scholarly journals Modelação espacial da adequabilidade de habitat a espécies invasoras: o Carpobrotus Edulis em terreno não dunar

Finisterra ◽  
2012 ◽  
Vol 43 (86) ◽  
Author(s):  
César Capinha
Keyword(s):  
Native Species ◽  
Threshold Model ◽  
Model Performance ◽  
Binary Logistic Regression ◽  
Carpobrotus Edulis ◽  
Modelling Framework ◽  
Exotic Invasive Species ◽  
Presence Data ◽  
Probability Threshold ◽  
Alien Invader

The use of habitat modelling for exotic invasive species can be extremely useful for identifying their potential impacts and for assisting in the design of eradication strategies. Even though the latter builds on theoretical assumptions that are quite different from those involved in the modelling of the habitat of native species, these two modelling methods are in fact quite similar. This article presents a habitat suitability modelling framework for Carpobrotus edulis, an alien invader plant in Serra do Bouro, Portugal. Several land surveys have been carried out in the study area in order to record the presence of this plant. The criteria for recording a presence were that the plant did not show any signs of weakness and that there were mat formations covering at least 5m2. Pseudo-absences were also obtained in a completely random way. The model was calibrated using a binary logistic regression. The performance of this model usually considered superior to that of models that rely on presence data only. Additionally, an evaluation technique based on the minimum area of higher adequacy is also presented. This technique assumes that, for a given probability threshold, model performance is higher whenever it has the same number of correct presences for a smaller predicted area. Using a 0.7 probability threshold, the model correctly predicted 80% of the total presences using only 8% of the study area. The model suggests that the main factor contributing to the expansion of Carpobrotus edulis has been the abandonment of agriculture in the study area. In addition, proximity to the shoreline and above-average erosion potential in the study area both seem to benefit the plant’s expansion. Conversely, steeper and longer slopes, and greater distances from the shoreline, were found to be significant contributors to the plant’s absence.

Prediction of daily lightning- and human-caused fires in British Columbia

2012 ◽  
Vol 21 (4) ◽  
pp. 342 ◽  
Author(s):  
S. Magnussen ◽  
S. W. Taylor
Keyword(s):  
British Columbia ◽  
Forest Cover ◽  
Atmospheric Stability ◽  
Model Performance ◽  
Binary Logistic Regression ◽  
Fire Weather Index ◽  
Explanatory Variables ◽  
Daily Number ◽  
Modelling Framework ◽  
Model Predictions

Daily records of the location and timing of human- and lightning-caused fires in British Columbia from 1981 to 2000 were used to estimate the probability of fire occurrence within 950 20 × 20-km spatial units (~950 000 km2) using a binary logistic regression modelling framework. Explanatory variables included lightning strikes, forest cover, surface weather observations, atmospheric stability indices and fuel moisture codes of the Canadian Fire Weather Index System. Because the influence of the explanatory variables in the models varied from year to year, model coefficients were estimated for each year. The arithmetic mean of the model coefficients was used for making daily predictions in a future year. A confidence interval around the mean or a quantile was derived from the ensemble of 20 model predictions. A leave-1-year-out cross-validation procedure was used to assess model performance for random years. The daily number of lightning-caused fires was reasonably well predicted at the provincial level (R = 0.83) and slightly less well predicted for a smaller (75 000 km2) administrative region. The daily number of human-caused fires was less well predicted at both the provincial (R = 0.55) and the regional level. The ability to estimate confidence intervals from the ensemble of model predictions is an advantage of the year-specific approach.

scholarly journals Implementing Target 10 of the Global Strategy for Plant Conservation at the National Botanic Gardens of Ireland

2013 ◽  
pp. 125-142
Author(s):  
Noeleen Smyth
Keyword(s):  
Native Species ◽  
Biological Diversity ◽  
Plant Conservation ◽  
Global Strategy ◽  
Convention On Biological Diversity ◽  
Effective Control ◽  
Botanic Gardens ◽  
Early Introduction ◽  
Carpobrotus Edulis ◽  
Chemical Treatments

