Land Area Research Articles

The impact of tourist destinations on wildlife in northern Finland

ABSTRACT Increased tourism impact, recreational activities and structures in natural areas can affect wildlife by increasing urbanization, landscape fragmentation and disturbance. I examined the potential effects of tourist destinations on four forest grouse (Tetraoninae) and five mammalian species in northern Finland. I analyzed density data obtained from wildlife counts carried out by hunters around ten tourist destinations. The densities of mountain hare and mustelid species were negatively correlated with the distance to a tourist destination. The densities of adult grouse, juvenile grouse, mountain hare, and mustelids were positively correlated with the area of mixed forests surrounding the destinations. The densities of adult and juvenile grouse were positively correlated, while the densities of pine marten and mustelids were negatively correlated with the area of agricultural land surrounding the destinations. The densities of the studied wildlife species varied among destinations and years. It seems that current recreational activities have not caused significant changes in the occurrence and abundance of wildlife species in the surroundings of the tourist destinations studied. Location of a destination, predator densities, and landscape structure around the destination had the most impact on the density of wildlife species.

Analyzing the impacts of watershed management interventions and scenarios on sediment export reduction in yezat watershed, north west Ethiopia using InVEST model

ABSTRACT This study aimed at assessing the long term impacts of watershed management interventions and scenarios on sediment export reduction in the data-scarce region of the Yezat watershed in north-west Ethiopia. The modified ecosystem services valuation model (InVEST) was employed to evaluate the amount of sediment export in the watershed. Different watershed management intervention scenarios were applied to evaluate the effectiveness of watershed management interventions on sediment export reduction. The results of the study showed that the mean annual sediment yield was 35 tons ha yr in 20000, due to the expansion of cultivated land and built-up area. Conversely, it decreased from 35 ton ha yr in 2000 -18.4 ton ha yr in 2021 due to watershed management interventions. On the contrary, moderate, severe, and very severe categories of sediment export intensity were high in 2000. But it decreased in 2021 due to watershed management interventions. The mean annual sediment export in the baseline scenario (BS) was 35 tons per year, which was reduced to 13.39 tons per year, 3.46 tons per year, and 1.17 tons per year in the reforestation scenario, soil/stone bund, and integrated scenarios, respectively. The result revealed that areas covered by high sediment severity classes were reduced.

Insights Into Urban Heat Island and Heat Waves Synergies Revealed by a Land‐Surface‐Physics‐Based Downscaling Method

AbstractResearchers have recently focused on the interplay of the urban heat island (UHI) effect and heat waves (HWs). However, the synergies of these two phenomena remains inconclusive at present. To address this gap, this study investigated UHIs and HWs synergies during the last 30 years in the Tokyo metropolitan area, through a unique and novel approach named Land‐Surface‐Physics‐Based Downscaling (LSP‐DS). LSP‐DS integrates the widely used Noah‐Multiparameterization (Noah‐MP) land‐surface model coupled with urban canopy‐process physics, aiming to conduct high‐resolution, long‐term urban‐specific simulations with much less computational resources. Our comprehensive analysis combining observation data and numerous LSP‐DS simulations confirms exacerbated UHIs during HWs. Specifically, HWs amplify the temperature differences between urban and rural environments, which is quantified by UHI intensity (UHII). During HWs, UHII increased more at night in inland areas and more during daytime in coastal areas. HWs present especially a heightened threat to coastal regions where daytime UHII increased by approximately 1°C during HWs. The Bowen ratio can explain the increase in the daytime UHII, and the daytime accumulated storage heat increase during HWs can explain the increase in nighttime UHII. Based on future projections of the increasing frequency of high temperatures, our findings highlight the impending heat‐related health challenges faced by urban residents.

Achieving higher grain yield in hybrid rice through the promotion of individual growth and development

AbstractEnsuring rice (Oryza sativa) self‐sufficiency in China relies significantly on achieving high grain yields in hybrid rice production. This study conducted field experiments across two site‐years, comparing grain yield per unit of land area, grain yield generated per seedling, and associated yield traits for a hybrid rice variety under two combinations of hill spacing and the number of seedlings per hill. The combinations included a hill spacing of 30 cm × 14 cm with one seedling per hill (H14S1) and a hill spacing of 30 cm × 24 cm with three seedlings per hill (H24S3). The results revealed that H14S1 consistently outperformed H24S3, demonstrating a 7%–16% increase in grain yield per unit of land area and an impressive 88%–104% higher grain yield generated per seedling. H14S1 exhibited 56%–77% more panicles formed per seedling and 10%–15% more spikelets per panicle compared to H24S3. H14S1 produced 78%–115% higher biomass at heading and maturity per seedling and 8%–25% higher biomass at heading and maturity per tiller than H24S3. This study underscores the importance of promoting the individual growth and development of seedlings as a crucial strategy for achieving higher grain yield in hybrid rice production.

