Information For Planning Management Research Articles

The impact of plant-derived fire management prescriptions on fire-responsive bird species.

In fire-prone regions, the occurrence of some faunal species is contingent on the presence of resources that arise through post-fire plant succession. Through planned burning, managers can alter resource availability and aim to provide the conditions required to promote biodiversity. Understanding how species occurrence changes at different spatial and temporal scales after fire is essential to achieve this goal. However, many fire prescriptions are guided primarily by the responses of fire-sensitive plants when setting tolerable fire intervals. This approach assumes that maintaining floristic diversity will satisfy the requirements of fauna. We surveyed bird species in two semi-arid vegetation types across an environmental gradient in south-eastern Australia. We conducted four surveys at each of 253 sites across a 75-year chronosequence of time since fire and used generalized additive mixed models to examine changes in the occurrence of birds in response to time since fire. Model predictions were compared to plant-derived fire prescriptions currently guiding fire management in the region. Time since fire was a significant predictor for 18 of 28 species modeled, in at least one vegetation type, over a gradient of 1.3° of latitude. We detected considerable variation in the responses of some species, both between vegetation types and geographically within a vegetation type. Our evaluation of plant-derived fire prescriptions suggests that the intervals considered acceptable for maintaining floristic diversity may not be sustainable for populations of birds requiring longer unburnt vegetation, with 6 of the 12 species assessed attaining a mean occurrence probability of 20.3% by the minimum tolerable fire interval, and 57.3% by the maximum tolerable fire interval, in their respective vegetation types. Our findings highlight the potential vulnerability of fire-responsive bird species if fire prescriptions are applied in a manner that fails to account for the slow development of habitat resources needed by some species, and the variation detected within the responses of species. This highlights the need for species-specific data collected at an appropriate spatial scale to inform management plans.

An opportunity missed: Strengthening health system data on multisystem inflammatory syndrome in children from low- and middle-income countries in Asia

BackgroundMultisystem inflammatory syndrome in children (MIS-C) is a severe complication associated with SARS-CoV-2 infection. The clinical epidemiology of MIS-C is not completely understood in low- and middle-income countries (LMICs) due to limited reporting, including in Asia where there was a substantial burden of COVID-19. We aimed to discuss the challenges of diagnosing MIS-C and factors which may cause children from Asian LMICs to have an increased risk of MIS-C. MethodsNot applicable. ResultsThe burden of MIS-C in Asian LMICs may be disproportionately high due to underlying risk factors, resource-limited health systems, and the increased infectivity and transmissibility of recent SARS-CoV-2 variants. Complex clinical features of MIS-C contributed to missed or delayed diagnosis and treatment, while underlying risk factors including ethnicity, chronic health conditions, and socioeconomic factors may have predisposed children in Asian LMICs to MIS-C. ConclusionsThere was a lack of data on the clinical epidemiology of MIS-C in Asian LMICs during the COVID-19 pandemic, despite reports of higher paediatric mortality rates compared to high-income countries. This highlights the need for LMICs to have strong surveillance systems to collect high-quality and timely data on newly emerging complications associated with a pandemic, such as MIS-C. This will lead to rapid understanding of these emerging complications, and inform clinical management, disease prevention and health system planning.

An Approach for Future Droughts in Northwest Türkiye: SPI and LSTM Methods

Predetermining the risk of possible future droughts enables proactive measures to be taken in key areas such as agriculture, water management, and food security. Through these predictions, governments, non-governmental organizations, and farmers can develop water-saving strategies, encourage more efficient use of water, and minimize economic losses that may occur due to drought. Thus, future drought forecasts stand out as a strategic planning tool for the protection of natural resources. To achieve this aim, forecasted drought conditions for the next decade (2024–2034) at nine meteorological stations in the Sakarya basin, located northwest of Türkiye, are examined, using historical monthly precipitation data from 1991 to 2023. This study uses the Standardized Precipitation Index (SPI) and Long Short-Term Memory (LSTM) deep learning methods to investigate future meteorological droughts. The research confirms the compatibility and reliability of the LSTM method for forecasting meteorological droughts by comparing historical and forecasted SPI values’ correlograms and trends. In addition, drought maps are created to visually represent the spatial distribution of the most severe droughts expected in the coming years, and areas at risk of drought in the Sakarya Basin are determined. The study contributes to the limited literature on forward-looking drought forecasts in the Sakarya Basin and provides valuable information for long-term water resource planning and drought management in the region.

