Changes In Distribution Of Species Research Articles

Vulvovaginal candidiasis clinical signs, and distribution of Candida species

Background: Vulvovaginal candidiasis is a global issue of concern due to its association with economic costs, sexually transmitted infections, and ascending genital tract infection. The aim of this study was to determine clinical signs and species distribution of Candida species causing vulvovaginal candidiasis. Methods: A cross-sectional study was conducted from December to June 2021-2024 among 400 women attending Obstetrics and Gynecology outpatient clinics in Sana'a City. The study involved collecting vaginal swabs from each participant and analyzing them in a microbiology laboratory. The swabs were used to identify yeast cells, fungal culturing, and germ tube formation tests. The study also used the VITEK II system to confirm species identification, with the VITEK® 2 YST ID identification card being used to identify Candida species. Results: A study of 400 women found that 91.8% were infected with Candida albicans, while 8.2% were infected with other non-Candida albicans. The majority were aged 26-35, with secondary education being the most common. Most were married, with 1-3 pregnancies. The most common sign distribution was vaginal discharge with a 99.5% prevalence. Dysuria was the lowest, with a 65.0% prevalence. Candida species were most frequently isolated, with Candida albicans being the most common. Candida tropicalis was found in 1 out of 6 women, while Candida dubliniensis, Candida famata, Candida glabrata, and Candida lusitaniae were found in 1 out of 6 women. Conclusions: The high prevalence rate of vulvovaginal candidiasis and observation of a low prevalence rate of nonalbicans Candida species in the present study substantiate the importance of conducting continuous epidemiological surveys to measure changes in species distribution from C. albicans to non-albicans Candida species in Yemen.

Integrating local knowledge into public policy instruments for enhancing restoration: A study case from western Mexican tropical dry forest

Local knowledge (LK) is often overlooked in the decision-making process during landscape restoration process. In this study, we focus on the Zicuirán-Infiernillo Biosphere Reserve as a case study. We propose a framework to incorporate LK into public policy instruments for implementing restoration interventions in Mexican protected natural areas (PNAs). Through semi-structured interviews, participant observation, and informal talks, conducted with residents from two communities located in the buffer zone and the border area of the reserve, we gathered valuable insights regarding the following: (1) the inhabitants' LK of the ecology and contributions of tropical dry forest, (2) the socioeconomic and environmental issues identified by these communities in their localities, (3) ecological and socioeconomic actions suggested by the residents to recover the forest or halt its degradation, and (4) the role of institutions and local organizations in restoration and conservation processes. Our findings indicate that residents recognized changes in species distribution and identified native trees that are tolerant to drought. Moreover, they acknowledged the beneficial contributions provided by forests, including climate and water cycle regulation, oxygen supply, and raw materials. Local people also demonstrated their awareness of environmental and socioeconomic issues and proposed activities to reverse vegetation cover loss and halt forest degradation. While reforestation emerged as the primary solution for forest recovery, assisted natural regeneration and natural regeneration were also suggested. Based on our results, we propose a framework that emphasizes a robust knowledge exchange among stakeholders, for facilitating the inclusion of LK in an ecological restoration-based education program. It is crucial for Mexican public policy instruments operating in PNAs to consider local knowledge to enhance the effectiveness of ecological restoration.

Treating gaps and biases in biodiversity data as a missing data problem.

Big biodiversity data sets have great potential for monitoring and research because of their large taxonomic, geographic and temporal scope. Such data sets have become especially important for assessing temporal changes in species' populations and distributions. Gaps in the available data, especially spatial and temporal gaps, often mean that the data are not representative of the target population. This hinders drawing large-scale inferences, such as about species' trends, and may lead to misplaced conservation action. Here, we conceptualise gaps in biodiversity monitoring data as a missing data problem, which provides a unifying framework for the challenges and potential solutions across different types of biodiversity data sets. We characterise the typical types of data gaps as different classes of missing data and then use missing data theory to explore the implications for questions about species' trends and factors affecting occurrences/abundances. By using this framework, we show that bias due to data gaps can arise when the factors affecting sampling and/or data availability overlap with those affecting species. But a data set per se is not biased. The outcome depends on the ecological question and statistical approach, which determine choices around which sources of variation are taken into account. We argue that typical approaches to long-term species trend modelling using monitoring data are especially susceptible to data gaps since such models do not tend to account for the factors driving missingness. To identify general solutions to this problem, we review empirical studies and use simulation studies to compare some of the most frequently employed approaches to deal with data gaps, including subsampling, weighting and imputation. All these methods have the potential to reduce bias but may come at the cost of increased uncertainty of parameter estimates. Weighting techniques are arguably the least used so far in ecology and have the potential to reduce both the bias and variance of parameter estimates. Regardless of the method, the ability to reduce bias critically depends on knowledge of, and the availability of data on, the factors creating data gaps. We use this review to outline the necessary considerations when dealing with data gaps at different stages of the data collection and analysis workflow.

