Evaluating the robustness of nature-based solutions: future resilience of sedum-based soft capping as a conservation approach for heritage sites in Britain and Ireland DOI Creative Commons
Jenny Richards,

Elizabeth Cooke,

Martin A. Coombes

et al.

Physical Geography, Journal Year: 2023, Volume and Issue: 45(1), P. 20 - 38

Published: May 11, 2023

Nature-based solutions are seen to benefit both society and biodiversity. However, research into their future resilience is required. Soft capping a nature-based conservation strategy that mimics the natural colonisation of plants on top ruined walls reduces rates material deterioration. To remain effective, soft species must be tolerant climatic conditions. We use Maxent distribution model assess low high emission scenarios across Britain Ireland. mid- end-century presence probability four native archaeophyte used in (Sedum album, S. acre, anglicum Saxifraga granulata). Future probabilities were calculated using climate models HadGEM3-GC31-LL, IPSL-CM6A-LR MIROC6. Results suggest current sedum-based caps will viable until mid-century with additional maintenance (e.g. watering) during droughts, although predominantly formed Sedum album may prone failure south-eastern England. In future, more resilient arid conditions need preferentially selected for ensure under warming climate. Species modelling provides useful way predicting solutions.

Language: Английский

Linking relative suitability to probability of occurrence in presence‐only species distribution models: Implications for global change projections DOI Creative Commons
Jeffrey R. Smith, Jonathan M. Levine

Methods in Ecology and Evolution, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Abstract Our ecological understanding of how biodiversity will respond to global change is a large extent based on projections from presence‐only species distribution models. Despite the incredible utility these models, we know that predictions they generate can be heavily influenced by user decisions about model structure or parameter choices. Here, test function used convert relative suitability probably occurrence in distributions models affect both magnitude and location change. We MaxEnt create maps for 354 avian under current climate conditions year 1981. In back‐casting analysis tested well three functions relating perform recovering observed changes range size: (1) logistic curve with informed, species‐specific, prevalence values, (2) default curve, (3) commonly statistical threshold. then quantified implications species' future shifts found using either common threshold habitat tends estimate larger effects past size than time‐series data, inflate much impact potentially misidentify locations greatest expansion contraction. further provide mathematical basis biases, suggesting their general applicability other systems. Last, show biases avoided analysing proportional rather absolute change, abandoning use thresholds. Incorporating practices facilitate more predictive when forecasting response

Language: Английский

Citations

0
Climate change and geographical distribution projections for major leaf beetles (Coleoptera: Chrysomelidae) in Saudi Arabia DOI
Mahmoud S. Abdel-Dayem, Hathal M. Al Dhafer, Ahmed M. Soliman

et al.

Journal of Economic Entomology, Journal Year: 2025, Volume and Issue: unknown

Published: March 4, 2025

Climate change has a substantial impact on the quality and diversity of insect pests, which may have adverse ecological economic effects. The family Chrysomelidae represents one most economically ecologically important groups within Coleoptera, with species acting as agricultural pests contributing substantially to biodiversity in arid regions. Based bioclimatic, topographic, vegetation data, current future distributions 4 chrysomelids (Caryedon acaciae (Gyllenhal, 1833), Chaetocnema pulla Chapuis, 1879, Phyllotreta cheiranthi Weise, 1903, Spermophagus sericeus (Geoffroy, 1785)) Saudi Arabia were predicted using MaxEnt modeling for 2050 under 2 Shared Socioeconomic Pathways (SSPs), SSP126 (low emission) SSP585 (high scenarios. leaf beetle models showed strong performance, average area curve (AUC) values ranging from 0.86 0.96 TSS 0.52 0.65. Five predictors chosen each 21 environmental variables. results show that key factors influence varied, being influential. According habitat suitability maps, future, such distribution will be severely altered, mostly by climate change. More precisely, C. face minor range shifts, while pulla, P. cheiranthi, S. expand their ranges substantially, especially Eastern Province. Our confirm importance implementing adaptive pest-management strategies address potential expansions various could intensify local challenges pose heightened threat systems.