Analysis of the implementation effect and evaluation of the vaccine protection effect of the live attenuated varicella vaccine program for school-age children in Bao’an district of Shenzhen,China

ABSTRACT The objective of the study is to analyze the implementation effect of the Live Attenuated Varicella Vaccine (VarV) Vaccination Program for eligible children in Bao’an District, Shenzhen, and evaluate the vaccine effectiveness. Children’s vaccination data was obtained from the Shenzhen Immunization Planning Information Management System, while varicella case data came from the China Disease Prevention and Control Information System. The Joinpoint regression method examined vaccination rate trends, and a retrospective cohort study assessed vaccine effectiveness. After program implementation, VarV vaccination rates significantly increased, surpassing provincial and national averages. Overall incidence declined 54.6% across age groups, with the largest reductions among 7- and 6-year-olds. One year post-vaccination, single-dose vaccine effectiveness was 91.1% (95% CI: 79.2% to 96.2%). However, two doses remained 91.4% effective(95% CI: 89.1% to 93.2%) after 7 years. Overall, Shenzhen’s VarV program achieved positive results. For children under six, routine immunization with two doses of VarV should be strengthened. Furthermore, we recommend that physicians conduct thorough inquiries to ascertain patients’ vaccination history and previous varicella infections. This will enable doctors to provide tailored vaccination recommendations based on comprehensive, practical evaluations.

Studying Urbanization Pattern in Sambalpur City during 1992-2042 using CA-ANN, and Markov-Chain Model

Models of land use/land cover (LULC) are crucial for assessing changes in LULC, forecasting land use needs, and providing guidance for sensible land use planning and management especially in urban areas. Urban sprawl is one of the main causes of the erratic variation in LULC around the globe. In this study, we used the CA-ANN and Markov-Chain models to analyse the LULC simulation based on LULC patterns of previous decades as well as the directional changes of urban expansion in Sambalpur city. We used the random forest (RF) model and Landsat imageries to prepare LULC maps for the years 1992, 2002, 2012 and 2022, for better classification accuracy. The result showed that the overall accuracy and kappa value were 94.24%, 89%, 94%, and 90% and 0.92, 0.80, 0.90 and 0.85, respectively for the selective years. Based on the transition matrix model (1992-2012), the LULC map of the year 2022 was obtained, and validated, and subsequently, LULC maps for the years 2032 and 2042 were predicted with a Kappa value of 94.97% and 93.24% respectively. The results revealed that the maximum amount of bare land converted in the settlement area, and the maximum sprawl occur in NW and 4km buffer zones. These findings define current and future patterns in LULC and offer vital information for planning and sustainable land use management in Sambalpur city.

ChinaRiceCalendar – seasonal crop calendars for early-, middle-, and late-season rice in China

Abstract. Long time series and large-scale rice calendar datasets provide valuable information for agricultural planning and field management in rice-based cropping systems. However, current regional-level rice calendar datasets do not accurately distinguish between rice seasons in China, causing uncertainty in crop model simulation and climate change impact analysis. Based on satellite remote sensing data, we extracted transplanting, heading, and maturity dates of early-, middle-, and late-season rice across China from 2003 to 2022 and established a multi-season rice calendar dataset named ChinaRiceCalendar (https://doi.org/10.7910/DVN/EUP8EY, Liu et al., 2023). Overall, the ChinaRiceCalendar dataset shows good agreement with field-observed phenological dates of early-, middle-, and late-season rice in Chinese agricultural meteorological stations (AMSs). According to the calendar data from 2003 to 2022 in China, the transplanting dates for early-, middle-, and late-season rice shifted by +0.7, −0.7, and −5.1 DOY (day of year) per decade, respectively; the heading dates for early-, middle-, and late-season rice shifted by −0.5, +2.7, and −0.6 DOY per decade, respectively; the maturity dates for early-, middle-, and late-season rice shifted by −0.7, +3.8, and −1.6 DOY per decade, respectively. ChinaRiceCalendar can be utilized to investigate and optimize the spatiotemporal structure of rice cultivation in China under climate and land use change.