Heavy metal exposure reduces larval gut microbiota diversity of the rice striped stem borer, Chilo suppressalis.

Cadmium (Cd), a widely distributed environmental pollutant in agroecosystems, causes negative effects on crops and herbivores through bottom-up processes. The gut microbial community of an insect can play a critical role in response to metal stress. To understand how microbiota affect the stress responses of organisms to heavy metals in agroecosystems, we initially used 16S rRNA sequencing to characterize the larval gut microbiota of Chilo suppressalis, an important agricultural pest, exposed to a diet containing Cd. The species richness, diversity, and composition of the gut microbial community was then analyzed. Results revealed that while the richness (Chao1 and ACE) of gut microbiota in larvae exposed to Cd was not significantly affected, diversity (Shannon and Simpson) was reduced due to changes in species distribution and relative abundance. Overall, the most abundant genus was Enterococcus, while the abundance of the genera Micrococcaceae and Faecalibaculum in the control significantly superior to that in Cd-exposed pests. Phylogenetic investigation of microbial communities by the reconstruction of unobserved states (PICRUSt) showed that the intestinal microorganisms appear to participate in 34 pathways, especially those used in environmental information processing and the metabolism of the organism. This study suggests that the gut microbiota of C. suppressalis are significantly impacted by Cd exposure and highlights the importance of the gut microbiome in host stress responses and negative effects of Cd pollution in agroecosystems.

Genetic insights, assessment of ecological niche and projected distribution changes of the mountain mayfly species Andesiops peruvianus under climate change in the andes

Genetic insights, assessment of ecological niche and projected distribution changes of the mountain mayfly species Andesiops peruvianus under climate change in the andes

Long-term climatic stability drives accumulation and maintenance of divergent freshwater fish lineages in a temperate biodiversity hotspot

Anthropogenic climate change is forecast to drive regional climate disruption and instability across the globe. These impacts are likely to be exacerbated within biodiversity hotspots, both due to the greater potential for species loss but also to the possibility that endemic lineages might not have experienced significant climatic variation in the past, limiting their evolutionary potential to respond to rapid climate change. We assessed the role of climatic stability on the accumulation and persistence of lineages in an obligate freshwater fish group endemic to the southwest Western Australia (SWWA) biodiversity hotspot. Using 19,426 genomic (ddRAD-seq) markers and species distribution modelling, we explored the phylogeographic history of western (Nannoperca vittata) and little (Nannoperca pygmaea) pygmy perches, assessing population divergence and phylogenetic relationships, delimiting species and estimating changes in species distributions from the Pliocene to 2100. We identified two deep phylogroups comprising three divergent clusters, which showed no historical connectivity since the Pliocene. We conservatively suggest these represent three isolated species with additional intraspecific structure within one widespread species. All lineages showed long-term patterns of isolation and persistence owing to climatic stability but with significant range contractions likely under future climate change. Our results highlighted the role of climatic stability in allowing the persistence of isolated lineages in the SWWA. This biodiversity hotspot is under compounding threat from ongoing climate change and habitat modification, which may further threaten previously undetected cryptic diversity across the region.

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data.

