Habitat Suitability Models Research Articles

Northern spotted owl nesting habitat under high potential wildfire threats along the California Coastal Redwood Forest

Large and severe wildfires, exacerbated by climate change and human behavior, are occurring more frequently in many forests across the western United States. While wildfire is a natural part of most terrestrial ecosystems, rapidly changing fire regimes have the potential to alter habitat beyond the adaptive capabilities of species. Spatial assessments of wildfire risks to species habitat may allow managers to pinpoint locations for management activities. To illustrate this, we spatially assessed wildfire risk within habitat that supports the nesting activity of the federally threatened northern spotted owl (Strix occidentalis caurina) in the California redwood coast ecoregion. To accomplish this, we built a scale-optimized ensemble nesting habitat suitability model and identified habitat with the highest wildfire hazard potential. Percent canopy cover at 100-m scale, slope at 400-m scale, and January precipitation at 800-m scale were the most influential environmental covariates for predicting northern spotted owl nesting habitat. Nearly 60% of nesting habitat was predicted to be at high or very high (>1986 index value) wildfire risks. We identified three areas in the Maple Creek Area of Humboldt County, Jackson State Demonstration Forest in Mendocino County, and Point Reyes National Seashore in Marin County, California with a high concentration of nesting habitat that are at a very high risk of experiencing high severity wildfires. We recommend these areas be targeted for future research to understand the impact of wildfire on northern spotted owl as well as management attention.

Identifying suitable habitat for Ixodes scapularis (Acari: Ixodidae) infected with Anaplasma phagocytophilum (Rickettsiales: Anaplasmataceae), Babesia microti (Piroplasmida: Babesiidae), and Borrelia miyamotoi (Spirochaetales: Spirochaetaceae) to guide surveillance efforts in the eastern United States.

Understanding the distribution of infected ticks is informative for the estimation of risk for tickborne diseases. The blacklegged tick, Ixodes scapularis (Acari: Ixodidae), is the primary vector for 7 medically significant pathogens in United States. However, knowledge of the ranges of these pathogens in host-seeking ticks is incomplete, particularly for those occurring at low prevalence. To aid in prioritizing costly field sampling efforts, we estimated ranges of suitable habitat for Anaplasma phagocytophilum, Babesia microti, and Borrelia miyamotoi in the eastern United States based on existing county-level surveillance records. The resulting suitability maps were compared against those developed previously for Bo. burgdorferi s.s., which shares similar ecology but has been detected in a greater number of counties. The overall accuracy of the habitat suitability models was high (AUC ≥ 0.92) for all 4 pathogens. The most important predictors were related to temperature and moisture. The upper midwestern and northeastern states were predicted to be highly suitable for all 4 pathogens. Based on our models, we prioritized sampling in 431, 275, and 539 counties currently lacking pathogen records that our models classified as suitable for A. phagocytophilum, Ba. microti, and Bo. miyamotoi, respectively. As a second-tier priority, we identified 311 (A. phagocytophilum), 590 (Ba. microti), and 252 (Bo. miyamotoi) counties, based on high suitability scores for Bo. burgdorferi. Our models can be used to improve cost-effectiveness of field sampling efforts aimed at improving accuracy and completeness of pathogen distribution maps.

The habitat-suitability models of the European mole cricket (Gryllotalpa gryllotalpa) as information tool for conservation and pest management

The European mole cricket, Gryllotalpa gryllotalpa, feeds on a wide range of crops and can also damage plants with its burrowing activities. In suitable habitats (like those with damp, rich soils in flood plains), G. gryllotalpa numbers can increase to high levels. On the other hand, the abundance of G. gryllotalpa has dramatically decreased in north-western Europe partly due to direct eradication and excessive pest control. Using habitat suitability modelling, we identified areas suitable for G. gryllotalpa occurrence based on previous reports of its occurrence and based on environmental data. We limited our study area to regions where G. gryllotalpa is the only known Gryllotalpa species. The most important variables in our models were found to be relative air humidity and minimum soil temperature of the coldest month. We suggest that soil temperature is a limiting factor for European mole cricket occurrence in the Czech Republic because most areas in the country experience soil temperatures just below 0 °C, while most reports of G. gryllotalpa occurrence in Europe are from areas where the soil temperature does not drop below 0 °C. The models we have developed can provide information on possible occurrences of the mole cricket and thus improve the decision-making process both in the field of pest control and the conservation of this species.

