Future Species Distributions Research Articles

Distribution of important medicinal plant species in Nepal under past, present, and future climatic conditions

Climate change is causing shifts in the habitat, distribution, ecology, and phenology of Himalayan plants. These changes are predicted to continue, jeopardizing the survival of medicinal plant species and local livelihoods that rely on them. We analyzed the present and future diversity and distribution of medicinal plant species influenced by different climate change scenarios, and calculated the climatic niche of the species using ensemble species distribution modeling (eSDM). We compiled 1041 (N) geospatial data of seven high-value medicinal plant species of Nepal: Aconitum spicatum (n = 100), Allium wallichii (n = 151), Bergenia ciliata (n = 48), Nardostachys jatamansi (n = 121), Neopicrorhiza scrophulariiflora (n = 94), Paris polyphylla (n = 310) and Valeriana jatamansi (n = 217) including over 85 % from field surveys and the rest from literature and online database. We used bioclimatic variables from Models for Interdisciplinary Research on Climate (MIROC) of version MIROC6, and selected Shared Socioeconomic Pathways (SSP)2-4.5 and SSP5-8.5 for the year of 2050 and 2070 for modeling. We found elevation, mean diurnal and annual temperature ranges (BIO2 and BIO7), and precipitation of warmest and coldest quarters (BIO18 and BIO19) to be the most high weight cofactors for projecting the future potential distribution of high-value medicinal plants in Nepal. Results showed that the suitable range of distribution for high-value medicinal plants would increase and concentrate in mountainous areas of central Nepal, but decline in (sub)tropical and temperate areas, suggesting both in-situ and ex-situ conservation practices, respectively.

The effect of climate and land cover changes on the distribution of Actinodaphne areolata Blume, an endemic and endangered species in Java, Indonesia

Actinodaphne areolata Blume is an endemic plant in Indonesia. The minimal distribution makes this species threatened and even listed as endangered species by IUCN. Therefore, analyses of climate change and land cover change were conducted to predict the future species distribution and to determine conservation action for this species. The plant occurrences from GBIF online database and Naturalis herbarium data were collected and validated. The environmental variables used in the model were topography, vegetation, soil, and climate. All environmental variables were selected with the multicollinearity test. Prediction of future land cover using cellular automata and the future species distribution for 2050 (2041-2060) and 2070 (2061-2080) under the Representative Concentration Pathways 4.5 and 8.5 scenarios were simulated using maximum entropy (maxent). The resulting habitat suitability prediction model has an AUC value of more than 0.92, indicating an adequate model for predicting habitat suitability for A.areolate. Environmental variables that affect the presence of A. areolata are temperature seasonality (bio4) and land cover. Land cover and climate change were estimated to impact plant distribution in the future negatively. The suitable habitat for A. areolata will gradually decrease throughout the year, so it is necessary to designate priority areas for conserving this species.

Geographic name resolution service: A tool for the standardization and indexing of world political division names, with applications to species distribution modeling.

Massive biological databases of species occurrences, or georeferenced locations where a species has been observed, are essential inputs for modeling present and future species distributions. Location accuracy is often assessed by determining whether the observation geocoordinates fall within the boundaries of the declared political divisions. This otherwise simple validation is complicated by the difficulty of matching political division names to the correct geospatial object. Spelling errors, abbreviations, alternative codes, and synonyms in multiple languages present daunting name disambiguation challenges. The inability to resolve political division names reduces usable data, and analysis of erroneous observations can lead to flawed results. Here, we present the Geographic Name Resolution Service (GNRS), an application for correcting, standardizing, and indexing world political division names. The GNRS resolves political division names against a reference database that combines names and codes from GeoNames with geospatial object identifiers from the Global Administrative Areas Database (GADM). In a trial resolution of political division names extracted from >270 million species occurrences, only 1.9%, representing just 6% of occurrences, matched exactly to GADM political divisions in their original form. The GNRS was able to resolve, completely or in part, 92% of the remaining 378,568 political division names, or 86% of the full biodiversity occurrence dataset. In assessing geocoordinate accuracy for >239 million species occurrences, resolution of political divisions by the GNRS enabled the detection of an order of magnitude more errors and an order of magnitude more error-free occurrences. By providing a novel solution to a significant data quality impediment, the GNRS liberates a tremendous amount of biodiversity data for quantitative biodiversity research. The GNRS runs as a web service and is accessible via an API, an R package, and a web-based graphical user interface. Its modular architecture is easily integrated into existing data validation workflows.