A Science and Community-Driven Approach to Illustrating Urban Adaptation to Coastal Flooding to Inform Management Plans

Academic research plays a pivotal role in illustrating and testing potential future adaptation strategies to sea level rise in low-lying coastal communities and enhances local municipalities’ adaptation plans. In Waikīkī, Hawai‘i, the built environment is increasingly impacted by flooding from multiple drivers: sea level rise-induced direct marine inundation, storm-drain backflow, and groundwater inundation (GWI), compounded by high-wave runup, extreme tides, heavy rainfall, and a shallow groundwater table. Given Waikīkī’s economic and cultural importance, in-place accommodation of flooding is desired, yet implementation plans have not been developed. By combining current scientific research, urban design visualizations, and community feedback, the interdisciplinary research team advanced intentional communication between the many parties seeking increased flood resilience through the end of the 21st century. Site-specific architectural renderings were a key tool to prompt structured community input on the coordination, prioritization, policy, and feasibility of adaptation measures for buildings, utilities, transportation, and open space. Public outreach reports document that the majority of participants thought all adaptation strategies presented were applicable, especially relocating critical equipment in buildings and streets. Proposed methods to develop sea level rise-adjusted minimum building elevation requirements may inform local municipalities’ future codes to minimize coastal property damage. The multi-year iterative process fostered growing participation in hosted and invited events, further improving the publicly distributed research products.

Analysis of Vegetation Cover Change with Satellite Images using Landsat 8 in the Inambari District in the Period 2013-2023

Multi-temporal analysis of vegetation cover allows the detection and monitoring of changes in vegetation cover, such as deforestation, reforestation, urban expansion or changes in land use, and also provides valuable information for territorial planning and land use management. . , those responsible for urban, regional and environmental planning can use these analyzes to make informed decisions about how to use and conserve natural resources in a sustainable way and also facilitate the environmental impact assessment of human activities, such as agriculture, mining or urbanization. The objective of this article is to identify and quantify the changes in vegetation cover in the Inambari district using Landsat 8 satellite images, which is non-experimental and quantitative in approach, the Arcgis 10.5 software was applied to make the maps of vegetation cover and was carried out in the District of Inambari, Province of Tambopata and Department of Madre de Dios, where the comparison of changes in vegetation cover was carried out in the years 2013, 2015, 2017 and 2023. The results showed that the variation The maximum vegetation cover was between the years 2015 and 2017 in the soil without vegetation cover, which was from 45190.27 to 264766.32 hectares with a percentage variation of 45.3% and the minimum variation was between the years 2013 to 2015 in the soil without vegetation cover, which It was from 25528.08 to 45190.27 Hectares with an increase of 4.1%.

Evaluation of Historic Trends for Monthly, Seasonal, and Annual Rainfall Series of Tenkasi, Tamil Nadu, India

Analyzing the variability and trends of rainfall plays a major role in water resource planning and management. Changes in rainfall patterns significantly influence the water availability in the irrigation structures and agronomical practices of crops. This study aimed to investigate the trends and estimate the magnitudes of monthly, seasonal, and annual rainfall series in Tenkasi, Tamil Nadu, India, using 49 years of rainfall data from 1971 to 2019. Sen’s Innovative trend analysis (ITA) method, Mann-Kendall (MK), and Simple Linear Regression (SLR) test were applied to assess the trends at 5 and 10 % significance levels. Trend magnitudes were estimated by Sen’s slope estimator (SSE) and SLR method. Changes in rainfall magnitude with mean values in percentage were estimated for all three slope estimation methods. The results revealed that the ITA method detected more significant trends of rainfall series over other methods. Significant downward trends were exhibited by October and north east monsoon (NEM) rainfall series had a trend magnitude of -0.43 mm/year and -0.04 mm/year. The percentage change in magnitude of the trend from mean values for October and the NEM series was -11.5% and -0.39%. Sub-trends within the October and NEM rainfall series showed that the low rainfall sub-series exhibited no trend, medium and high rainfall sub-series showed a downward trend. This study concluded that, in comparison to traditional trend analysis methods, the ITA method demonstrated a more rigorous investigation of trends. The significant decrease in rainfall during the NEM necessitates greater attention to water resources planning and management, serving as valuable scientific information for both crop planning and water resource management.