Comprehensive biodiversity data is crucial for ecosystem protection. The Biome mobile app, launched in Japan, efficiently gathers species observations from the public using species identification algorithms and gamification elements. The app has amassed >6 million observations since 2019. Nonetheless, community-sourced data may exhibit spatial and taxonomic biases. Species distribution models (SDMs) estimate species distribution while accommodating such bias. Here, we investigated the quality of Biome data and its impact on SDM performance. Species identification accuracy exceeds 95% for birds, reptiles, mammals, and amphibians, but seed plants, molluscs, and fishes scored below 90%. Our SDMs for 132 terrestrial plants and animals across Japan revealed that incorporating Biome data into traditional survey data improved accuracy. For endangered species, traditional survey data required >2000 records for accurate models (Boyce index ≥ 0.9), while blending the two data sources reduced this to around 300. The uniform coverage of urban-natural gradients by Biome data, compared to traditional data biased towards natural areas, may explain this improvement. Combining multiple data sources better estimates species distributions, aiding in protected area designation and ecosystem service assessment. Establishing a platform for accumulating community-sourced distribution data will contribute to conserving and monitoring natural ecosystems.

Spatio‐temporal data integration for species distribution modelling in R‐INLA

Abstract Species distribution modelling is a highly used tool for understanding and predicting biodiversity change, and recent work has emphasised the importance of understanding how species distributions change over both time and space. Spatio‐temporal models require large amounts of data spread over time and space, and as such are clear candidates to benefit from model‐based integration of different data sources. However, spatio‐temporal models are highly computationally intensive and integrating different data sources can make this approach even more unfeasible to ecologists. Here we demonstrate how the R‐INLA methodology can be used for model‐based data integration for spatio‐temporally explicit modelling of species distribution change. We demonstrate that this method can be applied to both point and areal data with two contrasting case studies, one using the SPDE approach for modelling spatio‐temporal change in the Gatekeeper butterfly (Pyronia tithonus) across Great Britain and the second using a spatio‐temporal areal model to describe change in caddisfly (Trichoptera) populations across the River Thames catchment. We show that in the caddisfly case study integrating together different data sources led to greater understanding of the change in abundance across the River Thames both seasonally and over 5 years of data. However, in the butterfly case study moving to a spatio‐temporal context exacerbated differences between the data sources and resulted in no greater ecological insight into change in the Gatekeeper population. Our work provides a computationally feasible framework for spatio‐temporally explicit integration of data within SDMs and demonstrates both the potential benefits and the challenges in applying this methodology to real ecological data.

Predicting the changing insect threat in the UK heritage environment

Environmental changes affecting museums and historic properties will probably result in increased numbers of insect pests or new species. Databases such as WhatsEatingYourCollection (WEYC) and the Global Biodiversity Information Facility have been used along with academic publications to predict such changes in the research presented here. The species mix in the WEYC database seems consistent across major London historic properties. Overall, common silverfish (Lepisma saccharinum) are often reported, although in future there may be an increase in other species such as Ctenolepisma longicaudatum and Ctenolepisma calvum given their increased frequency. Dermestidae (carpet and furniture beetles) may benefit from wood with increasing moisture content, and although not especially abundant, Attagenus smirnovi (brown carpet beetle) and Reesa vespulae (skin beetle) may increase as they have done on the European continent. Tineola bisselliella, a damaging moth, has invoked increasing concern over the last two decades and Cryptophagus spp. (fungus beetles) could mobilise fungal spores under a future climate more favourable to germination. Lyctus brunneus (powderpost beetle) may find future conditions favourable and attack sapwoods used in repairs. Furthermore, Reticulitermes flavipes (subterranean termite) is potentially an accidental import to the UK and may become more common given current temperatures are suitable for survival in well-drained loamy soils, and future climates would allow a presence in the north of England. Warmer conditions can lead to the presence of new species or a migration of species across the British Isles and their spread can also be encouraged through the loan of objects or on packing materials. Factors other than climate, such as changing indoor habitats, new food sources and novel uses of heritage venues can also encourage expanding insect populations. This article summarises these predicted changes in species distribution and outlines their potential threat to heritage.

Impact of artificial barriers on benthic macroinvertebrate functional diversity in estuarine ecosystems