Mapping the impacts of multiple stressors on the decline in kelps along the coast of Victoria, Australia

AbstractAimKelp forests throughout temperate regions of the world serve as foundation species that play a critical role in sustaining the health and function of marine ecosystems but are experiencing declines in abundance due to a loss in resilience as the ocean climate changes. Ocean warming along southeast Australia has already been linked to dramatic losses of kelp species and is contributing to the range expansion and population increases of two species of sea urchin. This research attempts to understand the impact of multiple stressors on the decline in kelps in this region.LocationCoastal Waters of Victoria, Southeast Australia.MethodsIn this study, we use long‐term (>20 years) datasets on biological observations across Victorian waters to determine trends in coverage and the impact of multiple environmental variables (oceanography, habitat, and urchin abundances) on two important kelps that serve as foundation species (Phyllospora comosaandEcklonia radiata)using boosted regression trees. These models were then used to develop predictive distribution models for each species and also to project abundance distributions into the future.ResultsWe found that both kelp species are decreasing in percent coverage over time with multiple environmental variables contributing to these declines, including increasing temperatures, intensifying wave energy, changes in currents and recruitment patterns, and increases in urchin populations. Additionally, future projections of temperature, wave energy, and urchin populations show that both species will continue to decrease across 62%–94% of their range by 2090.Main conclusionsLong‐term biological datasets allowed us to develop maps of the past, current, and future distributions of these important foundation species, providing valuable information to managers for prioritization of areas for targeted urchin management and restoration of kelps. Understanding the environmental factors affecting their distribution helps guide manager restoration investments in regions where kelp populations are most likely to persist in the future.

Modelling the distribution of marine fishery resources: Where are we?

AbstractEcological niche models (ENMs) and species distribution models (SDMs) have been widely applied to various studies relevant to biogeography, conservation biology, and ecology. These modelling techniques seek to develop spatial maps for projecting, among others past, current, and future species distributions. Born in the field of terrestrial ecology, only in recent years have these models been applied to marine environmental issues, especially to improve the forecasting of the distribution of occurrences and capturing of fishery resources. This study aimed to present through bibliometric analysis the characteristics of articles related to the use of ENMs and SDMs in marine fishery resources considering three main points: (1) state of the art: number of articles over the years, journals, countries, collaborations, and focus of research; (2) characteristics linked to fishery resources: marine biogeographic realms, taxonomic groups, life phases, oceanographic zones, and behaviours; (3) characteristics linked to methods: type of method, type of biological and, environmental data. We provide a list of 378 articles (derived from 930 screened ones), the results, and a discussion of our findings, which represent a baseline for the current status (strengths, limits, and gaps) of the interface between ENMs/SDMs and fishery resources.

Large variability in response to future climate and land-use changes among Chinese Theaceae species.

Theaceae is an important family in the phylogeny of angiosperm in China, which are potentially threatened by future changes in climatic and land use conditions. Therefore, understanding and predicting the isolated and combined effects of these two global change factors on Theaceae species is crucial for biodiversity conservation. Here, we assessed the isolated and combined effects of climate and land use change on the distribution shifts of 95 Theaceae species under different future scenarios by comparing projections of three model configurations: (1) dynamics climate and constant land use variables; (2) constant climate and dynamics land use variables; and (3) dynamics climate and dynamics land use variables. We find that all the three types of models predicted range contractions for most of the 95 Theaceae species under all future scenarios. Moreover, we find that climate change has rather strong effect for most species while land use change has nonsignificant or weak effect on future species distributions, although both of these two isolated effects are highly variable across individual species. Finally, the combined effect of these two factors reveals that the land use change may amplify or buffer distribution shifts expected from climate change impact depending on species. These findings emphasize the importance of taking into account the large variability in response to land use change among Theaceae species when developing land-based conservation strategies in a changing climate.