Analisis Pengaruh Produksi dan Luas Lahan Kelapa Sawit terhadap PDRB Sektor Pertanian: Pendekatan Regresi Linier Berganda menggunakan Data Sekunder 2013-2022

The issue in this research is that the increase and decrease of agricultural GDP per capita in Southeast Sulawesi are significantly influenced by several factors, one of which is the production factor and the availability of land for oil palm cultivation. Therefore, an analysis is needed regarding the impact of GDP on the production and land area of oil palm in Southeast Sulawesi. This study aims to understand the impact of oil palm production and cultivated area on the Gross Regional Domestic Product (GRDP) of the agricultural sector in Southeast Sulawesi Province. The sample for this study uses secondary data derived from the Southeast Sulawesi Provincial Statistics Agency and the Indonesian Palm Oil Statistics Book from 2013 to 2022. This research is analyzed using multiple linear regression methods with IBM SPSS Statistics 25 software. The results of this study indicate that oil palm production in the Southeast Sulawesi region has a negative and significant effect on the agricultural GRDP of Southeast Sulawesi, while the expansion of oil palm plantation area has a positive and significant effect on the agricultural sector GRDP in Southeast Sulawesi Province.

Defoliator outbreaks track with warming across the Pacific coastal temperate rainforest of North America

The biogeography of irruptive insect herbivores is determined by host availability and climate conditions. As such, outbreak distributions are sensitive to climatic change, especially across large latitudinal gradients. Here, we investigate the outbreak distributions of two understudied defoliators, hemlock sawfly Neodiprion tsugae (Hymenoptera) and western blackheaded budworm Acleris gloverana (Lepidoptera), that have both recently impacted the greatest land area recorded across the Pacific coastal temperate rainforest since the establishment of aerial survey programs. We compiled polygon‐based estimates of insect damage collected by aerial observers, forest inventory, and downscaled climatic data to develop gridded estimates of bioclimatic conditions across the extent of the Pacific coastal temperate rainforest, including the continental United States, British Columbia and Alaska. We leveraged these data to develop ensemble machine learning models with the goal of predicting the outbreak distribution of each insect. In this manuscript we: 1) describe the historical patterns of defoliator outbreaks, 2) identify and describe climatic conditions associated with outbreaks in both species and 3) assess whether historic outbreaks have tracked geographic shifts in climate conditions across the region. We demonstrate that outbreaks of hemlock sawfly and western blackheaded budworm have been observed across the Pacific coastal temperature rainforests of North America in each decade since the establishment of the Canadian and United States aerial survey programs. The distribution of outbreaks by both insects were best explained by host availability, a limited range of spring, summer, and winter temperatures, and minimum precipitation. Finally, we demonstrate that outbreaks have tracked the poleward shift in suitable climate over the last century. This study establishes a baseline understanding of the climatic constraints and biogeographic patterns of historic sawfly and budworm outbreaks across the Pacific coastal temperate rainforest and emphasizes the overarching importance of climate in driving the irruptive dynamics of these defoliator species.Keywords: climate envelope, defoliators, hemlock sawfly, Pacific coastal temperate rainforest, population dynamics, western blackheaded budworm

The potential of agroforestry to buffer climate change impacts on suitability of coffee and banana in Uganda