Competition reduces structural defense in an invasive thistle in the field

AbstractInvasive thistles reduce the productivity of pastures and rangelands because their structural defenses make them unpalatable to grazing livestock. However, plants potentially alter their growth patterns, including their allocation of resources to defense, in response to the presence of competing vegetation. Understanding the effects of competition on the structural defense of problematic pasture weeds can inform management plans that reduce the economic harm caused by these pests. We grew musk thistle (Carduus nutans L., also commonly called nodding thistle) in a fully crossed factorial field experiment in a single abandoned pasture in 2017 with two experimental factors: the level of thistle infestation (1 thistle or 5, resulting in densities of 4 or 20 plants m−2) and the presence or absence of grazing (simulated by weekly trimming of competing vegetation). We assessed the effects of treatments on defense by counting prickles >3-mm long on leaves. Our analysis included leaf age and leaf size as covariates. Competition reduced the number of prickles present on leaves. Regression analysis showed that an increase from, for example, 50 g to 200 g of competing vegetation within 50 by 50 cm study plots reduced the expected average number of prickles on intermediate-aged leaves with average length 25.5 cm by 76.9 prickles per leaf, or 41%. This pattern was similar for leaves of all ages, although the oldest leaves generally had fewer prickles than younger leaves. We did not observe differences in defense structures between plants neighbored by conspecifics and those neighbored by other competitors. Carduus nutans has been previously managed using high densities of grazers, and this practice may be more likely to damage less-defended individuals such as those we observed in our treatments with competition. This finding suggests that maintaining competition in pastures may increase C. nutans vulnerability to grazing.

MRI Data Analysis in Malformations of Cortical Development.

Brain magnetic resonance imaging (MRI) is a noninvasive imaging modality that utilizes powerful magnets and radio waves to generate detailed images of the brain, making it a valuable tool for investigating malformations of cortical development (MCD). Various MRI techniques, including 3D T1-weighted, multiplanar thin-sliced T2-weighted, and 3D fluid-attenuated inversion recovery (FLAIR) sequences, can provide high-resolution images with excellent spatial and contrast resolution, allowing for a detailed visualization of cortical anatomy and abnormalities. Almost all MCD can be detected and characterized using MRI. Advanced techniques, such as arterial spin labeling MR perfusion, diffusion tensor imaging (DTI), and functional MRI (fMRI), may be used to improve the detection rate of these malformations and to plan surgery in case of drug-resistant epilepsy. However, there are also limitations related to high cost, relatively low availability, need for sedation or anesthesia, and limited sensitivity for detecting subtle focal cortical malformations. Despite these limitations, brain MRI plays a crucial role in the investigation of MCD, providing valuable information for diagnosis, treatment planning, and patient management.

DIAGNOSTIC ACCURACY OF T2 WEIGHTED IMAGING AND GADOLINIUM ENHANCED MRI IN DIAGNOSIS AND STAGING OF URINARY BLADDER CARCINOMA TAKING HISTOPATHOLOGY AS GOLD STANDARDS

Urinary bladder carcinoma (UBC) diagnosis and staging are critical for treatment planning and patient prognosis. This histopathology-guided study evaluates the diagnostic accuracy of T2-weighted imaging (T2WI) and gadolinium-enhanced MRI (GE-MRI) in UBC diagnosis and staging, with histopathology as the gold standard. A total of 30 patients with suspected or confirmed UBC were included in the study. T2WI and GE-MRI were performed, and imaging findings were compared with histopathological results obtained from transurethral resection of bladder tumor (TURBT) or radical cystectomy specimens. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of T2WI and GE-MRI were calculated. The results demonstrate that T2WI had a sensitivity of 85%, specificity of 80%, PPV of 90%, NPV of 75%, and overall accuracy of 83.3% in diagnosing UBC. GE-MRI showed a sensitivity of 90%, specificity of 85%, PPV of 92%, NPV of 80%, and overall accuracy of 88.3%. Both imaging modalities exhibited high diagnostic accuracy in detecting UBC lesions and staging tumor extent. In conclusion, T2WI and GE-MRI are valuable tools for UBC diagnosis and staging, providing essential information for treatment planning and patient management.

AI dietician: Unveiling the accuracy of ChatGPT's nutritional estimations

We investigate the accuracy and reliability of ChatGPT, an artificial intelligence model developed by OpenAI, in providing nutritional information for dietary planning and weight management. The results have a reasonable level of accuracy, with energy values having the highest level of conformity: 97% of the artificial intelligence values fall within a 40% difference from United States Department of Agriculture data. Additionally, ChatGPT displayed consistency in its provision of nutritional data, as indicated by relatively low coefficient of variation values for each nutrient. The artificial intelligence model also proved efficient in generating a daily meal plan within a specified caloric limit, with all the meals falling within a 30% bound of the United States Department of Agriculture's caloric values. These findings suggest that ChatGPT can provide reasonably accurate and consistent nutritional information. Further research is recommended to assess the model's performance across a broader range of foods and meals.<END ABSTRACT>

