Wyniki wyszukiwania - Biblioteka Nauki

1

Maxent Modelling for Distribution of Plant Species Habitats of Rangelands (Iran)

100%

Chahouki M. A. Z. , Sahragard H. P.

Polish Journal of Ecology

|

2016

|

tom Vol. 64, nr 4

453--467

EN

Quantifying the pattern of habitat distribution for range plant species can assist sustainable planning of rangeland use and management. However, data of plant species distribution are often scarce and modeling of habitat distribution using commonly used models is difficult. In this study, the Maximum Entropy Method (MaxEnt) was used to model the distribution of plant habitat to find the effective variables in plant species occurrence in the Poshtkouh rangelands on Yazd province, central Iran. Maps of the environmental variables were generated using GIS and Geostatistics facilities. Accuracy of model output was assessed using area under the curve (AUC) of the receiver operating characteristic and keeping 30 percent of the data. Evaluation of model accuracy by AUC indicated good and acceptable predictive accuracy for all plant species habitats, except Artemisia sieberi which had high frequency. The predictive maps of Artemisia aucheri, Scariola orientalis — Astragalus albispinus, A. sieberi2 and A. sieberi — Zygophyllum eurypterum had fair agreement with their corresponding observed maps. In addition, the accuracy of S. orientalis — A. sieberi and Tamarix ramosissima predictive maps was low and the estimated conformity rate of prediction and observed maps was poor. In fact, due to differences in the optimal ecological range, level of agreement of predictive and observed maps at each site was different. MaxEnt was substantially excellent to predict distributions of plant species habitat with narrow ecological niches e.g. Rheum ribes — A. sieberi, Seidlitzia rosmarinus and Cornulaca monacantha. It can also perform well with fairly few samples due to employing regularization.

2

Spatial patterns and coexistence of the native forb, Psathyrostachys fragilis (Asteracea) and the native invader, Gundelia tournefortii (Poaceae) in a semi-arid rangeland of Iran

100%

Khojasted F. , Chahouki M. A. Z.

|

tom 61

|

nr 2

EN

In this study, we investigated the interactions between the dominant native invader, Gundelia tournefortii, and the dominant forage species, Psathyrostachys fragilis in rangelands of Taleghan (Iran). Four transects of 150 meters were considered as sampling unit. Using randomly-systematic method, 15 plots (1 × 1m) were placed along each transect with a distance of 10 m. List of species, the canopy cover and the numbers of plant species were determined in each plot. The spatial association of the two dominant species was assessed by studying association, covariation, and distribution pattern (using the Hopkins’ index) of plants. We found a clumped distribution pattern in both two dominant species. Results of this study revealed a strong competitive interaction between the dominant plant species in studied area with P. fragilis was more frequent and had more canopy cover than the native invader G. tournefortii. So, according to our findings, P. fragilis may present a suitable candidate for artificial re-vegetating and protecting against invaders to restore the biodiversity and ecological health of endangered rangelands.

3

Spatial patterns and coexistence of the native forb, Psathyrostachys fragilis (Asteracea) and the native invader, Gundelia tournefortii (Poaceae) in a semi-arid rangeland of Iran

100%

Khojasted F. , Chahouki M. A. Z.

Polish Journal of Ecology

|

2013

|

tom Vol. 61, nr 2

373--377

EN

In this study, we investigated the interactions between the dominant native invader, Gundelia tournefortii, and the dominant forage species, Psathyrostachys fragilis in rangelands of Taleghan (Iran). Four transects of 150 meters were considered as sampling unit. Using randomly-systematic method, 15 plots (1 x 1m) were placed along each transect with a distance of 10 m. List of species, the canopy cover and the numbers of plant species were determined in each plot. The spatial association of the two dominant species was assessed by studying association, covariation, and distribution pattern (using the Hopkins’ index) of plants. We found a clumped distribution pattern in both two dominant species. Results of this study revealed a strong competitive interaction between the dominant plant species in studied area with P. fragilis was more frequent and had more canopy cover than the native invader G. tournefortii. So, according to our findings, P. fragilis may present a suitable candidate for artificial re-vegetating and protecting against invaders to restore the biodiversity and ecological health of endangered rangelands.

4

Comparison of three modelling approaches for predicting plant species distribution in mountainous scrub vegetation (Semnan Rangelands, Iran)

80%

Chahouki M. A. Z. , Ahvazi L. K. , Azarnivand H.