The importance of managing invasive non-native species (INNS), be it through eradication or limitation, is set out in the United Nations Convention on Biological Diversity (CBD) which states that parties to the Convention should ‘prevent, control or eradicate alien species’ (IUCN, 2000). Unfortunately there is some evidence that botanic gardens have been implicated in being responsible for the early introduction of many environmental weeds listed by IUCN as among the worst invasive species (Hulme, 2011). Stronger global networking between botanic gardens to tackle the problem of INNS has been suggested by Hulme. Botanic gardens have a remit to meet Target 10 of the Global Strategy for Plant Conservation (GSPC) and the European Strategy for Plant Conservation (ESPC) Targets 10.1 and 10.2. The National Botanic Gardens, Glasnevin, in conjunction with University College Dublin and Mayo and Fingal County Councils, with grant funding from the Heritage Council, has monitored populations then researched and implemented effective control methods of two escaped garden plants: Hottentot fig (Carpobrotus edulis (L.) N.E. Br.) and giant rhubarb (Gunnera tinctoria (Molina) Mirb.) in EU protected habitats and in Special Areas of Conservation (SACs) in Ireland. Chemical treatments were trialled and tested in the field for both species, and successful regeneration of native vegetation in formerly invaded areas has been observed since treatments began in 2009.

scholarly journals Modelling of hardfacing layers deposition parameters using robust machine learning algorithms

2021 ◽  
Vol 2130 (1) ◽  
pp. 012016
Author(s):  
K Zając ◽  
K Płatek ◽  
P Biskup ◽  
L Łatka
Keyword(s):  
Gas Metal Arc Welding ◽  
Model Performance ◽  
Base Material ◽  
Neural Model ◽  
Machine Learning Algorithms ◽  
Influence Of Process Parameters ◽  
Generic Structure ◽  
Modelling Framework ◽  
Metal Arc Welding ◽  
Welding Processes

Abstract The study presents a data-driven framework for modelling parameters of hardfacing deposits by GMAW using neural models to estimate the influence of process parameters without the need of creating experimental samples of the material and detailed measurements. The process of GAS Metal Arc Welding (GMAW) hardfacing does sometimes create non-homogenous structures in the material not only in deposited material, but also in the heat-affected zone (HAZ) and base material. Those structures are not fully deterministic, so the modelling method should account for this unpredictable component and only learn the generic structure of the hardness of the resulting material. Artificial neural networks (ANN) were used to create a model of the process using only measured samples without any knowledge of equations governing the process. Robust learning was used to decrease the influence of outliers and noise in the measured data on the neural model performance. The proposed method relies on modification of the loss function and several of them are compared and evaluated as an attempt to construct general framework for analysing the hardness as a function of electric current and arc velocity. The proposed method can create robust models of the hardfacing layers deposition or other welding processes and predict the properties of resulting materials even for unseen parameters based on experimental data. This modelling framework is not typically used for metallurgy, and it requires further case studies to verify its generalisability.

Modelling the partially unknown distribution of wall lizards (Podarcis) in North Africa: ecological affinities, potential areas of occurrence, and methodological constraints

2008 ◽  
Vol 86 (9) ◽  
pp. 992-1001 ◽  
Author(s):  
A. Kaliontzopoulou ◽  
J. C. Brito ◽  
M. A. Carretero ◽  
S. Larbes ◽  
D. J. Harris
Keyword(s):  
North Africa ◽  
Habitat Type ◽  
Model Performance ◽  
Species Distribution Modelling ◽  
Data Sets ◽  
Mountain Ranges ◽  
Presence Data ◽  
Scale Models ◽  
Two Factors ◽  
Negative Effect