AbstractCoffee, an important global commodity, is threatened by climate change. Agroforestry has been considered as one option to maintain or enhance coffee production. In this study, we use a machine learning ensemble consisting of MaxEnt, Random Forest and Boosted Regression Trees to assess climate change impacts on the suitability to grow Arabica coffee, Robusta coffee and bananas in Uganda by 2050. Based on this, the buffering potential of Cordia africana and Ficus natalensis, the two commonly used shading trees in agroforestry systems is assessed. Our robust models (AUC of 0.7–0.9) indicate temperature-related variables as relevant for Arabica coffee suitability, while precipitation-related variables determine Robusta coffee and banana suitability. Under current climatic conditions, only a quarter of the total land area is suitable for growing Arabica coffee, while over three-quarters are suitable for Robusta coffee and bananas. Our results suggest that climate change will reduce the area suitable to grow Arabica coffee, Robusta coffee and bananas by 20%, 9% and 3.5%, respectively, under SSP3-RCP7.0 by 2050. A shift in areas suitable for Arabica coffee to highlands might occur, leading to potential encroachment on protected areas. In our model, implementing agroforestry with up to 50% shading could partially offset suitable area losses for Robusta coffee—but not for Arabica coffee. The potential to produce valuable Arabica coffee thus decreases under climate change and cannot be averted by agroforestry. We conclude that the implementation and design of agroforestry must be based on species, elevation, and regional climate projections to avoid maladaptation.

Onverwacht Group, Barberton Greenstone Belt, South Africa: 300 m.y. development of a Paleoarchean stagnant lid

The 3.55−3.26 Ga Onverwacht Group, Barberton Greenstone Belt, South Africa and Eswatini, records nearly 300 m.y. of Paleoarchean history dominated by basaltic, komatiitic, and felsic volcanism. It provides the oldest well-preserved record of crustal development and the nature and evolution of associated surface environments, ocean, atmosphere, and biosphere on early Earth. Sedimentary layers within this 10- to 12-km-thick sequence represent a range of proximal to distal sedimentary environments relative to the centers of volcanism. Proximal deposits include coarse felsic breccias, conglomerates, and sandstones and mafic to komatiitic lapillistones that often show evidence for deposition in relatively shallow water. Distal deposits are composed of fine pyroclastic debris, chemical sediments, and biogenic materials deposited under subaqueous conditions during local volcanic quiescence. They show abundant current-produced features and are interpreted to have formed at water depths of a few hundred meters or less under the influence of tidal and/or ocean-circulation currents. Terrigenous clastic sediments formed by the weathering and erosion of older rocks are essentially absent. The Onverwacht Group was deposited under marine conditions on what appears to have been a water world with little evidence of large land areas and no evidence of active tectonism. It is interpreted to represent the upper part of a Paleoarchean stagnant lid overlying but decoupled from an active mantle. The Barberton Greenstone Belt and other Paleoarchean terranes offer a view of this lid over the past 300 m.y. of its development and during the early stages of its fragmentation and disruption.

Landscape Dynamics of the Mu Us Sandy Land Based on Multi-Source Remote Sensing Images

This study meticulously investigates landscape alterations within the Mu Us Sandy Land, a critical region for desertification control in China. The research dissects the dynamic characteristics and inter-conversion of landscape elements across eleven distinct periods by employing multi-source remote sensing imagery spanning 1963 to 2020, alongside visual interpretation, random forest classification, and the desertification difference index (DDI). The analysis uncovers significant landscape transformations within the Mu Us Sandy Land over the past six decades, following a precise chronological sequence. A pivotal shift occurred around 1986, characterized by opposing trends within fixed and shifting sandy land. The earlier stage (pre-1986) witnessed a substantial decrease (66.9%) in the fixed sandy land area, accompanied by a corresponding rise (38.7%) in shifting sandy land. Conversely, the later stage (post-1986) era exhibited a remarkable increase (309.7%) in fixed sandy land, alongside a significant decline (78.9%) in shifting sand land coverage. This study identifies two stages of landscape transformation: a pre-1986 phase dominated by the conversion of fixed sandy land to semi-fixed sandy land and a post-1986 reversal toward shifting sand land into fixed sandy land. These sequential transformations have shaped the landscape pattern alterations observed in the Mu Us Sandy Land since 1963. The dramatic landscape improvements observed after 1986 can be primarily attributed to the implementation and continued investment in large-scale ecological restoration projects. This study’s findings, which reveal the intricate landscape dynamics and their implications for ecosystem management, provide a scientific foundation for refining and formulating comprehensive strategies to control desertification and manage the Mu Us Sandy Land’s unique ecosystem.