Polish Journal of Ecology

|

2012

|

tom 60

|

nr 2

EN

The predictive modeling of plant species distribution has wide applications in vegetation studies. This study attempts to assess three modeling approaches to predict the plant distribution in the dry (precipitation 128–275 mm) mountainous (altitude 1129–2260 m a.s.l.) scrub vegetation on the example of the rangelands of northeastern Semnan, Iran. The vegetation of the study area belongs to the communities of Artemisia, Astralagus, Eurotia and other scrub species. The main objective of this study is to compare the predictive ability of three habitat models, and to find the most effective environmental factors for predicting the plant species occurrence. The Canonical Correspondence Analysis (CCA), Logistic Regression (LR), and Artificial Neural Network (ANN) models were chosen to model the spatial distribution pattern of vegetation communities. Plant density and cover, soil texture, available moisture, pH, electrical conductivity (EC), organic matter, lime, gravel and gypsum contents and topography (elevation, slope and aspect) are those variables that have been sampled using the randomized systematic method. Within each vegetation type, the samples were collected using 15 quadrates placed at an interval of 50 m along three 750 m transects. As a necessary step, the maps of all factors affecting the predictive capability of the models were generated. The results showed that the predictive models using the LR and ANN methods are more suitable to predict the distribution of individual species. In opposite, the CCA method is more suitable to predict the distribution of the all studied species together. Using the finalized models, maps of individual species (for different species) or for all the species were generated in the GIS environment. To evaluate the predictive ability of the models, the accuracy of the predicted maps was compared against real-world vegetation maps using the Kappa statistic. The Kappa (κ) statistic was also used to evaluate the adequacy of vegetation mapping. The comparison between the vegetation cover of a map generated using the CCA application and its corresponding actual map showed a good agreement (i.e. κ= 0.58). The results also revealed that maps generated using the LR and ANN models for Astragalus spp., Halocnemum strobilaceum, Zygophyllum eurypterum and Seidlitzia rosmarinus species have a high accordance with their corresponding actual maps of the study area. Due to the high level of adaptability of Artemisia sieberi, allowing this specie to grow in most parts of the study area with relatively different habitat conditions, a predictive model for this species could not be fixed. In such cases, a set of predictive models may be used to formulate the environment-vegetation relationship. Finally, the predictive ability of the LR and ANN models for mapping Astragalus spp. was determined as κ = 0.86 and κ = 0.91 respectively, implying a very good agreement between predictions and observations. It is concluded that the combination of mod- elling of the local species distribution constitutes a promising future research area, which has the potentiality to enhance assessments and conservation planning of vegetation (like rangelands) based on predictive species models.

5

MaxEnt modeling for predicting impacts of environmental factors on the potential distribution of Artemisia aucheri and Bromus tomentellus-Festuca ovina in Iran

80%

Esfanjani J. , Ghorbani A. , Chahouki M. A. Z.

Polish Journal of Environmental Studies

|

2018

|

tom 27

|

nr 3

EN

The main goal of this study was to estimate the geographic distribution of Artemisia aucheri and Bromus tomentellus-Festuca ovina habitat using the maximum entropy modeling technique (MaxEnt) in the Chaharbagh rangeland of Golestan Province in Iran. Vegetation sampling was done using the random- systematic method. A total of 120 plots were placed in the study area. Soil samples were taken 0-30 cm (sampling of the soil due to the mountainous terrain and deep rooted plants, depths were determined at the 0-30 cm layer). Measured soil properties included texture, organic carbon, lime, pH, EC, and N. Topographical data (obtained from a DEM map) was elevation, slope, and aspect. To prepare the data for being enterer into MaxEnt software, first the map of soil factors was obtained through the kriging method in GIS software. Then, for analysis, the elevation, and slope, geographic directions, and soil factors maps and the presence points of plant species were entered. Using the jackknife method and response curve we found the most important environmental predictor variables. Results showed that N, sand, and clay had the greatest impacts on the distribution of A. aucheri and N, sand, silt, clay, and lime in soil had the greatest impacts on the distribution of B. tomentellus-F. ovina in the study area. Correspondence of actual map with the predictive one was assessed at a satisfactory level (Kappa coefficient = 0.05 for A. aucheri but Kappa coefficient = 0.51 for B. tomentellus-F. ovina). So MaxEnt method is the more successful in predicting B. tomentellus-F. ovina habitat than A. aucheri habitat, because the distribution of A. aucheri habitat was vast and outspread in the study area.

6

Comparison of different geostatistical methods for soil mapping using remote sensing and environmental variables in Poshtkouh rangelands, Iran

70%

Hosseini S. Z. , Kappas M. , Budaghabadi M. B. , Chahouki M. A. Z. , Khojasteh E. R.

Polish Journal of Environmental Studies

|

2014

|

tom 23

|

nr 3

EN

The aims of this study were: 1) to map the different soil parameters using three geostatistical approaches, including; ordinary kriging (OK), cokriging (CK), and regression kriging (RK), 2) to compare the accuracy of maps created by the mentioned methods, and 3) to evaluate the efficiency of using ancillary data such as satellite images, elevation, precipitation, and slope to improve the accuracy of estimations. In the rangelands of the Poushtkouh area of central Iran, 112 soil samples were collected. The maps of different soil parameters were created using the mentioned methods. To assess the accuracy of these maps, cross-validation analyses were conducted. The cross-validation results were assessed by the root mean square error (RMSE) and normal QQ-plot together with sum and average error to suggest the best estimation approach for mapping each soil parameter. The results have shown that, in most cases, taking the ancillary data into account in estimations has increased the accuracy of the created maps. Except for clay, the OK method was suggested as the best estimation method, and the RK and CK were the best recommended estimation methods for the rest of the parameters. The results suggest the application of the framework of this study for similar areas.