Predicting the potential distribution of wheatear birds using stacked generalization-based ensembles

Habitat suitability models, usually referred to as species distribution models (SDMs), are widely applied in ecology for many purposes, including species conservation, habitat discovery, and gain evolutionary insights by estimating the distribution of species. Machine learning algorithms as well as statistical models have been recently used to predict the distribution of species. However, they seemed to have some limitations due to the data and the models used. Therefore, this study proposes a novel approach for assessing habitat suitability based on ensemble learning techniques. Three heterogeneous ensembles were built using the stacked generalization method to model the distribution of four wheatear species (Oenanthe deserti, Oenanthe leucopyga, Oenanthe leucura, and Oenanthe oenanthe) located in Morocco. Initially, a set of base-learners were constructed by virtue of training for each specie's dataset six machine learning algorithms (Multi-Layer Perceptron (MLP), Support Vector Classifier (SVC), K-nearest neighbors (KNN), Decision Trees (DT), Gradient Boosting Classifier (GB), and Random Forest (RF)). Then, the predictions of these base learners were fed as training data to train three meta-learners (Logistic Regression (LR), SVC, and MLP). To evaluate and assess the performance of the proposed approaches, we used: (1) six performance criteria (accuracy, recall, precision, F1-score, AUC, and TSS), (2) Borda Count (BC) ranking method based on multiple criteria to rank the best-performing models, and (3) Scott Knott (SK) test to statistically compare the performance of the presented models. The results based on the six-evaluation metrics showed that stacked ensembles outperformed their singles in all species datasets, and the stacked model with SVC as a meta-learner outperformed the other two ensembles. The results showed the potential of using ensemble learning techniques to model species distribution and recommend the use of the stacked generalization technique as a combination strategy since it gave better results compared to single models in four wheatear species datasets. Moreover, to assess the impact of future climate changes on the distribution of the four wheatear species, the best-performing distribution model was selected and projected into the current and future climatic conditions. The distributions of the Moroccan wheatear birds were found to be slightly affected by future climate changes.

Assessment of the genetic diversity of Chinese freshwater mussels and refuge areas in the Yangtze River floodplain

Abstract Freshwater mussels are one of the most diverse and endangered faunas worldwide. Owing to the continuing global biodiversity loss, it is essential to identify and protect populations that are not severely affected by human disturbances and ensure that natural genetic diversity is not inevitably lost. The generation of baseline genetic diversity data will help guide species conservation and restoration plans in the Yangtze River Basin where freshwater mussels are facing multiple threats and where strong declines have been observed. The genetic diversity of freshwater mussels was assessed using 818 mtDNA cytochrome c oxidase subunit 1 (COI), 565 28S rRNA and 509 COI + 28S datasets, and refuge areas in the Yangtze River floodplain were predicted using a Maxent habitat suitability model. The results showed that the genetic diversity of Aculamprotula spp., Sinosolenaia carinata, Cuneopsis rufescens, Lamprotula cornuumlunae, Lanceolaria lanceolata, Ptychorhynchus pfisteri, Schistodesmus spp. and Sinohyriopsis cumingii was lower than that of other freshwater mussels, which indicated that the conservation status of these species should be prioritized. The habitat suitability modelling showed that Poyang Lake and Dongting Lake basins (lakes and tributary rivers connected to the Yangtze River mainstem) present the most suitable habitats for freshwater mussels, indicating that lateral hydrological connectivity may be the most important factor in maintaining the genetic diversity of Chinese freshwater mussels. Consequently, Poyang Lake and Dongting Lake basins should be established as protected areas. This study provides valuable information for the conservation and management of freshwater mussel biodiversity in the Yangtze River basin, which will not only help conserve this vulnerable group but will also provide wider benefits to freshwater ecosystems.

