Ensemble forecast of climate suitability for the Trans-Himalayan Nyctaginaceae species

Response of Extremely Small Populations to Climate Change-A Case of Trachycarpus nanus in Yunnan, China

Climate change affects the geographical distribution of plant species. Rare Trachycarpus nanus with a narrow distribution range, high medicinal value and extremely small population is facing increasing extinction risks under global climate change. In this study, 96 recorded occurrences and 23 environmental factors are used to predict the potential suitable area of T. nanus based on the optimized MaxEnt (3.4.4) model and ArcGIS (10.7) software. The results show that when the parameters are FC = LQ and RM = 1, the MaxEnt model is optimal and AUC = 0.946. The distribution patterns were predicted in the past, present, and four future phases, i.e., 2021-2040 (2030), 2041-2060 (2050), 2061-2080 (2070), and 2081-2100 (2090). The main factors are the annual precipitation (bio12), mean temperature of the coldest quarter (bio11), temperature seasonality (bio4), precipitation of the wettest quarter (bio16), and isothermality (bio3). The potential distribution of T. nanus is primarily concentrated in central Chuxiong, encompassing a total potential suitable area of 5.65 × 104 km2. In historical periods, the total habitat area is smaller than that in the present. In the future, the potential suitable area is generally increased. The centroid analysis shows that T. nanus will move to a high-altitude area and to the southeast. But its dispersal capacity may not keep up with the climate change rate. Therefore, additional protection sites for this species should be appropriately established and the habitat connectivity should be enhanced.

Predicting future climate change impacts on the potential distribution of the black howler monkey (Alouatta pigra): an endangered arboreal primate

Climate change is one of the main factors affecting biodiversity worldwide at an alarming rate. In addition to increases in global extreme weather events, melting of polar ice caps, and subsequent sea level rise, climate change might shift the geographic distribution of species. In recent years, interest in understanding the effects of climate change on species distribution has increased, including species which depend greatly on forest cover for survival, such as strictly arboreal primates. Here, we generate a series of species distribution models (SDMs) to evaluate future projections under different climate change scenarios on the distribution of the black howler monkey (Alouatta pigra), an endemic endangered primate species. Using SDMs, we assessed current and future projections of their potential distribution for three Social Economic Paths (SSPs) for the years 2030, 2050, 2070, and 2090. Specifically, we found that precipitation seasonality (BIO15, 30.8%), isothermality (BIO3, 25.4%), and mean diurnal range (BIO2, 19.7.%) are the main factors affecting A. pigra distribution. The future climate change models suggested a decrease in the potential distribution of A. pigra by projected scenarios (from - 1.23 to - 12.66%). The highly suitable area was the most affected above all in the more pessimist scenario most likely related to habitat fragmentation. Our study provides new insights into the potential future distribution and suitable habitats of Alouatta pigra. Such information could be used by local communities, governments, and non-governmental organizations for conservation planning of this primate species.

Predicting the potential impacts of climate change on the endangered endemic annonaceae species in east africa

Globally, endemic species and natural habitats have been significantly impacted by climate change, and further considerable impacts are predicted. Therefore, understanding how endemic species are impacted by climate change can aid in advancing the necessary conservation initiatives. The use of niche modeling is becoming a popular topic in biological conservation to forecast changes in species distributions under various climate change scenarios. This study used the Australian Community Climate and Earth System Simulator version 1 (ACCESS-CM2) general circulation model of coupled model intercomparison project phase 6 (CMIP6) to model the current distribution of suitable habitat for the four threatened Annonaceae species endemic to East Africa (EA), to determine the impact of climate change on their suitable habitat in the years 2050 (average for 2041-2060) and 2070 (average for 2061-2080). Two shared socio-economic pathways (SSPs) SSP370 and SSP585 were used to project the contraction and expansion of suitable habitats for Uvariodendron kirkii, Uvaria kirkii, Uvariodendron dzomboense and Asteranthe asterias endemic to Kenya and Tanzania in EA. The current distribution for all four species is highly influenced by precipitation, temperature, and environmental factors (population, potential evapotranspiration, and aridity index). Although the loss of the original suitable habitat is anticipated to be significant, appropriate habitat expansion and contraction are projections for all species. More than 70% and 40% of the original habitats of Uvariodendron dzombense and Uvariodendron kirkii are predicted to be destroyed by climate change, respectively. Based on our research, we suggest that areas that are expected to shrink owing to climate change be classified as important protection zones for the preservation of Annonaceae species.