The design scheme of urban and rural planning management system based on GIS

In urban construction and development, computer technology, information technology and CGI technology have been widely used in urban planning and management, and there are more and more application studies on related information systems. Although excellent results have been achieved in the overall development, there are still many places to be improved. CGI, as a combination of technology and geographic information system technology, applies innovation in the field of urban planning, which can not only show the characteristics of distributed, interactive and dynamic, but also fundamentally ensure the operation efficiency of urban planning management information system. Therefore, on the basis of understanding the current development status and application research of urban planning and management information system, this paper mainly studies the design scheme based on geographic information system technology according to the key technologies of urban planning and management system, so as to improve the effect of traditional urban planning and management and provide more quality services for social residents.

Application of ArcGIS 3D modeling technology in the study of land use policy decision making in China

In this paper, a land use management information system based on ArcGIS 3D modeling technology is constructed to process land use policy decisions through ArcSDE spatial data engine and Oracle relational database to realize a land use planning management information system. Using genetic algorithm in order to use for regional land use optimization allocation, the introduction of multi-intelligent body system in this algorithm will be able to enhance the optimization search ability of the algorithm and make the genetic algorithm to obtain land use planning supported. The behavior of the main body of the integrated land use planning decision maker will guide the development of the quantitative structure of land use in terms of spatial layout toward sustainability. The experimental results prove that the target is better than the other three types of scenarios under the integrated benefit model, then it is reduced by 18.67%, 15.98% and 16.61%, and the number of spatially contiguous areas is increased by 9.4%, 13.8% and 0.8%, respectively. The proposed model can reasonably configure the regional land use quantitative results and spatial layout, and coordinate the needs of different land use decision makers.

Coupling RESI with Multi-Scenario LULC Simulation and Spatiotemporal Variability Analysis: An Ecological Spatial Constraint Approach

Southwest China’s arid river valleys represent ecologically vulnerable areas with intense human activity. Understanding the historical changes in LULC and land cover and projecting the impacts of various development scenarios on future LULC have become crucial for regional spatial information management and territorial spatial planning. This research analyzes the land-use changes in the Yuanmou dry-hot valley over a 30-year span from 1990 to 2020. Building upon the PLUS model, we established a coupled habitat quality spatial and multi-scenario land-use simulation model. Four development scenarios were proposed: natural progression, economic development, ecological conservation, and balanced development. We conducted simulations and evaluations of land-use in the Yuanmou dry-hot valley for 2030 using the PLUS mode, assessing the sustainability of future development scenarios under varying ecological constraints. During the simulation, three distinct RESI regions were employed as restricted development zones, integrating the three ecological constraints with the four simulation scenarios. We introduced a novel approach based on ecological environmental quality as the ecological constraint, providing a scientific reference for sustainable development in ecologically vulnerable areas. The results indicate that under ecological conservation scenarios with high-to-low RESI constraints, the ecological environment is superior to the other three scenarios. The results show the following: (1) From 1990 to 2020, aside from a continuous decrease in grassland area, there was an increasing trend in the areas of water bodies, forests, croplands, construction lands, and unused lands in the Yuanmou dry-hot valley. (2) By 2030, under all four development scenarios, the cropland area is expected to expand rapidly, while forested areas will decrease; grassland areas will decline under natural and economic development scenarios but show opposite trends under the other scenarios; and construction land and unused land areas will decrease under the ecological conservation and balanced development scenarios. (3) Land-use intensity analysis for the four scenarios indicated that, by 2030, unused lands in the Yuanmou dry-hot valley are more likely to be converted into water bodies, forests are more likely to be converted into croplands and grasslands, grasslands are more likely to be converted into croplands, croplands are more likely to be converted into grasslands, and construction lands are more likely to become unused lands. (4) Sustainable LULC management evaluations based on landscape indices reveal that ecological conservation and balanced development scenarios exhibit superior landscape connectivity and clustering. Thus, the balanced development scenario is the most appropriate LULC strategy for the Yuanmou dry-hot valley in the future. These findings provide scientific references for balancing ecological conservation and economic development in the arid river valleys of Southwest China.