Language: Английский

Citations

0
Comparative Analysis of MaxEnt and Deep Learning Approaches for Modeling Humpback Whale Distribution in North Iceland DOI Creative Commons

Nils Barthel,

Charla J. Basran,

Marianne Rasmussen

et al.

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(3)

Published: March 1, 2025

In this study, we compared the established MaxEnt and a more novel deep learning approach for modeling distribution of humpback whales (Megaptera novaeangliae) in north Iceland. We examined mechanisms, structures, optimization techniques both approaches, highlighting their differences similarities. Monthly models Skjálfandi Bay were created, from 2018 until 2021, using presence-only sighting data satellite remote sensing data. Search efforts boat tracklines utilized to create pseudo-absence points models. Additionally, trained used projections year 2022, solely based on available environmental results area under curve value. The findings indicate that approaches have limitations advantages. does not allow continuous updating within time series, yet it mitigates risk overfitting by employing maximum entropy principle. model is likely overfit, but larger weight network increases model's capability capture complex relationships patterns. Ultimately, show had higher predictive performance current future whale distributions. Both inherent limitations, such as low resolution input data, spatial biases, inability fully entire complexity natural processes. Despite this, showed promising prompts further research different study areas applications other mobile animal species.

Language: Английский

Citations

0
Potential Distribution of Fusarium Head Blight Under Climate Change Scenarios in Iran DOI
Farid Houshyar,

Behnam Pouzeshimiyab,

Sevil Nematollahi

et al.

Journal of Phytopathology, Journal Year: 2025, Volume and Issue: 173(2)

Published: March 1, 2025

ABSTRACT Climate change is predicted to impact crop production and food security, with increased risks of pest infestations failures. Using proximal climate variables maximum entropy (MaxEnt) model, this research predicts the current future potential distribution Fusarium Head Blight (FHB), a significant disease affecting wheat barley. The analysis considered two Change Shared Socioeconomic Pathways (SSPs) over distinct time periods across various agro‐ecological zones (AEZs) in Iran. results indicated that conditions for FHB includes temperature, precipitation minimum temperature March, contributing 47.85% ± 1.63%, 28.75% 3.20% 23.40% 1.56% its distribution, respectively. Currently, was predominantly present AEZs including North West, Caspian Coastal, Central Zagros Southern Zagros, which collectively account 49% Iran's national production. However, projections suggested shift these areas Central, Khorasan, Arid Coastal AEZs, currently contribute 36% This emphasises need effective management strategies mitigate impacts on agricultural crops Iran due shifting FHB.

Language: Английский

Citations

0
Modeling the effect of climate change on the distribution of plant communities in Zayandeh-Rud basin, Iran DOI

Mahbobeh Hadinejad,

Ali Asghar Naghipour, Ataollah Ebrahimi‬

et al.

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(4)

Published: March 27, 2025

Language: Английский

Citations

0
Ecological Features of the Range of Euphorbia pilosa (Euphorbiaceae) at the Northern Limits of Distribution in Western Siberia DOI
К. С. Байков, Elena Baikova

Contemporary Problems of Ecology, Journal Year: 2025, Volume and Issue: 18(1), P. 72 - 81

Published: Feb. 1, 2025

Language: Английский

Citations

0
Predicting the potential distribution of the Gila Monster and evaluating the extent of protected natural areas for conservation DOI

Carson S. Gehman,

C. M. Gienger

Journal for Nature Conservation, Journal Year: 2025, Volume and Issue: unknown, P. 126944 - 126944

Published: April 1, 2025

Language: Английский

Citations

0
High-resolution habitat suitability maps for all widespread Italian breeding bird species DOI Creative Commons
Mattia Brambilla, Luca Ilahiane, Enrico Caprio

et al.