Species distribution modelling (SDM) is a powerful tool to investigate various biological questions with a spatial component, but is also sensitive to presence-data characteristics, particularly data precision and clustering. Here, we investigate the effect of these two factors on SDM using Maxent as the modelling technique and wall lizards (genus Podarcis Wagler, 1830) from North Africa as a model system. Podarcis are not ubiquitous in Africa as they are in Europe, but their ecological and distributional characteristics in this area are poorly known. Our results show that the most important environmental factors related to the distribution of this genus in North Africa are humidity, habitat type, and temperature. The areas of potential distribution predicted by models based on data sets with different precision and clustering characteristics show high relatedness to coastal areas and mountain ranges and extend to areas were presence records for these lizards are lacking. Our comparison of models based on different data sets indicates that finer scale models, even if based on fewer presence locations, outperform coarser scale ones. Data clustering does not have a negative effect on model performance, but is rather overcome by sample-size effects. Similar approaches may be of general application to other stenoic species for which available locations are scarce in comparison with the extension of the study area.

scholarly journals Land-use and related pressures have reduced biotic integrity more on islands than on mainlands

2019 ◽  
Author(s):  
Katia Sanchez-Ortiz ◽  
Ricardo E. Gonzalez ◽  
Adriana De Palma ◽  
Tim Newbold ◽  
Samantha L. L. Hill ◽  
...  
Keyword(s):  
Native Species ◽  
Oceanic Islands ◽  
Pressure Effects ◽  
Biotic Integrity ◽  
Biodiversity Hotspots ◽  
Global Models ◽  
Modelling Framework ◽  
Road Development ◽  
Safe Limits ◽  
Disproportionate Number

ABSTRACTTracking progress towards biodiversity targets requires indicators that are sensitive to changes at policy-relevant scales, can easily be aggregated to any spatial scale and are simple to understand. The Biodiversity Intactness Index (BII), which estimates the average abundance of a diverse set of organisms in a given area relative to their reference populations, was proposed in 2005 in response to this need. A new implementation of BII was developed as part of the PREDICTS project in 2016 and has been adopted by GEO BON, IPBES and CBD. The previous global models for BII estimation could not account for pressures having different effects in different settings. Islands are a setting of particular interest: many are home to a disproportionate number of endemic species; oceanic islands may have relatively low overall species diversity because of their isolation; and the pattern and timing of human pressures can be very different from that seen on mainlands. Here, we test whether biotic integrity – as estimated by BII – has decreased more severely on islands than mainlands. We update methods previously used to estimate BII globally (Newbold et al., 2016) to allow pressure effects to differ between islands and mainlands, while also implementing some other recent improvements in modelling. We estimate BII for islands and mainlands by combining global models of how two aspects of biodiversity – overall abundance, and compositional similarity to minimally-impacted sites – have been affected by human pressures. We use these models to project high-resolution (∼1km2) global maps of BII for the year 2005. We calculate average BII for island and mainland biomes, countries, IPBES regions and biodiversity hotspots; and repeat our analyses using a richness-based version of BII. BII on both islands and mainlands has fallen below the values proposed as safe limits across most regions, biomes and biodiversity hotspots. Our BII estimates are lower than those published in 2016, globally, within all biodiversity hotspots and within most biomes, and show greater spatial heterogeneity; detailed analysis of these differences shows that they arise mostly from a combination of improvements to the modelling framework. Average BII does not strongly differ between islands and mainlands, but richness-based BII has fallen by more on islands. It seems native species are more negatively affected by rising human population density and road development on islands than mainlands, and islands have seen more land conversion. Our results highlight the parlous state of biodiversity native to islands.

scholarly journals A test of native plant adaptation more than one century after introduction of the invasive Carpobrotus edulis to the NW Iberian Peninsula

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Carlos García ◽  
Josefina G. Campoy ◽  
Rubén Retuerto
Keyword(s):  
Native Species ◽  
Genetic Variance ◽  
Common Garden ◽  
Reciprocal Effects ◽  
Native Plant ◽  
Adaptive Responses ◽  
Long Term Effects ◽  
Carpobrotus Edulis ◽  
Nw Iberia