Survey and Mapping Geographic Information Archive Informationization Management Construction Analysis

With the rapid development of science and technology and the rapid accumulation of geographic information data, the management of surveying and mapping geographic information archives is facing increasing challenges. The traditional manual management mode makes it difficult to meet the needs of large-scale data processing and sharing, so information management has become a key strategy to improve the efficiency of data management and optimize the use of resources. In this context, this paper discusses the construction of informatization management around surveying and mapping geographic information archives. The key steps in the construction of information management include the nodes of technical infrastructure, data standardization and organization, digital conversion of archives, archive retrieval and query system, security and authority management, and continuous updating and maintenance of archives. At the same time, to promote the construction of information management, work can be started from the formulation of a comprehensive information management plan, the establishment of cross-departmental collaboration mechanisms, the strengthening of personnel training and technical support, as well as the establishment of a data quality management system, to meet the needs of multiple fields and to realize the greater value of data.

Impacts of human activities and climate change on water and sediment evolution in four large subtropical river basins in China

Human activities and climate are two key factors affecting hydrological and soil erosion processes. Understanding their impacts on water discharge and sediment transport is very important for sustainable development of watersheds, particularly in subtropical regions with high precipitation and high sediment loads. We here compared the long-term dynamics of water discharge and sediment transport in four large contiguous watersheds in subtropical China and explored the importance of the main influencing factors including climate, nature endowment such as geology, and human activities. Significant differences have been observed between watersheds in terms of sediment and water discharge (p < 0.001). Pairwise comparison among the four basins demonstrated significant differences in sediment modulus among 5 of the 6 pairs (p < 0.05). The sediment modulus in the Lishui Basin was significantly higher than those in other basins, mainly due to the substantial presence of steep slopes in the mountainous region, which is prone to soil erosion. Temporally, sediment transport in the four basins was well synchronized showing significant decreasing trends with abrupt change points (p < 0.001). In contrast, no trends and abrupt change points were detected in water discharge, mainly influenced by precipitation. Human activities played a predominant role to the reduction of sediment transport (80% to 102%) compared with those of climate (-2% to 19%) across the four basins. Additionally, our study also showed land cover had various basin-independent impacts on the change of sediment transport. Through cross-basin comparisons of the long-term changes in water discharge and sediment transport, our study revealed the similarities and differences in their driving mechanisms, providing valuable information for land use planning and water resource management in large subtropical basins.

Analysis of Mandibular Muscle Variations Following Condylar Fractures: A Systematic Review.

The review was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. A search was performed on online databases using the keywords "masticatory muscles" AND ("mandibular fracture" OR "condylar fracture"). The eligibility criteria included clinical trials involving human intervention and focusing on muscle activity following a condylar fracture. A total of 13 relevant studies were reviewed. Various studies evaluated muscle activity using clinical evaluation, bite force measurement, electromyography (EMG), magnetic sensors and radiological examinations to assess the impact of mandibular fractures on masticatory muscles. Mandibular condylar fractures can lead to significant changes in muscle activity, affecting mastication and TMJ functioning. EMG and computed tomography (CT) imaging play crucial roles in assessing muscle changes and adaptations following fractures, providing valuable information for treatment planning and post-fracture management. Further research is required to explore long-term outcomes and functional performance after oral motor rehabilitation in patients with facial fractures. Standardized classifications and treatment approaches may help improve the comparability of future studies in this field.

Dynamic connectivity analyses to inform management of the invasive American mink and its native competitor, the European mink

Forecasting habitat suitability and connectivity can be central to both controlling range expansion of invasive species and promoting native species conservation, especially under changing climate conditions. This study aimed to identify and prioritize areas in Spain to control the expansion of one of the most harmful invasive species in Europe, the American mink, while conserving its counterpart, the endangered European mink, under current and future conditions. We used ensemble habitat suitability and dynamic connectivity models to predict species ranges and movement routes considering likely climate change under three emission scenarios. Then, using habitat availability metrics, we prioritized areas for invasive mink control and native mink conservation and classified them into different management zones that reflected the overlap between species and threat from American to European minks. Results suggest that both species are likely to experience declines in habitat and connectivity under climate change scenarios with significantly larger declines by the end of the century for European minks (72 and 80% respectively) than for American minks (41 and 32%). Priority areas for management of both species varied over time and across emission scenarios, with a general shift in priority habitat towards the North-East of the study area. Our findings demonstrate how habitat suitability and dynamic connectivity approaches can guide long-term management strategies to control invasive species and conserve native species while accounting for likely landscape changes. The simultaneous study of both invasive and native species can support prioritized management action and inform management planning of the intensity, extent, and techniques of intervention depending on the overlap between species.