Impact of climate change on Southeast Asian natural habitats, with focus on protected areas

Natural habitats have been destroyed by anthropogenic factors for several decades, exacerbated by climate change. This study investigated the impact of climate change on natural habitats by using 55 Phasianidae species. We predicted current and future species distribution based on three climate change scenarios. We then (1) determined the effect of climate change on each species by comparing the distribution and elevation range shift between current and future predictions. In addition, we (2) estimated the total large habitat patches (> 40 km 2 ) for each species, and determine how it change in the future. We also (3) investigated large habitat patches change within PAs. Moreover, we (4) evaluated the Phasianidae diversity hotspots in the current and future predictions. The results showed climate change is likely to reduce the suitable natural habitats in Southeast Asia, with an average reduction of habitat patches was 180,970 km 2 (11%) when comparing the future predictions with the current state. Most of the species appeared to be retreating to higher altitudes and face suitable habitat reduction by 2100. The large habitat patch average declined 183,474 km 2 (12%), with 2–10 species in imminent danger of losing their habitat (depending on the climate change modeling scenarios). The current large patches in the protected areas represented a small proportion of the total large patch distribution, and there were fewer future large patches than currently available. The species risk a reduction in diversity, especially in the Indo-Burma region where most of them are facing a massive loss of their suitable habitats. We suggest the use of Phasianidae as indicator species to monitor natural forests in Southeast Asia and the implementation of adaptive conservation management to prevent further losses in the future.

Plant species biogeographic origin shapes their current and future distribution on the world's highest island mountain

Abstract In New Guinea, low elevations are thought to be dominated by plant species with biogeographic origins in Sunda (Borneo, Sumatra, Java, Mainland Asia) and high elevations by species from Sahul (Australia and New Guinea). In regions where frequent surveys of the flora are unfeasible, herbarium specimens collected over time offer an opportunity to study the co‐occurrence of species. Over 7000 collections have been made on New Guinea's Mount Jaya allowing us to examine species presence under current and future temperatures. Applying a Bayesian phylogenetic mixed effects model to the Mount Jaya elevation gradient, we show that species of Sunda origin are more likely to occupy warmer lowlands and Sahul species cooler higher elevations. Using the model to predict species distributions under a 2°C increase, we find that Sahul species are less likely to tolerate future temperatures, especially below 1000 m. Predictions also show a potential increase in species richness across the gradient. It is unclear if these increases are possible due to limits imposed by the species area relationship. Synthesis. These results emphasise how biogeographic origin influences current and future species distributions on tropical mountains. It remains to be seen how our results link to traits that dictate species' ability to tolerate increasing temperatures.

Predicting the Distribution of Three Korean Pit Viper Species (<i>Gloydius brevicaudus</i>, <i>G. ussuriensis</i>, and <i>G. intermedius</i>) under Climate Change

Climate change can pose severe threats to wildlife populations causing population declines and destroying their habitats. Particularly, pit vipers belonging to reptiles, poikilotherm, are vulnerable to climate change due to their narrow movement range and low dispersal capability. This study aimed to identify pit viper species vulnerable to climate change using their predicted geographical habitat range based on the current and future Korean pit viper species distribution model. The results of this study showed that three major environmental factors related to altitude and temperature (BIO4 and BIO5) influenced the habitat distribution of three pit viper species. These factors showed significant variation between increased, maintained, and decreased habitat areas of the species due to climate change. It was also predicted that the habitat of Korean pit vipers would decrease by more than 80% under the RCP 8.5 scenario. Especially, Central Asian pit viper was predicted to lose 98.52% of its habitat, indicating that it would be the most vulnerable species to climate change. Although we confirmed that forest areas around the Taebaek Mountains, known as current major distribution areas of pit vipers, would provide maintained or even increased habitat areas to these species along climate change, habitable space for the vipers was still predicted to be very narrow. Therefore, it is critical to protect the forest areas around the Taebaek Mountains to minimize the impact of climate change on Korean pit vipers. Moreover, since some populations of Central Asian pit viper, most vulnerable to climate change, are geographically isolated, it will be necessary to establish systematic conservation measures by determining the protection priority of populations through studying genetic diversity between populations. We believe that the results of this study will provide an important basis for establishing management measures in designating the habitat of a threatened population due to climate change as a protected area.