Abstract Background Although the immediate consequences of biological invasions on ecosystems and conservation have been widely studied, the long-term effects remain unclear. Invaders can either cause the extinction of native species or become integrated in the new ecosystems, thus increasing the diversity of these ecosystems and the services that they provide. The final balance of invasions will depend on how the invaders and native plants co-evolve. For a better understanding of such co-evolution, case studies that consider the changes that occur in both invasive and native species long after the introduction of the invader are especially valuable. In this work, we studied the ecological consequences of the more than one century old invasion of NW Iberia by the African plant Carpobrotus edulis. We conducted a common garden experiment to compare the reciprocal effects of competition between Carpobrotus plants from the invaded area or from the native African range and two native Iberian plant species (Artemisia crithmifolia and Helichrysum picardii) from populations exposed or unexposed to the invader. Results Exposure of H. picardii populations to C. edulis increased their capacity to repress the growth of Carpobrotus. The repression specifically affected the Carpobrotus from the invader populations, not those from the African native area. No effects of exposition were detected in the case of A. crithmifolia. C. edulis plants from the invader populations had higher growth than plants from the species' African area of origin. Conclusions We found that adaptive responses of natives to invaders can occur in the long term, but we only found evidence for adaptive responses in one of the two species studied. This might be explained by known differences between the two species in the structure of genetic variance and gene flow between subpopulations. The overall changes observed in the invader Carpobrotus are consistent with adaptation after invasion.

scholarly journals Monte Carlo based calibration and uncertainty analysis of a coupled plant growth and hydrological model

2013 ◽  
Vol 10 (12) ◽  
pp. 19509-19540 ◽  
Author(s):  
T. Houska ◽  
S. Multsch ◽  
P. Kraft ◽  
H.-G. Frede ◽  
L. Breuer
Keyword(s):  
Monte Carlo ◽  
Plant Growth ◽  
Cross Validation ◽  
Model Performance ◽  
Coupled Model ◽  
Radiation Use Efficiency ◽  
Retention Curve ◽  
Modelling Framework ◽  
Use Efficiency ◽  
Radiation Use

Abstract. Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil–plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the van-Genuchten–Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape parameter of the retention curve n was highly constrained whilst other parameters of the retention curve showed a large equifinality. The root and storage dry matter observations were predicted with a NSE of 0.94, a low bias of −58.2 kg ha−1 and a high R2 of 0.98. Dry matters of stem and leaves were predicted with less, but still high accuracy (NSE = 0.79, bias = 221.7 kg ha−1, R2 = 0.87). We attribute this slightly poorer model performance to missing leaf senescence which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use-efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need of including agricultural management options in the coupled model.

scholarly journals Using Sentinel-2 Multispectral Images to Map the Occurrence of the Cossid Moth (Coryphodema tristis) in Eucalyptus Nitens Plantations of Mpumalanga, South Africa

2019 ◽  
Vol 11 (3) ◽  
pp. 278 ◽  
Author(s):  
Samuel Kumbula ◽  
Paramu Mafongoya ◽  
Kabir Peerbhay ◽  
Romano Lottering ◽  
Riyad Ismail
Keyword(s):  
South Africa ◽  
Management Strategies ◽  
Vegetation Indices ◽  
Model Performance ◽  
Area Under The Curve ◽  
Mass Trapping ◽  
Eucalyptus Nitens ◽  
Operating Characteristics ◽  
Presence Data ◽  
Sentinel 2