Food Sovereignty in Nepal : A Current Appraisal

Food sovereignty issue is integrated with agro ecology, climate and environmental justice, right of food workers, agrarian reform and justice to women and peasants. Despite of the promises of food security by the use of new practices and technologies global hunger has significantly increased. Industrial food production and indiscriminant use of chemical fertilizers pesticides have caused air, water and soil pollution and consequently environment and human health has been seriously impaired. Nepal being a developing economy could hardly endow all her possible resources just to address food security issue, hence the food sovereignty issue remained veiled till 2075B.S. Present study aims to enquire the working status of food sovereignty principal on real grounds in the country. The study is based on secondary data and is quantitative in nature. As pre design it is descriptive and prescriptive both. The study examines efficacy of food sovereignty principal on six pillar of it which are: focus on food for people; Value food providers; localize food system; puts control locally; builds knowledge and skills and work with nature. Examining through facts and figures, it is found that there is food crisis in the country with its quantity and nutritive value. The extended net works of cooperative throughout the country may play significant role in activating food sovereignty principals. Existences of middle man, poorer financial assistance, poorer insurance coverage, limitation of minimum price support policy to fewer crops are some of the major problems. In addition land fragmentation, diminishing wet and dry land area are additional bottlenecks. Indiscriminant use of chemical fertilizers and pesticides pose a crucial problem to practice organic farming. Activities as river bed farming, tharu alu cultivation, Jhol mal preparation, kitchen gardening, community seed bank and use of local biochar are working well with positive outcomes to support food sovereignty efforts.

Insights into Global Visibility Patterns: Spatiotemporal Distributions Revealed by Satellite Remote Sensing

Accurate measurement of surface visibility is vital for transportation. Satellite remote sensing technology offers the advantage of monitoring vast areas over extended time periods, providing a novel approach to visibility monitoring. However, it currently lacks the capability to directly measure visibility, necessitating further theoretical exploration of visibility remote sensing methods. In this study, we introduced an innovative model for remote retrieval of global surface visibility. It leverages the Extreme Random Forest (ERF) model to optimize the residual components of the physical method. The proposed model comprehensively explores the intricate relationship among surface visibility, aerosol optical depth (AOD), atmospheric extinction coefficient, and aerosol heights. Utilizing surface visibility data collected from global ground-based meteorological stations in 2018, we assessed the performance of the proposed model through 10-fold cross-validation, yielding correlation coefficient (R) of 0.85, root mean square error (RMSE) of 2.7 km, and mean absolute error (MAE) of 1.6 km. Results from temporal and site cross-validation further confirm the model's strong performance in both time and spatial domains. Additionally, this study has developed a global visibility dataset at a daily resolution of 0.1°×0.1°. Temporal analysis of this dataset reveals that visibility values are higher from June to October, while values are lower in other months. Regarding the spatial distribution of visibility, oceanic areas exhibit markedly superior visibility compared to land areas. Additionally, Oceania, South Africa, and South America boast notably better visibility than other regions.

Análisis de la sostenibilidad en los sistemas de producción ovina en el Altiplano de Michoacán

The sustainability of sheep production systems may be at risk and must be evaluated in order to identify actions to improve their performance. Therefore, the objective of this research was to evaluate the sustainability of sheep production units in the highlands area of the state of Michoacán, Mexico. The method of sustainability indicators of agricultural holdings was used, through the scales: agroecological, socio-territorial and economic. 40 indicators were evaluated through a semi-structured survey in 108 production units. The indicators of each sheep production unit were concentrated in a database and scores were obtained according to the method guide. In order to group sheep production units with similar characteristics, a multivariate cluster analysis was carried out using the hierarchical method. Significant differences (p ≤ 0.05) were found in the three scales evaluated with: 42.3; 47.7 and 50.0% sustainability units respectively. The main limitation of sustainability was the agroecological scale, in the space organization component. Four clusters of sheep production units with different characteristics were obtained. The sheep production units in the area have not reached a state of acceptable sustainability. The limited land area puts its permanence at risk. These production units manage to generate economic resources and support family self-sufficiency, which has allowed them to remain over time, due to the diversity of the agricultural species they manage.

