Supporting and inhibiting factors in the Presence of Astragalus curvirostris Boiss. Case study in semi-steppe Rangelands in Zagheh, Lorestan province

Introduction:

Analyzing complex ecological data requires flexible and robust analytical methods that can non-linear relationships, interactions and missing data control. The generalized additive model is a simple method to investigate the reactions of species with respect to environmental variables, where the results can be easily interpreted. Multivariable regressions such as the Monotonic increase model can play a role in expressing the ecological niche of a particular species. This ecological domain can include the mutual effects of non-living and living factors, but the relative role of living factors such as species competition is not clear compared to non-living factors. This is one of the issues that needs more research. Also, in the studies related to the response curve, the behavior of the species is investigated only along an environmental gradient, if several factors determine the distribution and behavior of the species in a combined manner, this should also be considered. The comparison between the findings of researchers in different regions on the Astragalus curvirostris Boiss species consistently shows the extreme effectiveness of the species from environmental factors or their combination. Understanding the relationship between plants and environmental factors and how plants respond to changes in environmental factors is one of the important topics in plant ecology. Unfortunately, in recent years, disturbances such as livestock grazing, changes in land use, and climate change have caused the destruction of A. curvirostris habitats. These threats cause vegetation destruction, loss of biodiversity and soil erosion in many pastures and forests of Iran. Therefore, knowing the response of A. curvirostris to environmental variables and modeling the distribution of this species is necessary for its use in the restoration of degraded pastures in steppe and semi-steppe areas.

Aim

By doing the present study, we will achieve the aim of knowing more about the positive and negative effects of environmental factors as well as the inhibiting and helping factors in the growth, establishment and distribution of Astragalus curvirostris Boiss, it became possible to use it in the restoration and modification of appropriate and similar pasture ecosystems.

Material and Methods

The habitat of A. curvirostris was selected in a way that includes a wide range of abundance of the studied species. Therefore, according to the 40-hectare enclosure range in the research site of Zaghe rangelands plants in Lorestan province, this habitat was selected as a study site. Then, according to the gradient of environmental changes, five transects with a length of 400 meters distances of 100 meters were used. Then, on each of them, six plots with dimensions of 4 x 4 meters were established according to the dimensions of the species with equal distances. In total, 30 plots were used in the ecological unit and Geographical location and quantitative and qualitative amounts of vegetation in each of the plots were also recorded. In addition, climatic parameters were received from the Lorestan Meteorological Department. In order to investigate the effect of environmental factors on species distribution, a soil sample with three replicates (0-30 cm) was taken from each of the plots and Their physical and chemical characteristics including soil texture, acidity, percentage of neutralized substances, absorbable phosphorus, absorbable potassium, organic carbon and total nitrogen were measured. Considering the importance of the species in fodder production and soil protection in pastures, to determine the factors affecting the changes in the species composition from the canonical correspondence analysis and to investigate the changes in the performance of this species along the slope of the environmental factors from the Generalized Additive Models was used. Random-systematic method was used for sampling environmental and plant characteristics during the years (2016 to 2018).

Results and Discussion

Investigating the effect of a set of environmental factors on vegetation changes in communities, using the forward selection method in conic ranking, led to the selection of 4 variables from among 19 primary variables.. Organic carbon %, clay %, acidity and litter % of the soil surface and from the topographic group were the geographical direction of the range. Investigating the correlation between the percentage of A. curvirostris vegetation and the studied ecological factors showed that distribution of this species has positive correlation with factors such as the percentage of O.C and N. Applying the GAM with Poisson error distribution showed that the variables, height above sea level, percentage of organic matter and soil nitrogen, as well as the percentage of stone are effective on the yield of the species. Investigating the performance of the species in relation to the variable of height above sea level and the percentage of stones and pebbles from the Monotonic decrease model and vice versa, the response of this species along the slope of changes in the amount of organic carbon, soil nitrogen and the percentage of soil litter from the Monotonic increase model mathematical expression of relationships between environmental variables and biological and biophysical characteristics is only an aid for interpreting field observations. This model presents the ecological needs of the species and can be of interest to natural resource managers in pasture improvement operations in similar areas and if the forecasting models have appropriate accuracy, they can be used in correctional and pasture management programs to suggest species compatible with the conditions of the region. Therefore, information such as disturbances should also be considered as predictors in regression-based distribution modeling. In conclusion, it should be noted that in grassland ecosystems, due to the dynamics of biological factors, even the strongest correlations, both in static and dynamic studies, cannot be assumed definitively. Of course, this information together with the field investigation provides appropriate information.