Coryphodema tristis is a wood-boring insect, indigenous to South Africa, that has recently been identified as an emerging pest feeding on Eucalyptus nitens, resulting in extensive damage and economic loss. Eucalyptus plantations contributes over 9% to the total exported manufactured goods of South Africa which contributes significantly to the gross domestic product. Currently, the distribution extent of the Coryphodema tristis is unknown and estimated to infest Eucalyptus nitens compartments from less than 1% to nearly 80%, which is certainly a concern for the forestry sector related to the quantity and quality of yield produced. Therefore, the study sought to model the probability of occurrence of Coryphodema tristis on Eucalyptus nitens plantations in Mpumalanga, South Africa, using data from the Sentinel-2 multispectral instrument (MSI). Traditional field surveys were carried out through mass trapping in all compartments (n = 878) of Eucalyptus nitens plantations. Only 371 Eucalyptus nitens compartments were positively identified as infested and were used to generate the Coryphodema tristis presence data. Presence data and spectral features from the area were analysed using the Maxent algorithm. Model performance was evaluated using the receiver operating characteristics (ROC) curve showing the area under the curve (AUC) and True Skill Statistic (TSS) while the performance of predictors was analysed with the jack-knife. Validation of results were conducted using the test data. Using only the occurrence data and Sentinel-2 bands and derived vegetation indices, the Maxent model provided successful results, exhibiting an area under the curve (AUC) of 0.890. The Photosynthetic vigour ratio, Band 5 (Red edge 1), Band 4 (Red), Green NDVI hyper, Band 3 (Green) and Band 12 (SWIR 2) were identified as the most influential predictor variables. Results of this study suggest that remotely sensed derived vegetation indices from cost-effective platforms could play a crucial role in supporting forest pest management strategies and infestation control.

scholarly journals Predictions for an invaded world: a strategy to predict the distribution of native and non-indigenous species at multiple scales

2008 ◽  
Vol 65 (5) ◽  
pp. 742-745 ◽  
Author(s):  
Deborah A. Reusser ◽  
Henry Lee
Keyword(s):  
Native Species ◽  
Multiple Scales ◽  
Spatial Scales ◽  
Model Performance ◽  
Initial Step ◽  
Categorical Variables ◽  
Indigenous Species ◽  
Habitat Models ◽  
Habitat Scale ◽  
Non Indigenous Species

Abstract Reusser, D. A., and Lee II, H. 2008. Predictions for an invaded world: a strategy to predict the distribution of native and non-indigenous species at multiple scales. – ICES Journal of Marine Science, 65: 742–745. Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale.

scholarly journals Differences in Carbon Sequestration in Native vs. Exotic Pine Species (Tenerife, Canary Islands)

2013 ◽  
Vol 70 (2) ◽  
pp. 299-303
Author(s):  
José Ramón ARá‰VALO ◽  
Gloria GARCáA-FARIá‘A ◽  
Yeray MONTES DE OCA ◽  
Silvia FERNáNDEZ-LUGO
Keyword(s):  
Carbon Sequestration ◽  
Canary Islands ◽  
Native Species ◽  
Industrial Development ◽  
Carbon Sink ◽  
Fast Growth ◽  
Pinus Canariensis ◽  
Exotic Invasive Species ◽  
Exotic Invasive ◽  
Main Carbon

Global warming can be mitigated by carbon sequestration through forestry and agroforestry. For countries with low industrial development, carbon sequestration also represents an opportunity to fund sustainable development. In the Canary Islands, CO2 emissions are above the average for Spain, in fact, they are estimated to be three times higher. Authorities have been working in recent years to reduce these emissions and increase carbon sequestration. Afforestation on the island of Tenerife has been  carried  out  mainly  using  an  endemic  pine species  (Pinus canariensis), the  dominant  species  of native pine forest stands. However, the exotic Pinus radiata has also been introduced in some areas. The success of exotic invasive species is often attributed to their capacity for fast growth, particularly when resources are not limited and can continue to increase. In this situation, exotic species are more competitive  compared  to  native  ones.  We  evaluated  the  capacity  to  absorb  CO2  of P.  radiata  vs. P. canariensis  under  similar  environmental  conditions  and  planted  during  the  same  period.  Through allometric  equations  for  above  ground  biomass,  we  estimated  the  amount  of  biomass  and  carbon content in individuals and extrapolated these results to the rest of the mass (in the the Corona Forestal Natural  Park  in  Tenerife).  Our  preliminary  results  revealed  that P.  radiata  and P.  canariensis sequester  different  amounts  of  carbon  under  similar  environmental  conditions.  The  carbon  capture strategy of a species is strongly associated with disturbance, with species from disturbed sites having traits that confer capacity for fast growth. We suggest that P. radiata has a higher carbon sequestration capability per individual than the native species P. canariensis. However, the much larger extensions and density of P. canariensis make this species the main carbon sink on the island.

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