Spatial distributions, environmental drivers and co-existence patterns of key cold-water corals in the deep sea of the Azores (NE Atlantic)

Habitat-forming cold-water corals (CWCs) represent a key component of deep-sea benthic communities and a priority target for conservation. Although research efforts have been mounting to try and identify the drivers of CWC distributions, progress has been limited by the scarcity of ecological data. The present work employs habitat suitability models (HSMs) to estimate spatial distributions, environmental drivers and co-existence patterns of 14 habitat-forming CWCs in the Azores, an area considered a hotspot of coral diversity in the Atlantic. The modelled CWCs showed a strong bathymetric zonation, which seems to be determined by the vertical stratification of water masses in the region. In particular, the modelled CWCs can be clustered in four groups named after the isopycnal (vertical) layers in which Atlantic water masses are organized: species restricted to upper water masses, species extending down from upper water masses, species restricted to intermediate water masses and species extending up from deep water masses. Horizontal patterns further indicate that the Azores Current and different production regimes north and south of the archipelago likely influence the distribution of CWCs in sub-surface waters. Such results have important implications for the regional management of deep-sea benthic communities and, in particular, for the design of representative networks of protected areas. The combined habitat of all modelled species covered only 11%. Given that they all possess the characteristics of benthic foundation organisms and represent indicator taxa of vulnerable marine ecosystems all the modelled species should be viewed as important targets for conservation. The lace coral Errina dabneyi deserves particular attention since this species appears to be endemic to the Azores and has a very limited estimated distribution.

Habitat connectivity supports the local abundance of fire salamanders (Salamandra salamandra) but also the spread of Batrachochytrium salamandrivorans

ContextHabitat connectivity can stabilise animal populations by facilitating immigration and genetic exchange, but it increases the risk of infectious diseases being spread by hosts. Chytridiomycosis caused by Batrachochytrium salamandrivorans (Bsal) threatens European salamander diversity. The extent to which the connectivity of populations of fire salamanders (Salamandra salamandra) contributes to the spread of Bsal remains unclear.ObjectivesWe analysed the impact of habitat connectivity of fire salamanders on the spread of Bsal. Moreover, we show how local salamander abundance is associated with habitat connectivity over a five-year period.MethodsWe developed fire salamander habitat suitability models (HSMs) for the Eifel area (Germany), currently considered the core of the range of Bsal in Europe. Habitat models were used to calculate pairwise resistance between salamander occurrences to test whether Bsal presence and salamander abundance were associated with habitat connectivity.ResultsFire salamanders are widely distributed in the Eifel. Solid bedrock and topographic positioning were important predictors of stream suitability as breeding habitats, while deciduous forests and grassland cover determined overall fire salamander habitat suitability along with breeding habitat suitability. Bsal-positive salamander occurrences were better-connected than Bsal-negative or untested occurrences. Nevertheless, fire salamander larvae were more abundant in well-connected sites.ConclusionThe connection of salamander populations by suitable habitat seems to support local salamander abundance while facilitating the spread of Bsal. In situ conservation measures counteracting host species connectivity to interrupt Bsal transmission pathways must be implemented with caution, as they may weaken the demographic advantages of connectivity.

Assessing Potential Habitat for Freshwater Mussels by Transferring a Habitat Suitability Model within the Ozark Ecoregion, Missouri

Habitat suitability models for freshwater mussels can inform conservation of these imperiled animals. Riverscape-scale hydrogeomorphic variables were previously used to predict suitable mussel habitat in the Meramec River basin, Missouri. We evaluated transferability of the Meramec River habitat suitability model to the Gasconade and Little Black rivers, in the Ozark Highlands ecoregion, Missouri. The best-fit models relied on transferring and adapting the original modeling framework to better represent the unique habitat characteristics of each river. Mussel bed occurrence in both rivers was associated with reaches that were classified as pools. Mussel beds in the Gasconade River were also associated with laterally stable reaches adjacent to small bluffs, distant from gravel bars, and with higher stream power indices. Mussel beds in the Little Black River were associated with reaches with higher surface water availability during low-flow conditions, lower stream power indices, and bluffs located downstream. Our results show that existing habitat models can be transferred to other streams with similar environmental conditions, but differences in watershed characteristics can affect transferability.

Population Assessments of Federally Threatened Everglades Bully in Big Cypress National Preserve, Florida, USA, Using Habitat Suitability Modeling and Micromorphology.