Comparative Analysis of Multiple – Linear Regression Algorithm with Random Forest Regression for Prediction of House Plot Prices

Humans basically have a basic need to have a place to live, which can be a house or shelter. Along with the rapid population growth in Indonesia, which continues to increase every year, many people do not have or have a decent place to live. Therefore, careful planning is needed so that every family can have a decent home. One very important aspect in planning investment in the form of property is predicting future house prices. One approach that can be used is to use a Random Forest and Multiple Linear Regression algorithm, which is an algorithm from Machine Learning. There are several factors that can influence the price of a house, including land area, building area, number of bedrooms, bathrooms and garage. In this research, multiple linear regression and random forest regression methods were chosen. The aim of this research is to find the best prediction results between the two methods. To achieve accurate predictions, research was carried out repeatedly by dividing the dataset into 80% for training and 20% for testing. The research results show that the random forest regression algorithm provides the best results, with an accuracy of 81.6%.

Analisis Pengaruh Curah Hujan terhadap Frekuensi Kejadian Banjir di Kabupaten Kotabaru, Kalimantan Selatan

The accumulation of water on the ground is what causes flooding, whereas rainfall is the amount of rainwater collected in a flat area Rainfall and flooding are two related but distinct concepts. While rainfall refers to the amount of precipitation that falls in a particular area, flooding is the result of excessive water accumulation on the ground. Indonesia can be classified as a country with high rainfall due to its average annual rainfall ranging from 2000 to 3000 millimeters. In cases of heavy rainfall, excessive water discharge can occur. This can result in flooding when the land, rivers, or water reservoirs cannot manage the overflow effectively. Flooding is a common occurrence in Kotabaru Regency located in South Kalimantan, as it is a combination of mountainous regions, coastal areas, land areas, and small islands. The objective of the study is to examine whether flooding is always caused by high rainfall in Kotabaru Regency from January 2018 to December 2022. The correlation analysis is part of the research design, which utilizes secondary data collected and analyzed in Microsoft Excel. The findings suggest that moderate intensity rainfall is responsible for 73.3% of floods that occurred between 2018-2022. Moreover, 26.7% of floods occurred when rainfall is less than 20 mm/day. However, other factors such as monsoons, tropical cyclones, and El-Nino Southern Oscillation (ENSO) can affect the variability of rainfall and inffluence the occurrence of flood in the area.

Economic Factors Affecting Corn Commodity Switching (Zea Mays) To California Papaya Commodity (Carica Papaya L.) In South Oku District

Current conditions in South Ogan Komeroing Ulu Regency, generally California papaya farming income is greater than corn farming income. This is influenced by several economic factors. Therefore, the purpose of this study was to analyze the economic factors affecting the transfer of corn commodity (zea mays) to California papaya commodity (carica papaya l.) in South OKU District. This research was conducted in South OKU District, Muaradua Subdistrict and Buay Rawan Subdistrict. Determination of the location was carried out intentionally (Purposive). The sampling method used was the multistage sampling method. Multistage sampling with a total sample size of 60 samples. The research method used in this research is the survey method. This data processing method used is the logit regression analysis method. Based on the research that has been done, it is concluded that the economic factors that influence land conversion from corn commodity to California papaya in South OKU Regency are independent variables, namely price, farming costs, farming experience, land area and income have a significant effect on consumer decisions.

The attribution of February extremes over North America: A forecast-based storyline study

Abstract The importance of extreme event attribution rises as climate change causes severe damage to populations resulting from unprecedented events. In February 2019, a planetary wave shifted along the U.S.-Canadian border, simultaneously leading to troughing with anomalous cold events and ridging over Alaska and northern Canada with abnormal warm events. Also, a dry-stabilized anticyclonic circulation over low latitudes induced warm extreme events over Mexico and U.S. Florida. Most attribution studies compare the climate model simulations under natural or actual forcing conditions and assess probabilistically from a climatological point of view. However, in this study, we use multiple ensembles from an operational forecast model, promising statistical as well as dynamically constrained attribution assessment, often referred to as the storyline approach to extreme event attribution. In the globally averaged results, increasing CO2 concentrations lead to distinct warming signals at the surface, resulting mainly from diabatic heating. Our study finds that CO2-induced warming eventually affects the possibility of extreme events in North America, quantifying the impact of anthropogenic forcing over less than a week’s forecast simulation. Our study assesses the validity of the storyline approach conditional on the forecast lead times, which is hindered by rising noise in CO2 signals and the declining performance of the forecast model. The forecast-based storyline approach is valid for at least half of the land area within a six-day lead time before the target extreme occurrence. Our attribution results highlight the importance of achieving net-zero emissions ahead of schedule to reduce the occurrence of severe heatwaves.