Projecting species distributions using fishery‐dependent data

AbstractMany marine species are shifting their distributions in response to changing ocean conditions, posing significant challenges and risks for fisheries management. Species distribution models (SDMs) are used to project future species distributions in the face of a changing climate. Information to fit SDMs generally comes from two main sources: fishery‐independent (scientific surveys) and fishery‐dependent (commercial catch) data. A concern with fishery‐dependent data is that fishing locations are not independent of the underlying species abundance, potentially biasing predictions of species distributions. However, resources for fishery‐independent surveys are increasingly limited; therefore, it is critical we understand the strengths and limitations of SDMs developed from fishery‐dependent data. We used a simulation approach to evaluate the potential for fishery‐dependent data to inform SDMs and abundance estimates and quantify the bias resulting from different fishery‐dependent sampling scenarios in the California Current System (CCS). We then evaluated the ability of the SDMs to project changes in the spatial distribution of species over time and compare the time scale over which model performance degrades between the different sampling scenarios and as a function of climate bias and novelty. Our results show that data generated from fishery‐dependent sampling can still result in SDMs with high predictive skill several decades into the future, given specific forms of preferential sampling which result in low climate bias and novelty. Therefore, fishery‐dependent data may be able to supplement information from surveys that are reduced or eliminated for budgetary reasons to project species distributions into the future.

Realizing certainty in an uncertain future climate: modeling suitable areas for conserving wild Citrus species under different change scenarios in India.

Citrus is an important horticultural crop of India and is often prone to diseases, particularly under increased temperature scenarios. For developing disease-resistant Citrus varieties, conservation of wild relatives is extremely important. However, our knowledge on temperature tolerance of these wild relatives of Citrus to varied climate change scenarios is extremely limited. Therefore, we determined the climatic niche of six wild relatives of cultivated Citrus species (C. indica Tanaka, C. karna Rafin., C. latipes (Swingle) Tanaka, C. macroptera Montrouz., C. medica L., and C. sinensis (L.) Osbeck.) and identified the geographical areas in India that would remain climatically stable in future through ecological niche modeling (ENM). Raster data on 19 bioclimatic variables with a resolution of 0.04° were used to generate niche models for each Citrus species that delineated their potential distribution areas. Future species distribution predictions for the year 2050 were made using the climate change scenarios from the most appropriate climate models, i.e., IPSL-CM5A-LR and NIMR-HADGEM2-AO with four Representative Concentration Pathways (RCPs). Ensemble of current and future projections was used to identify climatically stable areas for each species. Precipitation-related bioclimatic variables were the key climatic determinants for the modeled distribution pattern. The consensus of current and future projections suggests that most areas with stable climates for the species in the future would be available in the northeastern states of Arunachal Pradesh, Meghalaya, Mizoram, and Tripura. Efforts for in situ conservation and establishment of germplasm banks and citrus orchards may be encouraged in these identified areas.

Can pikas hold the umbrella? Understanding the current and future umbrella potential of keystone species Pika (Ochotona spp.)