In Big Cypress National Preserve, the federally threatened Everglades bully (Sideroxylon reclinatum subsp. austrofloridense) is sympatric with its conspecific, more widespread relative, the Florida bully (Sideroxylon reclinatum subsp. reclinatum). In this area of overlap, the only reliable characters to distinguish the two are cryptic, micromorphological traits of the abaxial laminar surface. In order to better understand the distribution of the federally threatened taxon, we used a combination of habitat suitability modeling (HSM), field surveys, and microscopy. Using models to inform initial surveys, we collected leaf material of 96 individuals in the field, 86 of which we were able to identify to subspecies. Of these, 73 (85%) were identified as the threatened taxon, expanding both the known range and population size within Big Cypress. We used these 73 new occurrences to rerun HSMs to create a more accurate picture of where the taxon is likely to occur. A total of 15,015 hectares were predicted to be suitable habitat within Big Cypress, with 34,069 hectares across the entire study area. These model results could be used to inform the critical habitat designation for this taxon. For at-risk, cryptic taxa, such as the Everglades bully, multiple approaches are needed to inform management and conservation priorities, including the consideration of a hybridization zone.

Threatened Habitats of Carnivores: Identifying Conservation Areas in Michoacán, México

The present study contributes to bridging the gap in research related to the presence and distribution patterns of carnivore mammals in western México and identifies priority areas for biodiversity conservation in western Michoacán, México. The distribution of 11 carnivore species (Canis latrans; Urocyon cinereoargenteus; Herpailurus yagouaroundi; Leopardus pardalis; Leopardus wiedii; Puma concolor; Panthera onca; Conepatus leuconotus; Bassariscus astutus; Nasua narica; Procyon lotor) in western México was modeled through the application of a two-scale approach, including a large modeled region that corresponded to the western part of the country, for which consensus models were obtained that represent the species’ bioclimatic envelopes (historic occurrence records); and the second modeled study area that includes only the western portion of the state of Michoacán in which compounded models of the species’ habitat suitability (field occurrence records) for this region were proposed. Using species’ habitat suitability models as biodiversity units, prioritization exercises were carried out on important areas for the conservation of these species, as well as the comparison and analysis of the existing natural protected areas (NPA) and existing proposed conservation areas in the study area. The different exercises for prioritizing areas for conservation yielded similar results and show the potential percentages of the landscape that can be subjected to conservation programs. The highest conservation priority values were mainly located in the Costas del Sur and Cordillera del Sur provinces. This study signifies a flexible basis from which future studies on planning and designing a network of natural protected areas can be carried out in this region.

Forecasting Prorocentrum minimum blooms in the Chesapeake Bay using empirical habitat models

Aquaculturists, local beach managers, and other stakeholders require forecasts of harmful biotic events, so they can assess and respond to health threats when harmful algal blooms (HABs) are present. Based on this need, we are developing empirical habitat suitability models for a variety of Chesapeake Bay HABs to forecast their occurrence based on a set of physical-biogeochemical environmental conditions, and start with the dinoflagellate Prorocentrum minimum (also known as P. cordatum).To identify an optimal set of environmental variables to forecast P. minimum blooms, we first assumed a linear relationship between the environmental variables and the inverse of the logistic function used to forecast the likelihood of bloom presence, and repeated the method using more than 16,000 combinations of variables. By comparing goodness-of-fit, we found water temperature, salinity, pH, solar irradiance, and total organic nitrogen represented the most suitable set of variables. The resulting algorithm forecasted P. minimum blooms with an overall accuracy of 78%, though with a significant variability ~ 30-90% depending on region and season. To understand this variability and improve model performance, we incorporated nonlinear effects into the model by implementing a generalized additive model. Even without considering interactions between the five variables used to train the model, this yielded an increase in overall model accuracy (~ 81%) due to the model’s ability to refine the regions in which P. minimum blooms occurred. Including nonlinear interactions increased the overall model accuracy even further (~ 85%) by accounting for seasonality in the interaction between solar irradiance and water temperature. Our findings suggest that the influence of predictors of these blooms change in time and space, and that model complexity impacts the model performance and our interpretation of the driving factors causing P. minimum blooms. Apart from their forecasting potential, our results may be particularly useful when constructing explicit relationships between environmental conditions and P. minimum presence in mechanistic models.