Improving Soil Quality and Yield of Intercropping-System Crops in a Dry Land Area through Plant Growth Promoting Rhizobacteria Application Frequency

The future of agriculture is prone to choose technology that can enhance the quality of the resources to support the sustainability of food production. Plant Growth Promoting Rhizobacteria (PGPR) is a reliable technology for future agriculture as it is environment-friendly, and able to optimize resource utilization and decrease external input. This research aimed to analyze the effect of PGPR (Pseudomonas fluorescens + Bacillus polymyxa) application frequency on chemical soil properties, a yield of an intercropping system in dry land, the in-between correlation of the parameters, and to determine the best PGPR application frequency. Randomized Complete Block Design (RCBD) was used in this research to put the treatment in the experimental unit properly. The treatments consisted of i) one-time application of PGPR at the planting time, ii) twice application of PGPR at the planting time and 15 Days After Planting (DAP), iii) three times application of PGPR at the planting time, 15 DAP and 30 DAP, iv) without application of PGPR as control. The results showed that PGPR application frequency improved chemical soil properties, yield, and total by-products as livestock feed. The activity of soil enzymes, nitrogenase, and phosphatase, was enhanced compared to the control. The application of PGPR in dryland areas is recommended to maintain soil fertility and support sustainable intercropping crop production. Further studies are needed to conduct mixed farming between agriculture, animal husbandry, clean energy (biogas), and organic fertilizer (residue from the biogas digester).

Performance of kharif maize under conservation tillage in silty clay loam soil

Maize is a major staple food as well as potential cash crop for millions of people, mostly grown in the winter season in Bangladesh under conventional tillage practice. But huge area of cultivable land remains fallow in kharif-1 season in Sylhet region as well as other parts of Bangladesh. Hence, we aimed to identify the best variety and tillage method to grow maize in silty clay loam soil in kharif season. An experiment was conducted to study the performance of six maize varieties in the Kharif-I season (summer) under three tillage methods in silty clay loam soil of Eastern Surma-Kushiyara floodplain (AEZ-20). The experiment was arranged in RCBD with three replications to observe yield contributing traits and yield performance of maize. Among the varieties, BARI Hybrid Maize-16 showed the highest yield attributes and grain yield followed by BARI Hybrid Maize-13 and BARI Hybrid Maize-9. Based on tillage, the maximum number of leaves per plant, cob length and diameter, kernel rows per cob, kernels per row, kernels per cob, highest grain yield, and stover yields were recorded in conventional tillage. Therefore, considering the yield and tillage methods, BARI Hybrid Maize-16 showed the best yield performance under conventional tillage in the kharif-I season in silty clay loam soil of Eastern Surma-Kushiyara floodplain of Bangladesh.

A scalable big data approach for remotely tracking rangeland conditions

Rangelands, covering half of the global land area, are critically degraded by unsustainable use and climate change. Despite their extensive presence, global assessments of rangeland condition and sustainability are limited. Here we introduce a novel analytical approach that combines satellite big data and statistical modeling to quantify the likelihood of changes in rangeland conditions. These probabilities are then used to assess the effectiveness of management interventions targeting rangeland sustainability. This approach holds global potential, as demonstrated in Mongolia, where the shift to a capitalist economy has led to increased livestock numbers and grazing intensity. From 1986 to 2020, heavy grazing caused a marked decline in Mongolia’s rangeland condition. Our evaluation of diverse management strategies, corroborated by local ground observations, further substantiates our approach. Leveraging globally available yet locally detailed satellite data, our proposed condition tracking approach provides a rapid, cost-effective tool for sustainable rangeland management.

Dynamics of dispersal: Modeling the impact of dandelion proliferation on environmental and economic equilibria

Dandelion, with its unique wind dispersal mechanism, can easily spread its seeds across vast land areas, encroaching on territories of other creatures. To address this issue, two models are considered: The first model considers wind patterns, temperature, and moisture in dandelion growth, using differential equations to analyze population changes over time. Sensitivity analysis reveals the models responsiveness to these factors. The second model combines ecological and economic factors to assess the impact of invasive species, employing fuzzy mathematics to determine the severity of impact. The study identifies Canada Goldenrod as particularly destructive. These models offer insights for future invasive species management policies, showcasing innovations in incorporating partial differential functions and fuzzy mathematics for more accurate estimations.