AbstractFunctional diversity research enhances our understanding of ecosystems and both their functioning and their responses to environmental variations. This study investigated the biological trait responses of benthic invertebrate communities to various environmental conditions in estuarine habitats. We analyzed benthic macroinvertebrate communities in freshwater and estuarine environments to compare their characteristics between estuary sites with and without artificial barriers. Moreover, we combined taxonomic analyses (species richness, abundance, and four community indices) with functional diversity indices and biological trait analyses. The major results are as follows: (i) the most important environmental factors shaping species distribution in estuarine habitats were salinity and electrical conductivity; (ii) comparing functional diversity indices, tidal estuaries revealed that seawater intrusion induced changes in species distribution and the dispersion of benthic macroinvertebrates; (iii) the presence or absence of artificial barriers in estuaries affected biological traits owing to the influence of specific functional strategies of certain species. Consequently, the presence or absence of artificial barriers in estuaries can lead to significant changes in habitat connectivity and functional diversity related to ecosystem functions. These findings indicate that the presence of artificial barriers can significantly influence the ecological dynamics of estuarine ecosystems, thereby affecting species distribution, functional diversity and habitat connectivity. Understanding these effects contributes to a more comprehensive understanding of ecosystem functionings, as it complements existing taxonomic findings and integrates information about the functional aspects of diverse ecosystems.

Geospatial Inventory of the Galakand Forestry Area Utilizing GIS Database and Remote Sensing Techniques

This study investigated the dramatic reduction of forested areas in Azerbaijan, exceeding 50% over the past two centuries, largely due to increased wood production. Focusing on the period between 1880 and 1990, it analyzed the impact of timber harvesting on the composition of dominant tree species, with a special focus on beech trees, in the Galakand forestry area. Utilizing GIS databases and remote sensing techniques, the research assessed the changes in forest cover and species distribution, highlighting the critical transition from lush beech and oak forests to areas dominated by hornbeam, east hornbeam, oak-hornbeam, and juniperus-bush light forests. The study demonstrated the negative consequences of historical overexploitation, advocating for forest farming practices that promote the recovery and preservation of native forest ecosystems. Key findings revealed a marked decline in valuable wood species due to intensive logging activities, particularly between 1880 and 1914, and the detrimental effects of forest renewal cabins established from 1930 to 1970. The outlined measures in the study highlighted that the forest primarily comprises wooded areas (reserves with a completeness of 0.1-0.2, clearings, and clearings), non-forest lands repurposed as pastures and forested pastures with a density ranging from 0.3 to 0.4. Overall, the findings underscore the importance of sustainable forest management practices to reverse the adverse effects of historical overexploitation and preserve the biodiversity of Azerbaijan's ecosystems. The paper emphasized the necessity of sustainable forest management to reverse the damage and protect Azerbaijan's biodiversity to enhance measures for sustainable forestry, along with the critical role of advanced GIS and remote sensing in monitoring and conserving forest resources.

Making better use of tracking data can reveal the spatiotemporal and intraspecific variability of species distributions

Understanding geographic ranges and species distributions is crucial for effective conservation, especially in the light of climate and land use change. However, the spatial, temporal and intraspecific resolution of digital accessible information on species distributions is often limited. Here, we suggest to make better use of high‐resolution tracking data to address existing limitations of occurrence records such as spatial biases (e.g. lack of observations in parts of the geographic range), temporal biases (e.g. lack of observations during a certain period of the year), and insufficient information on intraspecific variability (e.g. lack of population‐ or individual‐level variation). Addressing these gaps can improve our knowledge on geographic ranges, intra‐annual changes in species distributions, and population‐level differences in habitat and space use. We demonstrate this with tracking data and species distribution models (SDMs) of the barnacle goose, a migratory bird species wintering in western Europe and breeding in the Arctic. Our analyses show that tracking data can 1) supplement occurrence records from the Global Biodiversity Information Facility (GBIF) in remote areas such as the European and Russian Arctic, 2) improve information on the temporal use of wintering, staging and breeding areas of migratory species and 3) be used to reveal distribution patterns at the population level. We recommend a broader use of tracking data to address the Wallacean shortfall (i.e. the incomplete knowledge on the geographic distribution of species) and to improve forecasts of biodiversity responses to climate and land use change (e.g. species vulnerability assessments). To avoid common pitfalls, we provide six recommendations for consideration during the research cycle when using tracking data in species distribution modelling, including steps to assess biases and integrate information on intraspecific variability in modelling approaches.

Temperature induced changes in species distribution increases sensitivity of aquatic invertebrate communities to chemicals.

In this commentary, I will discuss how climate warming might influence the impacts of chemicals on (aquatic) ecosystems. It provides a commentary on Sinclair etal. (2024).

Decadal changes in biomass and distribution of key fisheries species on Newfoundland's Grand Banks.