The umbrella species concept is a frequently used concept in conservation since the conservation of an umbrella species may benefit other species. Keystone species are often suggested as potential umbrella species, but the validity of this approach remains uncertain. Moreover, climate change can have a multidirectional effect on the distribution of species, in which the distribution of umbrella species can be affected differently than that of beneficiary species. The validity of applying the umbrella species concept in conservation may thus be jeopardised by climate change. This study assessed the potential of two keystone species, the plateau pika ( Ochotona curzoniae ) and the Daurian pika ( Ochotona dauurica ), to be umbrella species for 13 potentially beneficiary species under current and future environmental conditions. Of these 13 species, five currently only co-occur with the plateau pika, five only with the Daurian pika, and three with both pika species. Current and future distributions of the pika species and potentially beneficiary species were predicted using bioclimatic and land-use variables. Range overlaps, Pearson correlations, niche similarity tests and relative suitability tests were performed to assess the umbrella potential of both pika species. Our results show that at present, both pika species may be considered to be umbrella species, benefitting several co-occurring species. However, species that currently co-occur with both pika species will not benefit from conservation of either of the pikas in the future years under climate change scenarios. The plateau pika loses its potential to act as umbrella species for two of the four species which currently may benefit. We can conclude that keystone species like pikas can act as umbrella species for carefully selected potentially beneficiary species under current conditions. Due to climate change related shifts in species distributions, they may however lose their umbrella species status in the future, which should be considered when selecting species conservation strategies. • The umbrella potential of two keystone species was explored under multiple scenarios of climate change. • Predicted umbrella potential of one keystone species was stronger than the other. • Umbrella potential is not necessarily maintained under future scenarios of climate change • Choice of beneficiary species highly influences the umbrella potential of keystone species. • Integration of predicted distribution range shifts in action plans is essential.

Predicting current and future species distribution of the raccoon dog (Nyctereutes procyonoides) in Shanghai, China

Rapid urbanization has caused drastic changes in urban ecosystems, resulting in various urgent management needs from mitigating biodiversity loss to preventing human-wildlife conflicts. Using species distribution modeling to understand urban species’ distributional patterns and predict their future changes is thus important to support decision-making. Raccoon dog (Nyctereutes procyonoides) that previously inhabited Shanghai had been extirpated from the metropolitan area but recently returned to and expanded in almost all districts, causing hundreds of human-raccoon dog conflicts. In this study, we initiated a citizen science project, identified factors associated with raccoon dog habitat selection, and predicted its current suitable habitat as well as potential future ranges under different city development scenarios. By constructing an ensemble modeling using data from camera trap surveys, interviews and rescuing records, we found that raccoon dog distribution was positively associated with several anthropogenic factors including nighttime light, human population, and percentage area of buildings. We predicted a 156,024 ha suitable habitat for raccoon dogs throughout Shanghai, among which only 5,811 ha (3.72 %) was currently occupied. Our results indicated considerable potential of raccoon dogs’ future expansion, which had been consistently ignored in previous management plans. To alleviate the increasing human-raccoon dog conflicts, we found strategies to slow down raccoon dog movement effective tools, and suggest adaptive management to provide fast response and flexible solutions. This is the first study to investigate human-wildlife conflict in China’s urban environment, and our approach has substantial implications for Shanghai as well as other regions where urban species are undergoing rapid expansion.

Predicting range shifts of the giant pandas under future climate and land use scenarios.

Understanding and predicting how species will respond to global environmental change (i.e., climate and land use change) is essential to efficiently inform conservation and management strategies for authorities and managers. Here, we assessed the combined effect of future climate and land use change on the potential range shifts of the giant pandas (Ailuropoda melanoleuca) in Sichuan Province, China. We used species distribution models (SDMs) to forecast range shifts of the giant pandas by the 2050s and 2070s under four combined climate and land use change scenarios. We also compared the differences in distributional changes of giant pandas among the five mountains in the study area. Our SDMs exhibited good model performance and were not overfitted, with a mean Boyce index of 0.960 ± 0.015 and a mean omission rate of 0.002 ± 0.003, and suggested that precipitation seasonality, annual mean temperature, the proportion of forest cover, and total annual precipitation are the most important factors in shaping the current distribution pattern of the giant pandas. Our projections of future species distribution also suggested a range expansion under an optimistic greenhouse gas emission, while suggesting a range contraction under a pessimistic greenhouse gas emission. Moreover, we found that there is considerable variation in the projected range change patterns among the five mountains in the study area. Especially, the suitable habitat of the giant panda is predicted to increase under all scenarios in the Minshan mountains, while is predicted to decrease under all scenarios in Daxiangling and Liangshan mountains, indicating the vulnerability of the giant pandas at low latitudes. Our findings highlight the importance of an integrated approach that combines climate and land use change to predict the future species distribution and the need for a spatial explicit consideration of the projected range change patterns of target species for guiding conservation and management strategies.