Climate Change Impacts on the Potential Distribution Pattern of Osphya (Coleoptera: Melandryidae), an Old but Small Beetle Group Distributed in the Northern Hemisphere

Exploring the development of species distribution patterns under climate change is the basis of biogeography and macroecology. However, under the background of global climate change, few studies focus on how the distribution pattern and the range of insects have or will change in response to long-term climate change. An old but small, Northern-Hemisphere-distributed beetle group Osphya is an ideal subject to conduct the study in this aspect. Here, based on a comprehensive geographic dataset, we analyzed the global distribution pattern of Osphya using ArcGIS techniques, which declared a discontinuous and uneven distribution pattern across the USA, Europe, and Asia. Furthermore, we predicted the suitable habitats of Osphya under different climate scenarios via the MaxEnt model. The results showed that the high suitability areas were always concentrated in the European Mediterranean and the western coast of USA, while a low suitability exhibited in Asia. Moreover, by integrating the analyses of biogeography and habitat suitability, we inferred that the Osphya species conservatively prefer a warm, stable, and rainy climate, and they tend to expand towards higher latitude in response to the climate warming from the past to future. These results are helpful in exploring the species diversity and protection of Osphya.

Global warming pushes the distribution range of the two alpine 'glasshouse' Rheum species north- and upwards in the Eastern Himalayas and the Hengduan Mountains

Alpine plants' distribution is being pushed higher towards mountaintops due to global warming, finally diminishing their range and thereby increasing the risk of extinction. Plants with specialized 'glasshouse' structures have adapted well to harsh alpine environments, notably to the extremely low temperatures, which makes them vulnerable to global warming. However, their response to global warming is quite unexplored. Therefore, by compiling occurrences and several environmental strata, we utilized multiple ensemble species distribution modeling (eSDM) to estimate the historical, present-day, and future distribution of two alpine 'glasshouse' species Rheum nobile Hook. f. & Thomson and R. alexandrae Batalin. Rheum nobile was predicted to extend its distribution from the Eastern Himalaya (EH) to the Hengduan Mountains (HM), whereas R. alexandrae was restricted exclusively in the HM. Both species witnessed a northward expansion of suitable habitats followed by a southerly retreat in the HM region. Our findings reveal that both species have a considerable range shift under different climate change scenarios, mainly triggered by precipitation rather than temperature. The model predicted northward and upward migration for both species since the last glacial period which is mainly due to expected future climate change scenarios. Further, the observed niche overlap between the two species presented that they are more divergent depending on their habitat, except for certain regions in the HM. However, relocating appropriate habitats to the north and high elevation may not ensure the species' survival, as it needs to adapt to the extreme climatic circumstances in alpine habitats. Therefore, we advocate for more conservation efforts in these biodiversity hotspots.

Spatiotemporal maintenance of flora in the Himalaya biodiversity hotspot: Current knowledge and future perspectives

Mountain ecosystems support a significant one-third of all terrestrial biodiversity, but our understanding of the spatiotemporal maintenance of this high biodiversity remains poor, or at best controversial. The Himalaya hosts a complex mountain ecosystem with high topographic and climatic heterogeneity and harbors one of the world's richest floras. The high species endemism, together with increasing anthropogenic threats, has qualified the Himalaya as one of the most significant global biodiversity hotspots. The topographic and climatic complexity of the Himalaya makes it an ideal natural laboratory for studying the mechanisms of floral exchange, diversification, and spatiotemporal distributions. Here, we review literature pertaining to the Himalaya in order to generate a concise synthesis of the origin, distribution, and climate change responses of the Himalayan flora. We found that the Himalaya supports a rich biodiversity and that the Hengduan Mountains supplied the majority of the Himalayan floral elements, which subsequently diversified from the late Miocene onward, to create today's relatively high endemicity in the Himalaya. Further, we uncover links between this Miocene diversification and the joint effect of geological and climatic upheavals in the Himalaya. There is marked variance regarding species dispersal, elevational gradients, and impact of climate change among plant species in the Himalaya, and our review highlights some of the general trends and recent advances on these aspects. Finally, we provide some recommendations for conservation planning and future research. Our work could be useful in guiding future research in this important ecosystem and will also provide new insights into the maintenance mechanisms underpinning other mountain systems.

AlleleShift: an R package to predict and visualize population-level changes in allele frequencies in response to climate change

Background

At any particular location, frequencies of alleles that are associated with adaptive traits are expected to change in future climates through local adaption and migration, including assisted migration (human-implemented when climate change is more rapid than natural migration rates). Making the assumption that the baseline frequencies of alleles across environmental gradients can act as a predictor of patterns in changed climates (typically future but possibly paleo-climates), a methodology is provided by AlleleShift of predicting changes in allele frequencies at the population level.