Telemetry-based spatial–temporal fish habitat models for fishes in an urban freshwater harbour

Fish habitat associations are important measures for effective aquatic habitat management, but often vary over broad spatial and temporal scales, and are therefore challenging to measure comprehensively. We used a 9-year acoustic telemetry dataset to generate spatial–temporal habitat suitability models for seven fish species in an urban freshwater harbour, Toronto Harbour, Lake Ontario. Fishes generally occupied the more natural regions of Toronto Harbour most frequently. However, each species exhibited unique habitat associations and spatial–temporal interactions in their habitat use. For example, largemouth bass exhibited the most consistent seasonal habitat use, mainly associating with shallow, sheltered embayments with high aquatic vegetation (SAV) cover. Conversely, walleye seldom occupied Toronto Harbour in summer, with the highest occupancy of shallow, low-SAV habitats in the spring, which corresponds to their spawning period. Others, such as common carp, shifted between shallow summer and deeper winter habitats. Community level spatial–temporal habitat importance estimates were also generated, which can serve as an aggregate measure for habitat management. Acoustic telemetry provides novel opportunities to generate robust spatial–temporal fish habitat models based on wild fish behaviour, which are useful for the management of fish habitat from a fish species and community perspective.

Continent-wide recent emergence of a global pathogen in African amphibians

IntroductionEmerging infectious diseases are increasingly recognized as a global threat to wildlife. Pandemics in amphibians, caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd), have resulted in biodiversity loss at a global scale. Genomic data suggest a complex evolutionary history of Bd lineages that vary in pathogenicity. Africa harbors a significant proportion of global amphibian biodiversity, and multiple Bd lineages are known to occur there; yet, despite the decline of many host species, there are currently no described Bd-epizootics. Here, we describe the historical and recent biogeographical spread of Bd and assess its risk to amphibians across the continent of Africa.MethodsWe provide a 165-year view of host-pathogen interactions by (i) employing a Bd assay to test 4,623 specimens (collected 1908–2013); (ii) compiling 12,297 published Bd records (collected 1852–2017); (iii) comparing the frequency of Bd-infected amphibians through time by both country and region; (iv) genotyping Bd lineages; (v) histologically identifying evidence of chytridiomycosis, and (vi) using a habitat suitability model to assess future Bd risk.ResultsWe found a pattern of Bd emergence beginning largely at the turn of the century. From 1852–1999, we found low Bd prevalence (3.2% overall) and limited geographic spread, but after 2000 we documented a sharp increase in prevalence (18.7% overall), wider geographic spread, and multiple Bd lineages that may be responsible for emergence in different regions. We found that Bd risk to amphibians was highest in much of eastern, central, and western Africa.DiscussionOur study documents a largely overlooked yet significant increase in a fungal pathogen that could pose a threat to amphibians across an entire continent. We emphasize the need to bridge historical and contemporary datasets to better describe and predict host-pathogen dynamics over larger temporal scales.

Does scale or method matter for conservation? Application of directional and omnidirectional connectivity models in spatial prioritizations

IntroductionThe maintenance of habitat connections between fragmented habitat patches is vital for the conservation of wildlife populations and ecosystem functioning. The awareness of connectivity issues for species conservation has resulted in a growth of connectivity modeling and the application of these results in conservation planning. Such connectivity modeling efforts can include several decisions or data limitations, which could influence the connectivity results and ultimately a systematic conservation plan (SCP). However, there has been little investigation of how these different decisions on species, scale, and extent influence the ultimate conservation planning outcomes.MethodsWe modeled the connectivity of northern bobwhite (Colinus virginianus), North American river otter (Lontra canadensis), and black bear (Ursus americanus), three species with varying ecological requirements, through the Congaree Biosphere Region, South Carolina, USA. We modeled habitat suitability for each species using boosted regression trees and converted these results into resistance layers for the connectivity analyses. We compared models for each species at multistate regional and local extents using directional and omnidirectional circuit theory approaches. We then used the results from each modeling combination as conservation goals for three different SCPs to determine how connectivity modeling decisions may influence geographic conservation decisions.ResultsThere was substantial positive spatial correlation between the three connectivity models of each species, and there appeared to be general agreement among mammals as to most important primary corridors. Across all species, the greatest agreement was between the omnidirectional and local directional models as compared with the regional directional plan, which highlighted a unique corridor. The omnidirectional conservation plan required the least amount of planning units to achieve its conservation goals, followed by the local and then regional directional plans that required over 200 km2more land area to be conserved.DiscussionOur results indicate that overall variations in connectivity modeling decisions may have only a moderate impact on the identification of important movement corridors for conservation at the local scale. Practitioners should base modeling decisions on the ecology of the study region, conservation question, and available computing resource.

