Urban and Peri-Urban Tree Cover in European Cities: Current Distribution and Future Vulnerability Under Climate Change Scenarios

The coypu (Myocastor coypus) is a semi-aquatic rodent native to South America which has become invasive in Europe and other parts of the world. Although recently listed as species of European Union concern in the EU Invasive Alien Species Regulation, an analysis of the current European occurrence and of its potential current and future distribution was missing yet. We collected 24,232 coypu records (corresponding to 25,534 grid cells at 5 × 5 km) between 1980 and 2018 from a range of sources and 28 European countries and analysed them spatiotemporally, categorising them into persistence levels. Using logistic regression, we constructed consensus predictions across all persistence levels to depict the potential current distribution of the coypu in Europe and its change under four different climate scenarios for 2041–2060. From all presence grid cells, 45.5% showed at least early signs of establishment (records temporally covering a minimum of one generation length, i.e. 5 years), whereas 9.8% were considered as containing established populations (i.e. three generation lengths of continuous coverage). The mean temperature of the warmest quarter (bio10), mean diurnal temperature range (bio2) and the minimum temperature of the coldest month (bio6) were the most important of the analysed predictors. In total, 42.9% of the study area are classified as suitable under current climatic conditions, of which 72.6% are to current knowledge yet unoccupied; therefore, we show that the coypu has, by far, not yet reached all potentially suitable regions in Europe. Those cover most of temperate Europe (Atlantic, Continental and Pannonian biogeographic region), as well as the coastal regions of the Mediterranean and the Black Sea. A comparison of the suitable and occupied areas showed that none of the affected countries has reached saturation by now. Under climate change scenarios, suitable areas will slightly shift towards Northern regions, while a general decrease in suitability is predicted for Southern and Central Europe (overall decrease of suitable areas 2–8% depending on the scenario). Nevertheless, most regions that are currently suitable for coypus are likely to be so in the future. We highlight the need to further investigate upper temperature limits in order to properly interpret future climatic suitability for the coypu in Southern Europe. Based on our results, we identify regions that are most at risk for future invasions and provide management recommendations. We hope that this study will help to improve the allocation of efforts for future coypu research and contribute to harmonised management, which is essential to reduce negative impacts of the coypu and to prevent further spread in Europe.

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Socioeconomic Factors and Urban Tree Cover Policies in a Subtropical Urban Forest

GIScience & Remote Sensing ◽

10.2747/1548-1603.49.3.428 ◽

2012 ◽

Vol 49 (3) ◽

pp. 428-449 ◽

Cited By ~ 31

Author(s):

Zoltan Szantoi ◽

Francisco Escobedo ◽

John Wagner ◽

Joysee M. Rodriguez ◽

Scot Smith

Keyword(s):

Socioeconomic Factors ◽

Urban Forest ◽

Tree Cover ◽

Urban Tree ◽

Urban Tree Cover

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Characterizing spatial structure of urban tree cover (UTC) and impervious surface cover (ISC) density using remotely sensed data in Osmaniye, Turkey

SN Applied Sciences ◽

10.1007/s42452-020-2154-0 ◽

2020 ◽

Vol 2 (3) ◽

Author(s):

Murat Atasoy

Keyword(s):

Spatial Structure ◽

Impervious Surface ◽

Remotely Sensed ◽

Tree Cover ◽

Remotely Sensed Data ◽

Surface Cover ◽

Urban Tree ◽

Impervious Surface Cover ◽

Urban Tree Cover

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The current and future projected distribution of Solanum hoplopetalum (Solanaceae): an indigenous weed of the south-western Australian grain belt

Australian Journal of Botany ◽

10.1071/bt11242 ◽

2012 ◽

Vol 60 (2) ◽

pp. 128 ◽

Cited By ~ 4

Author(s):

Pippa J. Michael ◽

Paul B. Yeoh ◽

John K. Scott

Keyword(s):

Climate Change ◽

Current Distribution ◽

South Australia ◽

Climate Change Scenarios ◽

Management Options ◽

South Wales ◽

Major Factors ◽

Lower South ◽

Significant Match ◽

Western Australian

The factors determining the distribution of the Western Australian endemic Solanum hoplopetalum Bitter & Summerh. (Solanaceae) were assessed because it was identified as a potential weed risk to Australian cropping regions, including under climate change scenarios. Incubation at constant temperatures determined daily plant growth rates and plants required 1380 degree-days above a threshold of 12.4°C to complete growth to flowering. From this and published information on the plant’s biology, we developed a mechanistic niche model using CLIMEX. The model projection for current climates produced a highly significant match to known distribution records. Spatially, the lower south-west and areas eastwards to South Australia, western New South Wales and southern parts of the Northern Territory were climatically suitable for growth of S. hoplopetalum. However, by 2070 the area under risk decreases, with the projected distribution under climate change contracting southwards. We hypothesise that climatic extremes and edaphic factors, possibly high soil pH, may be major factors determining the current distribution of S. hoplopetalum. Containment on the southern edge of the current distribution, interstate quarantine and local eradication in new areas of invasion are recommended as management options to combat the potential for this native weed to spread.