Canadian fisheries management has embraced the precautionary approach and the incorporation of ecosystem information into decision-making processes. Accurate estimation of fish stock biomass is crucial for ensuring sustainable exploitation of marine resources. Spatio-temporal models can provide improved indices of biomass as they capture spatial and temporal correlations in data and can account for environmental factors influencing biomass distributions. In this study, we developed a spatio-temporal generalized additive model (st-GAM) to investigate the relationships between bottom temperature, depth, and the biomass of three key fished species on The Grand Banks: snow crab (Chionoecetes opilio), yellowtail flounder (Limanda ferruginea), and Atlantic cod (Gadus morhua). Our findings revealed changes in the centre of gravity of Atlantic cod that could be related to a northern shift of the species within the Grand Banks or to a faster recovery of the 2J3KL stock. Atlantic cod also displayed hyperaggregation behaviour with the species showing a continuous distribution over the Grand Banks when biomass is high. These findings suggest a joint stock assessment between the 2J3KL and 3NO stocks would be advisable. However, barriers may need to be addressed to achieve collaboration between the two distinct regulatory bodies (i.e., DFO and NAFO) in charge of managing the stocks. Snow crab and yellowtail flounder centres of gravity have remained relatively constant over time. We also estimated novel indices of biomass, informed by environmental factors. Our study represents a step towards ecosystem-based fisheries management for the highly dynamic Grand Banks.

Decadal vegetation changes in a subarctic‐alpine ecosystem: Can effects of Iceland's largest hydropower reservoir, climate change, and herbivory be detected?

AbstractAimsWhile plot‐based vegetation surveys provide means to precisely track changes in plant species abundance and distribution, ecosystems are continuously influenced by numerous drivers, confounding interpretation of monitoring results. Following the making of Iceland's largest hydropower reservoir in 2006, a decadal vegetation monitoring was set up. Relating our results to those of different types of environmental monitoring associated with the hydropower project, we aimed to gain insights into the forces driving the spatio‐temporal vegetation pattern.LocationSubarctic‐alpine area near Hálslón reservoir, East Iceland.MethodsAt the time of its making, we conducted a baseline plant survey in a total of 72 plots, spread around Hálslón reservoir's vicinity (each containing ten 0.25 m2 subplots). Plots were located in three different habitat types (heathlands, wetlands, poorly vegetated land), at three different sites regarding direction and distance from the reservoir. A decade later, we resurveyed the plots and reviewed the results of other environmental monitoring projects in the area, mostly presented in the gray literature.ResultsTemporal changes in vegetation were mostly inconsistent between and within habitat types, but some general trends were noticed, that is, decreased lichen and fern cover in heathlands. Distance from the reservoir did not significantly affect changes in vegetation cover. The greatest overall changes were detected where great changes in herbivore land usage had been recorded during the study.ConclusionsDirect effects of Hálslón reservoir on vegetation in our study plots were not noticed. Most likely, the reservoir indirectly impacted vegetation in our study through loss of grazing area, affecting herbivore land usage, coupled with an unrelated population growth of two of the area's main wild herbivores before and during the study period. Response to climate change was not detected, potentially concealed by substantial land‐use change and a short study period.

Changes in fish species diversity, size structure and distribution in the trawlable demersal zones of Lake Malawi, Malawi

Changes in fish species diversity, size structure and distribution in the trawlable demersal zones of Lake Malawi, Malawi

Changing Epidemiology of Clinical Isolates of Candida Species during the Coronavirus Disease 2019 Pandemic: Data Analysis from a Korean Tertiary Care Hospital for 6 Years (2017-2022).