A greener Loess Plateau in the future: moderate warming will expand the potential distribution areas of woody species

Understanding the effect of future global warming on the distribution and diversity of woody species in the Loess Plateau is critical to the vegetation restoration and rebuilding of this area and yet is highly challenging. In the absence of enough experimental data, projection based on species distribution models is the best option for assessing the future shift in species distribution areas. Here, via a comprehensive habitat suitability model, we present an assessment of potential distribution area change for two plant life forms with a total of 42 key woody species, including 21 tree species and 21 shrub species, on the Loess Plateau under multiple scenarios, and based on this information, we explore the responses of regional potential woody species diversity to future global warming. The results showed that moderate warming will promote the expansion of potential distribution areas for most woody species and generally increase regional species diversity, which will result in a greener Loess Plateau. Our results also show that shrub species are more drought-tolerant and less adversely affected by climate change and thus should be considered a priority in vegetation restoration, especially in the arid area of the northern Loess Plateau. These results are helpful for identifying priority restoration areas, selecting appropriate species for artificial planting, and providing useful information for vegetation restoration and management in the future.

The ‘lawnification’ of Australia’s eastern grassy woodlands: the past, current and likely future spread of an invasive perennial grass, Bothriochloa pertusa

Many of today’s damaging invasive plants were intentionally introduced for pasture development and amenity. By examining the introduction history and consequent spread of these species, we can identify factors associated with their successful establishment and dominance. Using collated presence/absence and cover data, alongside a review of the literature and discussions with land managers, we present a comprehensive analysis of the introduction history and spread of the environmental and agricultural grassy weed, Bothriochloa pertusa (L.) A.Camus (Indian couch) throughout Queensland, Australia. Using this data, we also perform habitat suitability models to predict its potential distribution and local-scale cover across Queensland in relation to key environmental variables. We found that B. pertusa was introduced on multiple occasions and across a large area of Queensland, despite re-occurring doubts and poor evidence for its benefit to livestock production. Livestock grazing, associated disturbances (i.e. land clearing, soil erosion) and climatic extremes were commonly associated with its spread throughout the landscape. In 2020 the main area of B. pertusa invasion as indicated by occurrence records spanned 28,537,600 ha. Results from the habitat suitability models suggest the occurrence and local-scale cover of B. pertusa is largely determined by climate variables and the foliage projective cover of trees. Based on these results B. pertusa still has considerable capacity to spread and increase in dominance across many areas of Queensland, particularly further west and south of its current range. The introduction and spread history of B. pertusa suggests propagule pressure, traits, climate, land management and cultural perceptions are all key factors implicated in the spread of B. pertusa. Where B. pertusa has become dominant there has been a major shift in lifeform from native perennial tussock species to a grazing tolerant stoloniferous species. To slow this process of ‘lawnification’ we recommend more conservative grazing strategies and strategically selected protected areas to maintain cover of grazing sensitive native tussock grass species.

Current and future distribution of a parasite with complex life cycle under global change scenarios: Echinococcus multilocularis in Europe.

Global change is expected to have complex effects on the distribution and transmission patterns of zoonotic parasites. Modelling habitat suitability for parasites with complex life cycles is essential to further our understanding of how disease systems respond to environmental changes, and to make spatial predictions of their future distributions. However, the limited availability of highquality occurrence data with high spatial resolution often constrains these investigations. Using 449 reliable occurrence records for Echinococcus multilocularis from across Europe published over the last 35 years, we modelled habitat suitability for this parasite, the aetiological agent of alveolar echinococcosis, in order to describe its environmental niche, predict its current and future distribution under three global change scenarios, and quantify the probability of occurrence for each European country. Using a machine learning approach, we developed large-scale (25 × 25 km) species distribution models based on seven sets of predictors, each set representing a distinct biological hypothesis supported by current knowledge of the autecology of the parasite. The best-supported hypothesis included climatic, orographic and land-use/land-cover variables such as the temperature of the coldest quarter, forest cover, urban cover and the precipitation seasonality. Future projections suggested the appearance of highly suitable areas for E. multilocularis towards northern latitudes and in the whole Alpine region under all scenarios, while decreases in habitat suitability were predicted for central Europe. Our spatially explicit predictions of habitat suitability shed light on the complex responses of parasites to ongoing global changes.