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Modeling the current distribution suitability and future dynamics of Culicoides imicola under climate change scenarios

PeerJ ◽

10.7717/peerj.12308 ◽

2021 ◽

Vol 9 ◽

pp. e12308

Author(s):

Hongyan Gao ◽

Long Wang ◽

Jun Ma ◽

Xiang Gao ◽

Jianhua Xiao ◽

...

Keyword(s):

Climate Change ◽

Current Distribution ◽

Habitat Suitability ◽

Southern China ◽

Sub Saharan Africa ◽

Future Climate Change ◽

Climate Change Scenarios ◽

African Horse Sickness ◽

Vector Surveillance ◽

Culicoides Imicola

Background African horse sickness, a transboundary and non-contagious arboviral infectious disease of equids, has spread without any warning from sub-Saharan Africa towards the Southeast Asian countries in 2020. It is imperative to predict the global distribution of Culicoides imicola (C. imicola), which was the main vector of African horse sickness virus. Methods The occurrence records of C. imicola were mainly obtained from the published literature and the Global Biodiversity Information Facility database. The maximum entropy algorithm was used to model the current distribution suitability and future dynamics of C. imicola under climate change scenarios. Results The modeling results showed that the currently suitable habitats for C. imicola were distributed in most of the southern part areas of America, southwestern Europe, most of Africa, the coastal areas of the Middle East, almost all regions of South Asia, southern China, a few countries in Southeast Asia, and the whole Australia. Our model also revealed the important environmental variables on the distribution of C. imicola were temperature seasonality, precipitation of coldest quarter, and mean temperature of wettest quarter. Representative Concentration Pathways (RCPs) is an assumption of possible greenhouse gases emissions in the future. Under future climate change scenarios, the area of habitat suitability increased and decreased with time, and RCP 8.5 in the 2070s gave the worst prediction. Moreover, the habitat suitability of C. imicola will likely expand to higher latitudes. The prediction of this study is of strategic significance for vector surveillance and the prevention of vector-borne diseases.

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Mapping Urban Tree Cover Changes Using Object-Based Convolution Neural Network (OB-CNN)

Remote Sensing ◽

10.3390/rs12183017 ◽

2020 ◽

Vol 12 (18) ◽

pp. 3017

Author(s):

Shirisa Timilsina ◽

Jagannath Aryal ◽

Jamie B. Kirkpatrick

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Urban Trees ◽

Tree Cover ◽

Urban Tree ◽

Object Based ◽

Parcel Size ◽

Tree Coverage ◽

The Relationship ◽

Urban Tree Cover

Urban trees provide social, economic, environmental and ecosystem services benefits that improve the liveability of cities and contribute to individual and community wellbeing. There is thus a need for effective mapping, monitoring and maintenance of urban trees. Remote sensing technologies can effectively map and monitor urban tree coverage and changes over time as an efficient and low-cost alternative to field-based measurements, which are time consuming and costly. Automatic extraction of urban land cover features with high accuracy is a challenging task, and it demands object based artificial intelligence workflows for efficiency and thematic accuracy. The aim of this research is to effectively map urban tree cover changes and model the relationship of such changes with socioeconomic variables. The object-based convolutional neural network (CNN) method is illustrated by mapping urban tree cover changes between 2005 and 2015/16 using satellite, Google Earth imageries and Light Detection and Ranging (LiDAR) datasets. The training sample for CNN model was generated by Object Based Image Analysis (OBIA) using thresholds in a Canopy Height Model (CHM) and the Normalised Difference Vegetation Index (NDVI). The tree heatmap produced from the CNN model was further refined using OBIA. Tree cover loss, gain and persistence was extracted, and multiple regression analysis was applied to model the relationship with socioeconomic variables. The overall accuracy and kappa coefficient of tree cover extraction was 96% and 0.77 for 2005 images and 98% and 0.93 for 2015/16 images, indicating that the object-based CNN technique can be effectively implemented for urban tree coverage mapping and monitoring. There was a decline in tree coverage in all suburbs. Mean parcel size and median household income were significantly related to tree cover loss (R2 = 58.5%). Tree cover gain and persistence had positive relationship with tertiary education, parcel size and ownership change (gain: R2 = 67.8% and persistence: R2 = 75.3%). The research findings demonstrated that remote sensing data with intelligent processing can contribute to the development of policy input for management of tree coverage in cities.