Methods

The prediction procedure involves a first calibration and prediction step through redundancy analysis (RDA), and a second calibration and prediction step through a generalized additive model (GAM) with a binomial family. As such, the procedure is fundamentally different to an alternative approach recently proposed to predict changes in allele frequencies from canonical correspondence analysis (CCA). The RDA step is based on the Euclidean distance that is also the typical distance used in Analysis of Molecular Variance (AMOVA). Because the RDA step or CCA approach sometimes predict negative allele frequencies, the GAM step ensures that allele frequencies are in the range of 0 to 1.

Results

AlleleShift provides data sets with predicted frequencies and several visualization methods to depict the predicted shifts in allele frequencies from baseline to changed climates. These visualizations include 'dot plot' graphics (function shift.dot.ggplot), pie diagrams (shift.pie.ggplot), moon diagrams (shift.moon.ggplot), 'waffle' diagrams (shift.waffle.ggplot) and smoothed surface diagrams of allele frequencies of baseline or future patterns in geographical space (shift.surf.ggplot). As these visualizations were generated through the ggplot2 package, methods of generating animations for a climate change time series are straightforward, as shown in the documentation of AlleleShift and in the supplemental videos.

Availability

AlleleShift is available as an open-source R package from https://cran.r-project.org/package=AlleleShift and https://github.com/RoelandKindt/AlleleShift. Genetic input data is expected to be in the adegenet::genpop format, which can be generated from the adegenet::genind format. Climate data is available from various resources such as WorldClim and Envirem.

Climate-Fungal Pathogen Modeling Predicts Loss of Up to One-Third of Tea Growing Areas

Climate change will affect numerous crops in the future; however, perennial crops, such as tea, are particularly vulnerable. Climate change will also strongly influence fungal pathogens. Here, we predict how future climatic conditions will impact tea and its associated pathogens. We collected data on the three most important fungal pathogens of tea (Colletotrichum acutatum, Co. camelliae, and Exobasidium vexans) and then modeled distributions of tea and these fungal pathogens using current and projected climates. The models show that baseline tea-growing areas will become unsuitable for Camellia sinensis var. sinensis (15 to 32% loss) and C. sinensis var. assamica (32 to 34% loss) by 2050. Although new areas will become more suitable for tea cultivation, existing and potentially new fungal pathogens will present challenges in these areas, and they are already under other land-use regimes. In addition, future climatic scenarios suitable range of fungal species and tea suitable cultivation (respectively in CSS and CSA) growing areas are Co. acutatum (44.30%; 31.05%), Co. camelliae (13.10%; 10.70%), and E. vexans (10.20%; 11.90%). Protecting global tea cultivation requires innovative approaches that consider fungal genomics as part and parcel of plant pathology.

Impact of habitat alteration on amphibian diversity and species composition in a lowland tropical rainforest in Northeastern Leyte, Philippines

The impact of anthropogenic habitat alteration on amphibians was investigated, employing an investigative focus on leaf-litter and semi-aquatic species across different habitat alteration types. The habitat alteration types which include primary forest, selectively logged primary forest, secondary forest, abandoned farm areas and pasture (this represents a gradient of habitat alteration ranging from least altered to most altered, respectively) also encompass two habitat types: stream and terrestrial. Species assemblage was compared between habitat alteration types and habitat types, where a total 360 leaf-litter and semi-aquatic amphibians were observed (15 species, 6 families). It was found that amphibian abundance was significantly higher in both forest and stream habitat, and species richness did not differ with respect to habitat alteration type. It was determined, however, that species richness was highly dependent on habitat type (significantly higher in stream habitat). Meanwhile, diversity (Shannon-Wiener) was significantly higher in both forest and stream habitat, and species composition differed markedly between habitat alteration types for stream strip plots. Forest habitat exhibited domination by forest specialist species, while altered habitat (abandoned farm areas and pasture) exhibited domination by open-habitat specialist species. Additionally, strong relationships were found between species composition and abundance, as well as richness and diversity (within the measured habitat structures and observed microclimatic conditions). Analyses determined that the higher abundance of leaf-litter and semi-aquatic amphibians was best explained by higher DBH (1.3 m from the ground) and lower temperature and the higher species richness was best explained by higher understorey density. Additionally, higher diversity was associated with increasing understorey density, tree density and temperature. In general, the assemblage of leaf-litter and semi-aquatic amphibians in the lowland tropical rainforest in northeastern Leyte was affected by habitat alteration, highlighting the on-going importance of conservation efforts.