This study assessed the changes in Candida species distribution and antifungal susceptibility patterns during the coronavirus disease 2019 (COVID-19) pandemic compared with a pre-pandemic period in Korea. We retrospectively investigated the specimen, species type, and antifungal susceptibility of Candida isolates obtained between 2016 and 2022. Data between two periods were compared: 2016-2019 (pre-pandemic) and 2020-2022 (pandemic). We included 11,396 clinical isolates of Candida species (5137 isolates in the pre-pandemic and 6259 isolates in the pandemic). The most prevalent species was Candida albicans (50.4%), followed by Candida glabrata (22.7%), Candida tropicalis (12.5%), and Candida parapsilosis complex (12.5%). Their ranks were unchanged; however, their relative isolation ratios varied during the pandemic, exhibiting differences ranging from 0.4 to 2.5 across species. The incidence of candidemia increased during the pandemic (average 1.79 episodes per 10,000 patient days) compared with pre-pandemic levels (average 1.45 episodes per 10,000 patient days) in both intensive-care-unit (ICU) and non-ICU patients. Additionally, C. parapsilosis complex candidemia increased by 1.6-fold during the pandemic. During the pandemic, C. albicans and C. tropicalis candidemia significantly increased by 1.5- and 1.4-fold in ICU patients. In contrast, C. parapsilosis complex candidemia surged 2.1-fold in non-ICU patients. These species exhibited reduced resistance to fluconazole, voriconazole, caspofungin, and micafungin in the pandemic compared with the pre-pandemic. This study underscores the heightened incidence of Candida-related infections during the COVID-19 pandemic and emphasizes the importance of ongoing surveillance of Candida species epidemiology beyond the pandemic's scope.

Vertical eDNA distribution of cold-water fishes in response to environmental variables in stratified lake.

In summer, the survival zones of cold-water species are predicted to narrow by both increasing water temperatures from the surface and by expanding hypoxic zones from the lake bottom. To examine how the abundance of cold-water fishes changes along environmental gradients, we assessed the vertical environmental DNA (eDNA) distributions of three salmonid species which may have different water temperature tolerances during both stratification and turnover periods using quantitative PCR (qPCR). In addition, we examined on the vertical distribution of diverse fish fauna using an eDNA metabarcoding assay. The results suggested that the kokanee salmon (Oncorhynchus nerka) eDNA were abundant in deep, cold waters. On the other hand, rainbow trout (O. mykiss) eDNA were distributed uniformly throughout the water column, suggesting that they may have high water-temperature tolerance compared with kokanee salmon. The eDNA concentrations of masu salmon (O. masou) were below the detection limit (i.e., <10 copies μL-1) at all stations and depths and hence could not be quantified during stratification. Together with the finding that the eDNA distributions of other prey fish species were also constrained vertically in species-specific ways, our results suggest that climate change will result in substantial changes in the vertical distributions of lake fish species and thus affect their populations and interactions.

Synthesis reveals approximately balanced biotic differentiation and homogenization.

It is commonly thought that the biodiversity crisis includes widespread declines in the spatial variation of species composition, called biotic homogenization. Using a typology relating homogenization and differentiation to local and regional diversity changes, we synthesize patterns across 461 metacommunities surveyed for 10 to 91 years, and 64 species checklists (13 to 500+ years). Across all datasets, we found that no change was the most common outcome, but with many instances of homogenization and differentiation. A weak homogenizing trend of a 0.3% increase in species shared among communities/year on average was driven by increased numbers of widespread (high occupancy) species and strongly associated with checklist data that have longer durations and large spatial scales. At smaller spatial and temporal scales, we show that homogenization and differentiation can be driven by changes in the number and spatial distributions of both rare and common species. The multiscale perspective introduced here can help identify scale-dependent drivers underpinning biotic differentiation and homogenization.

Climate change impact on small mammals from two Neotropical hotspots

Abstract Current climate change represents the unprecedented change in weather patterns across global and regional scales over a short period due to human activity. It is expected to drive changes in species distributions across the globe. Our goal here was to analyse (i) how climate change can impact the future distribution of species in two Neotropical hotspots, and (ii) how future distribution can impact the threatened status of species. We used ecological niche modelling to estimate suitable areas in the present and four future climate change scenarios (SSPs) for 40 species of nonvolant small mammals endemic to the Atlantic Forest and Cerrado biomes of South America. We also inferred species’ future threat levels according to the IUCN’s A3 criteria using future relative area estimates. We found that species will gradually lose more area in all future scenarios, from the most optimistic Shared Socio-economic Pathway (SSP1-2.6) to the most pessimistic (SSP5-8.5) scenario. Species endemic to the Cerrado will see a greater area reduction than species endemic to the Atlantic Forest. Consequently, the Cerrado will have more threatened species than the Atlantic Forest. Species that occupy both biomes will lose proportionally less area than those endemic to the Cerrado but more area than those endemic to the Atlantic Forest. In conclusion, small mammal species will, in general, be negatively impacted by climate change. However, the degree of impact depends on the trajectory of greenhouse gas concentrations and where the species live.