Seasonal activity and depth distribution of resident yellow-phase American eels (Anguilla rostrata) in a large fluvial ecosystem

Abstract The American eel (Anguilla rostrata) is a catadromous species occupying diverse habitats, but little is known about the specific activities of this elusive nocturnal fish. Mobile radio and acoustic telemetry were used to locate 33 transmitter-implanted resident yellow eels (729 ± 22 mm TL), acquiring 1613 locations from 2014 to 2017 in a 21-km2 slow-flowing section of the upper St. Lawrence River. Measurements of distance moved, water depth, and temperature were used to study activity, homing, and site fidelity. Movement was greatest in spring, late April (422 m, median semi-monthly), after emergence from winter dormancy, from their deepest habitat (3.71 ± 0.06 m) to their shallowest (1.74 ± 0.17 m). Activity was low in early summer and early fall (69 m). As temperature reached a maximum during midsummer (24.3 ± 0.29°C), most eels became more active (106 m) and moved deeper (2.46 ± 0.28 m), probably following prey fish. Activity increased in mid-to-late fall (277 m), decreased considerably at ≲8°C when settling into their winter habitat, and ceased at ≲4°C. Temperatures of ≃10°C (8.1–11.1°C) corresponded with the greatest seasonal activity and spring/fall commercial hoop-net catches. These spatial and temporal habitat insights can help focus sampling and assessment procedures, as well as habitat suitability modelling.

Current and Future Habitat Suitability Models for Four Ticks of Medical Concern in Illinois, USA.

The greater U.S. Midwest is on the leading edge of tick and tick-borne disease (TBD) expansion, with tick and TBD encroachment into Illinois occurring from both the northern and the southern regions. To assess the historical and future habitat suitability of four ticks of medical concern within the state, we fit individual and mean-weighted ensemble species distribution models for Ixodes scapularis, Amblyomma americanum, Dermacentor variabilis, and a newly invading species, Amblyomma maculatum using a variety of landscape and mean climate variables for the periods of 1970-2000, 2041-2060, and 2061-2080. Ensemble model projections for the historical climate were consistent with known distributions of each species but predicted the habitat suitability of A. maculatum to be much greater throughout Illinois than what known distributions demonstrate. The presence of forests and wetlands were the most important landcover classes predicting the occurrence of all tick species. As the climate warmed, the expected distribution of all species became strongly responsive to precipitation and temperature variables, particularly precipitation of the warmest quarter and mean diurnal range, as well as proximity to forest cover and water sources. The suitable habitat for I. scapularis, A. americanum, and A. maculatum was predicted to significantly narrow in the 2050 climate scenario and then increase more broadly statewide in the 2070 scenario but at reduced likelihoods. Predicting where ticks may invade and concentrate as the climate changes will be important to anticipate, prevent, and treat TBD in Illinois.

Planning Ginkgo biloba future fruit production areas under climate change: Application of a combinatorial modeling approach

Ginkgo biloba forests are widely studied for their fruits’ high medicinal, edible, and economic values with an increasing global demand for its fruits supply. The impact of climate change on the habitat suitability of this species has been assessed in previous studies. This study was to address the climate change impact on both habitat suitability and fruit yield. We used fruit grain weight to represent fruit productivity and quality of Ginkgo fruit forests and related it to climate variables to develop a climate response function (Method I). Meanwhile, we also built a Maxent habitat suitability model and associated it with fruit grain weight (Method II). Results showed that Method I provided much higher prediction accuracy (R2 = 0.68) than Method II (R2 = 0.39). We combined Method I with the species habitat model to predict suitable production areas of Ginkgo fruit to achieve high fruit production within suitable habitats for the contemporary and future periods. We found that Ginkgo fruit grain weight was mainly affected by mean annual average temperature (MAT) and mean annual precipitation (MAP), while the degree-days below 0 ℃ (DD < 0) was the main climate factor limiting the distribution of Ginkgo fruit forests suitable habitat. The combined model predictions showed that the suitable production areas of Ginkgo fruit forests are expected to decrease and move northeastward in the future under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. Our predictions can be used to maximize Ginkgo fruit quality production while minimizing the risk of low survival in the planning of Ginkgo fruit forest production areas.