Habitat Suitability Estimation Using a Two-Stage Ensemble Approach

Biodiversity conservation is important for the protection of ecosystems. One key task for sustainable biodiversity conservation is to effectively preserve species’ habitats. However, for various reasons, many of these habitats have been reduced or destroyed in recent decades. To deal with this problem, it is necessary to effectively identify potential habitats based on habitat suitability analysis and preserve them. Various techniques for habitat suitability estimation have been proposed to date, but they have had limited success due to limitations in the data and models used. In this paper, we propose a novel scheme for assessing habitat suitability based on a two-stage ensemble approach. In the first stage, we construct a deep neural network (DNN) model to predict habitat suitability based on observations and environmental data. In the second stage, we develop an ensemble model using various habitat suitability estimation methods based on observations, environmental data, and the results of the DNN from the first stage. For reliable estimation of habitat suitability, we utilize various crowdsourced databases. Using observational and environmental data for four amphibian species and seven bird species in South Korea, we demonstrate that our scheme provides a more accurate estimation of habitat suitability compared to previous other approaches. For instance, our scheme achieves a true skill statistic (TSS) score of 0.886, which is higher than other approaches (TSS = 0.725 ± 0.010).

Distribution Pattern of Endangered Plant Semiliquidambar cathayensis (Hamamelidaceae) in Response to Climate Change after the Last Interglacial Period

Semiliquidambar cathayensis is a special and endangered plant in China, used for traditional Chinese medicine and in landscape applications. Predicting the impact of climate change on the distribution of S. cathayensis is crucial for its protection and the sustainable use of resources. We used the maximum entropy (MaxEnt) model optimized by the ENMeval data packet to analyze the potential geographic distribution changes of S. cathayensis in 12 provinces of Southern China for the different periods since the last interglacial period (LIG, 120–140 ka). Considering the potential geographic distribution changes in the province, and based on the two climate scenarios of Representative Concentration Pathways (RCP) 2.6 and RCP 8.5, the distribution range of S. cathayensis was analyzed and we predicted the range for the 2050s (average for 2041–2060) and 2070s (average for 2061–2080). The area under AUC (Area under the receiver operating characteristic (ROC) curve) is 0.9388 under these parameters, which indicates that the model is very accurate. We speculate that the glacial period refugia were the Nanling and Wuyi Mountains for S. cathayensis, and central and Western Fujian and Taiwan are likely to be the future climate refugia. In the mid-Holocene (MH, 6 ka), the growth habitat was 32.41% larger than the modern habitat; in the 2050s and 2070s (except RCP2.6–2070s), the growth habitat will shrink to varying degrees, so efforts to support its in situ and ex situ conservation are urgently needed. The jackknife test showed that the main factors affecting the geographical distribution of S. cathayensis were annual precipitation, precipitation of the wettest month, and precipitation of the driest month. The annual precipitation may be the key factor restricting the northward distribution of S. cathayensis. In general, the centroid of the distribution of S. cathayensis will move northward. The centroid of the adaptive habitats will move northward with the highest degree of climate abnormality. We think that Hainan Island is the most likely origin of S. cathayensis. These findings provide a theoretical basis for the establishment of genetic resources protection measures, the construction of core germplasm resources, and the study of the formation and evolution of Hamamelidaceae.

Modeling the Effect of Climate Change on the Potential Distribution of Qinghai Spruce (Picea crassifolia Kom.) in Qilian Mountains

Qinghai spruce forests play a key role in water conservation in the dry region of northwest China. So, it is necessary to understand the impacts of climate change on the species to implement adaptation strategies. Based on the four-emission scenario (i.e., RCP2.6 (Representative Concentration Pathway), RCP4.5, RCP6.0 and RCP8.5) set by the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report, in the study, we predicted the potential distribution of Qinghai spruce (Picea crassifolia Kom.) under current and future scenarios using a maximum entropy (Maxent) model. Seven variables, selected from 22 variables according to correlation analysis combining with their contribution rates to the distribution, are used to simulate the potential distribution of the species under current and future scenarios. Simulated results are validated by area under the operating characteristic curve (AUC). Results demonstrate that elevation, mean temperature of wettest quarter, annual mean temperature, and mean diurnal range are more important in dominating the potential distribution of Qinghai spruce. Ratios of the suitable area to the total study area are 34.3% in current climate condition, 34% in RCP2.6, 33.9% in RCP4.5, 33.8% in RCP6.0, and 30.5% in RCP8.5, respectively. The warmer the climate condition is, the more area of higher suitable classification is changed to that of lower suitable classification. The ratios of real distribution area in simulated unsuitable class to the real distribution area change from 4.3% (60.7 km2) in the current climate to 13% (185 km2) in RCP8.5, suggesting that the real distribution area may decrease in the future. We conclude that there is a negative effect of climate change on the distribution of Qinghai spruce forest. The result can help decision-makers to draft adaptation countermeasures based on climate change.