Predicted impacts of climate change and extreme temperature events on the future distribution of fruit bat species in Australia

Fruit bats are important pollinators and seed dispersers whose distribution may be affected by climate change and extreme-temperature events. We assessed the potential impacts of those changes and events on the future distribution of fruit bats in Australia. Correlative species distribution modelling was used to predict the distribution of seven (based on data availability) tropical and temperate fruit bat species. We used bioclimatic variables, the number of days where temperature ≥42 °C (known to induce extreme heat stress and mortality in fruit bats), and land cover (a proxy for habitat) as predictors. An ensemble of machine-learning algorithms was used to make predictions for the current-day distribution and future (2050 and 2070) scenarios, using multiple emission scenarios (RCP 4.5 and 8.5) and global circulation models (Australian Community Climate and Earth System Simulator, Hadley Centre Global Environment Model Carbon Cycle, and the Model for Interdisciplinary Research on Climate). Our results predict, under current conditions, on average, 9.1 % and 90.8 % of the area are suitable and unsuitable, respectively. Under future scenarios, on average, 6.7 % and 89.7 % continued to be suitable and unsuitable, respectively, while there was a 1.1 % gain and 2.4 % loss in suitable areas. Under current conditions, we predict, on average, 5.6 % and 3.4 % are suitable inside and outside species’ IUCN-defined range, respectively. While under future scenarios, 4.8 % (4.4 % stable and 0.4 % gain) and 2.9 % (2.2 % stable and 0.6 % gain) are suitable inside and outside the range respectively. On average, the gain in areas inside the range covers 2703.5 grid cells of size 5 km, while outside the range it is 4070.3 cells. Under future scenarios, the loss in areas is predicted to be 1.2 % and 1.1 % on average, inside and outside species range respectively. Fruit bats are likely to respond to climate change and extreme temperatures by migrating to more suitable areas, including regions not historically inhabited by those species. Our results can be used for identifying areas at risk of new fruit-bat colonisation, such as human settlements and orchards, as well as areas that might be important for habitat conservation.

Hindcast-validated species distribution models reveal future vulnerabilities of mangroves and salt marsh species.

Rapid climate change is threatening biodiversity via habitat loss, range shifts, increases in invasive species, novel species interactions, and other unforeseen changes. Coastal and estuarine species are especially vulnerable to the impacts of climate change due to sea level rise and may be severely impacted in the next several decades. Species distribution modeling can project the potential future distributions of species under scenarios of climate change using bioclimatic data and georeferenced occurrence data. However, models projecting suitable habitat into the future are impossible to ground truth. One solution is to develop species distribution models for the present and project them to periods in the recent past where distributions are known to test model performance before making projections into the future. Here, we develop models using abiotic environmental variables to quantify the current suitable habitat available to eight Neotropical coastal species: four mangrove species and four salt marsh species. Using a novel model validation approach that leverages newly available monthly climatic data from 1960 to 2018, we project these niche models into two time periods in the recent past (i.e., within the past half century) when either mangrove or salt marsh dominance was documented via other data sources. Models were hindcast‐validated and then used to project the suitable habitat of all species at four time periods in the future under a model of climate change. For all future time periods, the projected suitable habitat of mangrove species decreased, and suitable habitat declined more severely in salt marsh species.

Application of integrated species distribution models in parasitic diseases prevention and control: a review

Species distribution model, a mathematical model theoretically based on the temporal and spatial locations of species in the ecosystem and their associations with other species, is useful to display the current species distribution and predict the future species distribution, which has been widely applied in ecology, biogeography and spatial transmission of infectious diseases. Integrated species distribution model is a comprehensive, summative and reliable combination model that simultaneously uses multiple species distribution models or integrates multiple data sources for modeling. This review describes the theory and classification of species distribution models, and summarizes the creation and verification of integrated species distribution models and their applications in parasitic disease prevention and control. During the practical applications of integrated species distribution models, the study scale, niche matching, big data utilization, combination of multidisciplinary methods and knowledge background and ecological implications should be emphasized.