Scientific Data, Journal Year: 2025, Volume and Issue: 12(1)

Published: April 19, 2025

Tackling the current global biodiversity crisis requires large-scale spatially accurate data to rapidly assess knowledge gaps and set conservation priorities. Obtaining such is often challenging because surveying across broad spatial scales massive logistical economic efforts. Here, we provide high-resolution (0.81 81 km2, depending on species ecology) habitat suitability raster maps for all 225 widespread breeding bird in Italy. Maps were generated by means of distribution models based ~2.5 million (≤1 km-scale) expert-validated occurrence records. Occurrence collected during seasons 2010-2016 over 3000 skilled observers, mostly through Ornitho.it web platform, with aim realizing second Atlas Breeding Birds Italy, released 2022. These will be useful ecologists, scientists practitioners investigating patterns avian diversity identifying We discuss potential applications this dataset inferring composition ecological communities distributions at Italian scale.

Language: Английский

Citations

0
Impacts of climate change on the distribution of riverine endemic fish species in Iran, a biodiversity hotspot region DOI
Toktam Makki, Hossein Mostafavi, M. Ali Akbar

et al.

Freshwater Biology, Journal Year: 2023, Volume and Issue: 68(6), P. 1007 - 1019

Published: April 2, 2023

Abstract Iran is one of the world's fish biodiversity hotspots. Most riverine species in this country are currently under threat by human activities. In addition to those threats, climate change expected alter rainfall and temperature regimes, imposing further limitations, particularly endemic fishes. Therefore, understanding how these respond an important issue conservation Iranian freshwater biodiversity. This study aimed predict potential distribution 16 two scenarios (i.e., RCP 4.5 8.5) river habitats 2050s 2080s. The analysis conducted using MaxEnt model. Seven environmental variables were used for modelling: maximum width, elevation, slope, basins occupied target species, average annual precipitation, mean temperature, difference between coldest hottest months year . validation model each showed that AUC (area ROC curve) scores range from 0.87 0.99. Under optimistic (RCP 4.5) pessimistic 2080s, will face four different outcomes their habitat range: reduction (three species), expansion (five (seven species) no (one species). It concluded most unique geographical area serious challenges change. Delineating changes can help prioritise measures valuable species. Considering our results, translocation new locations also should be investigated.

Language: Английский

Citations

10
Understanding the invasion potential of Chromolaena odorata and Lantana camara in the Western Ghats, India: An ecological niche modelling approach under current and future climatic scenarios DOI Creative Commons
Bodi Surya Pratap Chandra Kishore, Amit Kumar, Purabi Saikia

et al.

Ecological Informatics, Journal Year: 2023, Volume and Issue: 79, P. 102425 - 102425

Published: Dec. 12, 2023

Invasive species are the major cause of native biodiversity loss and extinction, which have predominantly affected one world's 'hottest hotspots' located in Western Ghats, India with varied intensity. Therefore, present study, an investigation has been undertaken to model potential habitat dominant invasive plant (IPSs) viz., Chromolaena odorata (L.) R.M.King & H.Rob. Lantana camara L. current future climate change scenarios by evaluating influence bioclimatic topographical variables using distribution modelling (SDM). The study exhibited large invasion proliferation C. (33.01%) (30.33%) especially Nilgiri Biosphere Reserve (NBR) under scenario. projections derived Shared Socioeconomic Pathways Climate Scenarios datasets (SSPs 126, 245, 370, 585) demonstrated a significant reduction (>5.48% WG), while surge (>5.83% WG) barring few exceptions. However, highlighted (45,262 sq. km; 31.33% SSP 126 (2021–40)) (33,844 23.43% 245 concentrations were observed NBR (L. camara: 5711 12.6%; odorata: 5090 15.04%) southern coasts. introduces comprehensive novel method leveraging SSPs identify hotspots invasions Indian tropical forests ecological niche modelling. These findings hold relevance for prompt actions management both regions susceptible invasions.

Language: Английский

Citations

9