Predicting the potential distribution of the endangered red panda across its entire range using MaxEnt modeling

An upsurge in anthropogenic impacts has hastened the decline of the red panda (Ailurus fulgens). The red panda is a global conservation icon, but holistic conservation management has been hampered by research being restricted to certain locations and population clusters. Building a comprehensive potential habitat map for the red panda is imperative to advance the conservation effort and ensure coordinated management across international boundaries. Here, we use occurrence records of both subspecies of red pandas from across their entire range to build a habitat model using the maximum entropy algorithm (MaxEnt 3.3.3k) and the least correlated bioclimatic variables. We found that the subspecies have separate climatic spaces dominated by temperature-associated variables in the eastern geographic distribution limit and precipitation-associated variables in the western distribution limit. Annual precipitation (BIO12) and maximum temperature in the warmest months (BIO5) were major predictors of habitat suitability for A. f. fulgens and A. f. styani, respectively. Our model predicted 134,975 km2 of red panda habitat based on 10 percentile thresholds in China (62% of total predicted habitat), Nepal (15%), Myanmar (9%), Bhutan (9%), and India (5%). Existing protected areas (PAs) encompass 28% of red panda habitat, meaning the PA network is currently insufficient and alternative conservation mechanisms are needed to protect the habitat. Bhutan's PAs provide good coverage for the red panda habitat. Furthermore, large areas of habitat were predicted in cross-broader areas, and transboundary conservation will be necessary.

Determining bioclimatic space of Himalayan alder for agroforestry systems in Nepal

Himalayan alder species are proven to be very useful in traditional as well as contemporary agroforestry practice. These nitrogen-fixing trees are also useful in the land restoration. Therefore, understanding the distribution of Himalayan alder and the potential zone for plantation is meaningful in the agroforestry sector. Suitable climatic zones of Alnus spp. were modelled in MaxEnt software using a subset of least correlated bioclimatic variables for current conditions (1950-2000), topographic variables (DEM derived) and Landuse Landcover (LULC) data. We generated several models and selected the best model against random models using ANOVA and t-test. The environmental variables that best explained the current distribution of the species were identified and used to project into the future. For future projections, ensemble scenarios of climate change projection derived from the results of 19 Earth System Models (ESM) were used. Our model revealed that the most favorable conditions for Alnus nepalensis are in central Nepal in the moist north-west facing slope, whereas for Alnus nitida they are in western Nepal. The major climatic factor that contributes to Alnus species distribution in Nepal appears to be precipitation during the warmest quarter for A. nepalensis and precipitation during the driest quarter for A. nitida. Future projections revealed changes in the probability distribution of these species, as well as where they need conservation and where they can be planted. Also, our model predicts that the distribution of Alnus spp. in hilly regions will remain unchanged, and therefore may represent sites that can be used to revitalize traditional agroforestry systems and extract source material for land restoration.

Distribution and in situ conservation of a relic Chinese oil woody species Xanthoceras sorbifolium (yellowhorn)

To understand the contemporary and anticipated future (future 30–50 years) distribution of Chinese wild yellowhorn (Xanthoceras sorbifolium Bunge) and to improve the species’ in situ conservation strategy within the network of China’s National Nature Reserves (NNR), we used BiodiversityR to predict the species’ distribution utilizing the “always-suitable” map concept. We then delineated the always-suitable distributions with the existing NNRs to identify potential conservation areas using an approach that concurrently considered spatial distribution, gap analysis, the role of climate change, and economic analyses. Seven bioclimatic variable predictors and 12 environmental niche modelling submodels successfully contributed to the final model assembly (AUC = 0.916, κ = 0.398). The species range delineation indicated that 71 of the 427 NNRs were included in the always-suitable area, accounting for 26 007 km2 (1.58%) of the species total distribution. This mapping endeavour highlighted the negative impact of climate change with a projected 15%–20% habitat decline and expected species’ distribution centers shifting from the country’s northwest to the southeast. Our results predict the continuous deterioration of X. sorbifolium because of its existing utilization as an oil source and its increased bioenergy potential. The adoption of a flexible management strategy embracing acceptable trade-offs between conservation and utilization within China’s NNRs could effectively alleviate the expected species decline.