Call for integrating future patterns of biodiversity into European conservation policy

AbstractGiven the unprecedented rates of global warming, widespread shifts in species’ distributions are anticipated to play a key role for their survival. Yet, current conservation policies often allocate priority to native species and their typical habitats, thereby preserving historic conditions rather than preparing for future species distributions. Policy initiatives aimed at halting biodiversity loss, such as the EU 2030 Biodiversity Strategy, could provide an opportunity to proactively integrate species’ future distributions into conservation objectives on an international scale, for example, by encouraging management actions that allow for species migration along projected paths of dispersal. Acknowledging climate‐tracking species as a conceptually distinct phenomenon, we qualitatively analyzed to which extent the EU 2030 Biodiversity Strategy and the legal framework it is embedded in, such as the Draft Note on Designation Criteria (ENV.D.3/JC) and the Framework for Blue and Green Infrastructure (SWD/2019/193), integrated climate‐trackers into their conservation objectives. We found that the Biodiversity Strategy did not explicitly incorporate future patterns of species distributions into conservation planning but emphasized the maintenance of historical community compositions and species distributions. While the commitments in these legal documents to nature restoration will certainly be helpful for biodiversity conservation today and after 2030, it may miss the chance to be a more comprehensive conservation policy.

Restoring habitat for fire-impacted species’ across degraded Australian landscapes

In the summer of 2019–2020, southern Australia experienced the largest fires on record, detrimentally impacting the habitat of native species, many of which were already threatened by past and current anthropogenic land use. A large-scale restoration effort to improve degraded species habitat would provide fire-affected species with the chance to recover and persist in burnt and unburnt habitat. To facilitate this, decision-makers require information on priority species needs for restoration intervention, the suite of potential restoration interventions, and the priority locations for applying these interventions. We prioritize actions in areas where restoration would most likely provide cost-effective benefits to priority species (defined by each species proportion of habitat burned, threat status, and vulnerability to fires), by integrating current and future species habitat suitability maps with spatially modelled costs of restoration interventions such as replanting, removing invasive species, and implementing ecologically appropriate fire management. We show that restoring the top ∼69% (112 million hectares) of the study region (current and future distributions of priority species) accounts for, on average, 95% of current and future habitat for every priority species and costs ∼AUD$73 billion yr−1 (AUD$650 hectare−1 yr−1) annualized over 30 years. This effort would include restoration actions over 6 million hectares of fire-impacted habitat, costing ∼AUD$8.8 billion/year. Large scale restoration efforts are often costly but can have significant societal co-benefits beyond biodiversity conservation. We also show that up to 291 MtCO2 (∼150 Mt DM) of carbon could be sequestered by restoration efforts, resulting in approximately AUD$253 million yr−1 in carbon market revenue if all carbon was remunerated. Our approach highlights the scale, costs, and benefits of targeted restoration activities both inside and outside of the immediate bushfire footprint over vast areas of different land tenures.

Combining Ecological Niche Models and ecosystem services indicators to assess impacts of climate change on kelp: application to French coasts

ABSTRACT Kelp forests, primarily Laminaria digitata, provide a broad range of ecosystem services of high social, economic, and ecological value and are considered one of the most productive ecosystems on the planet. Several studies have shown that kelp ecosystems are regressing in response to multiple stressors, especially climate change, which could lead to local extinctions. This may induce a decrease in the ecosystem services provided. Many studies use ecological niche models (ENM) to project potential future species distributions under climate change scenarios; however, no study has projected the future supply of ecosystem services resulting from shifts in species ranges and changes in biomass. In this study, using French coasts as a case study, we developed a new and reproducible methodological framework that combines ENM and ecosystem services indicators to assess impacts of climate change on ecosystem services supplied by kelp. To this end, we first identified ecosystem services currently provided by kelp and then used ENM to project future kelp distribution from 2041 to 2050 under climate scenarios RCP2.6 and RCP8.5. Finally, by estimating the biomass of kelp, we assessed the current and future ecosystem services provided by kelp.