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Geographic distribution of Desmodus rotundus in Mexico under current and future climate change scenarios: Implications for bovine paralytic rabies infection

Veterinaria México OA ◽

10.21753/vmoa.4.3.390 ◽

2017 ◽

Vol 4 (3) ◽

Cited By ~ 1

Author(s):

Heliot Zarza ◽

Enrique Martínez-Meyer ◽

Gerardo Suzán ◽

Gerardo Ceballos

Keyword(s):

Climate Change ◽

Geographic Distribution ◽

Current Distribution ◽

Climate Model ◽

Global Climate Model ◽

Future Climate ◽

Epidemiological Surveillance ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Desmodus Rotundus

Veterinaria México OA ISSN: 2448-6760Cite this as:Zarza H, Martínez-Meyer E, Suzán G, Ceballos G. Geographic distribution of Desmodus rotundus in Mexico under current and future climate change scenarios: Implications for bovine paralytic rabies infection. Veterinaria México OA. 2017;4(3). doi: 10.21753/vmoa.4.3.390.Climate change may modify the spatial distribution of reservoirs hosting emerging and reemerging zoonotic pathogens, and forecasting these changes is essential for developing prevention and adaptation strategies. The most important reservoir of bovine paralytic rabies in tropical countries, is the vampire bat (Desmodus rotundus). In Mexico, the cattle industry loses more than $2.6 million US dollar, annually to this infectious disease. Therefore, we predicted the change in the distribution of D. rotundus due to future climate change scenarios, and examined the likely effect that the change in its distribution will have on paralytic rabies infections in Mexico. We used the correlative maximum entropy based model algorithm to predict the potential distribution of D. rotundus. Consistent with the literature, our results showed that temperature was the variable most highly associated with the current distribution of vampire bats. The highest concentration of bovine rabies was in Central and Southeastern Mexico, regions that also have high cattle population densities. Furthermore, our climatic envelope models predicted that by 2050–2070, D. rotundus will lose 20 % of its current distribution while the northern and central regions of Mexico will become suitable habitats for D. rotundus. Together, our study provides an advanced notice of the likely change in spatial patterns of D. rotundus and bovine paralytic rabies, and presents an important tool for strengthening the National Epidemiological Surveillance System and Monitoring programmes, useful for establishing holistic, long-term strategies to control this disease in Mexico.Figure 4. Modelled suitability for future distribution of Desmodus rotundus according to Global Climate Model GFDL-CM3 for two time periods (2050 and 2070), and two Representative Concentration Pathways (RCP 4.5 and 8.5). Left-hand column shows suitability values, with blue indicating more suitable conditions.

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Prediction of the Suitable Area of the Chinese White Pines (Pinus subsect. Strobus) under Climate Changes and Implications for Their Conservation

Forests ◽

10.3390/f11090996 ◽

2020 ◽

Vol 11 (9) ◽

pp. 996

Author(s):

Lele Lin ◽

Jian He ◽

Lei Xie ◽

Guofa Cui

Keyword(s):

Climate Change ◽

Current Distribution ◽

Future Climate ◽

Ex Situ ◽

Future Climate Change ◽

Climate Change Scenarios ◽

White Pine ◽

Chinese White ◽

The Future ◽

Pine Species

White pines (Pinus subsect. Strobus) play important roles in forest ecosystems in the Northern Hemisphere. Species of this group are narrowly distributed or endangered in China. In this study, we used a species distribution model (SDM) to project and predict the distribution patterns of the 12 species of Chinese white pine under a variety of paleoclimatic and future climate change scenarios based on 39 high-resolution environmental variables and 1459 distribution records. We also computed the centroid shift, range expansion/contraction, and suitability change of the current distribution area to assess the potential risk to each species in the future. The modeling results revealed that the suitable habitat of each species is consistent with but slightly larger than its actual distribution range and that temperature, precipitation, and UV radiation are important determining factors for the distribution of different white pine species. The results indicate that the Last Glacial Maximum (LGM) greatly affected the current distribution of the Chinese white pine species. Additionally, it was predicted that under the future climate change scenarios, there will be a reduction in the area of habitats suitable for P. armandii, P. morrisonicola, and P. mastersiana. Furthermore, some of the current distribution sites of P. armandii, P. kwangtungensis, P. mastersiana, P. morrisonicola, P. sibirica, and P. wallichiana were predicted to become more unsuitable under these scenarios. These results indicate that some Chinese white pine species, such as P. armandii, P. morrisonicola, and P. mastersiana, may have a very high risk of population shrinkage in the future. Overall, this study provided relevant data for the long-term conservation (both in situ and ex situ) and sustainable management of Chinese white pine species.

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