Modeling the impact of climate change on wild Piper nigrum (Black Pepper) in Western Ghats, India using ecological niche models

The center of diversity of Piper nigrum L. (Black Pepper), one of the highly valued spice crops is reported to be from India. Black pepper is naturally distributed in India in the Western Ghats biodiversity hotspot and is the only known existing source of its wild germplasm in the world. We used ecological niche models to predict the potential distribution of wild P. nigrum in the present and two future climate change scenarios viz (A1B) and (A2A) for the year 2080. Three topographic and nine uncorrelated bioclim variables were used to develop the niche models. The environmental variables influencing the distribution of wild P. nigrum across different climate change scenarios were identified. We also assessed the direction and magnitude of the niche centroid shift and the change in niche breadth to estimate the impact of projected climate change on the distribution of P. nigrum. The study shows a niche centroid shift in the future climate scenarios. Both the projected future climate scenarios predicted a reduction in the habitat of P. nigrum in Southern Western Ghats, which harbors many wild accessions of P. nigrum. Our results highlight the impact of future climate change on P. nigrum and provide useful information for designing sound germplasm conservation strategies for P. nigrum.

Suitability Analysis and Projected Climate Change Impact on Banana and Coffee Production Zones in Nepal

The Government of Nepal has identified opportunities in agricultural commercialization, responding to a growing internal demand and expansion of export markets to reduce the immense trade deficit. Several cash crops, including coffee and bananas, have been identified in the recently approved Agriculture Development Strategy. Both of these crops have encouraged smallholder farmers to convert their subsistence farming practices to more commercial cultivation. Identification of suitable agro-ecological zones and understanding climate-related issues are important for improved production and livelihoods of smallholder farmers. Here, the suitability of coffee and banana crops is analyzed for different agro-ecological zones represented by Global Environmental Stratification (GEnS). Future shifts in these suitability zones are also predicted. Plantation sites in Nepal were geo-referenced and used as input in species distribution modelling. The multi-model ensemble model suggests that climate change will reduce the suitable growing area for coffee by about 72% across the selected emission scenarios from now to 2050. Impacts are low for banana growing, with a reduction in suitability by about 16% by 2050. Bananas show a lot of potential for playing an important role in Nepal as a sustainable crop in the context of climate change, as this study indicates that the amount of area suited to banana growing will grow by 40% by 2050. Based on our analysis we recommend possible new locations for coffee plantations and one method for mitigating climate change-related problems on existing plantations. These findings are expected to support planning and policy dialogue for mitigation and support better informed and scientifically based decision-making relating to these two crops.

Integrating subsistence practice and species distribution modeling: assessing invasive elodea's potential impact on Native Alaskan subsistence of Chinook salmon and whitefish

Alaska has one of the most rapidly changing climates on earth and is experiencing an accelerated rate of human disturbance, including resource extraction and transportation infrastructure development. Combined, these factors increase the state's vulnerability to biological invasion, which can have acute negative impacts on ecological integrity and subsistence practices. Of growing concern is the spread of Alaska's first documented freshwater aquatic invasive plant Elodea spp. (elodea). In this study, we modeled the suitable habitat of elodea using global and state-specific species occurrence records and environmental variables, in concert with an ensemble of model algorithms. Furthermore, we sought to incorporate local subsistence concerns by using Native Alaskan knowledge and available statewide subsistence harvest data to assess the potential threat posed by elodea to Chinook salmon (Oncorhynchus tshawytscha) and whitefish (Coregonus nelsonii) subsistence. State models were applied to future climate (2040-2059) using five general circulation models best suited for Alaska. Model evaluations indicated that our results had moderate to strong predictability, with area under the receiver-operating characteristic curve values above 0.80 and classification accuracies ranging from 66 to 89 %. State models provided a more robust assessment of elodea habitat suitability. These ensembles revealed different levels of management concern statewide, based on the interaction of fish subsistence patterns, known spawning and rearing sites, and elodea habitat suitability, thus highlighting regions with additional need for targeted monitoring. Our results suggest that this approach can hold great utility for invasion risk assessments and better facilitate the inclusion of local stakeholder concerns in conservation planning and management.