanche community forests systems, providing an effective reference for decision makers.

Tree Mortality Risks Under Climate Change in Europe: Assessment of Silviculture Practices and Genetic Conservation Networks

General Context: Climate change can positively or negatively affect abiotic and biotic drivers of tree mortality. Process-based models integrating these climatic effects are only seldom used at species distribution scale.

Objective: The main objective of this study was to investigate the multi-causal mortality risk of five major European forest tree species across their distribution range from an ecophysiological perspective, to quantify the impact of forest management practices on this risk and to identify threats on the genetic conservation network.

Methods: We used the process-based ecophysiological model CASTANEA to simulate the mortality risk of Fagus sylvatica, Quercus petraea, Pinus sylvestris, Pinus pinaster, and Picea abies under current and future climate conditions, while considering local silviculture practices. The mortality risk was assessed by a composite risk index (CRIM) integrating the risks of carbon starvation, hydraulic failure and frost damage. We took into account extreme climatic events with the CRIMmax, computed as the maximum annual value of the CRIM.

Results: The physiological processes' contributions to CRIM differed among species: it was mainly driven by hydraulic failure for P. sylvestris and Q. petraea, by frost damage for P. abies, by carbon starvation for P. pinaster, and by a combination of hydraulic failure and frost damage for F. sylvatica. Under future climate, projections showed an increase of CRIM for P. pinaster but a decrease for P. abies, Q. petraea, and F. sylvatica, and little variation for P. sylvestris. Under the harshest future climatic scenario, forest management decreased the mean CRIM of P. sylvestris, increased it for P. abies and P. pinaster and had no major impact for the two broadleaved species. By the year 2100, 38–90% of the European network of gene conservation units are at extinction risk (CRIMmax=1), depending on the species.

Conclusions: Using a process-based ecophysiological model allowed us to disentangle the multiple drivers of tree mortality under current and future climates. Taking into account the positive effect of increased CO2 on fertilization and water use efficiency, average mortality risk may increase or decrease in the future depending on species and sites. However, under extreme climatic events, our process-based projections are as pessimistic as those obtained using bioclimatic niche models.