Environmental factors influencing the distribution of endangered endemic species Hedysarum criniferum Boiss in arid and semi-arid rangelands,Iran

Understanding the factors influencing the distribution of plant species is crucial for enhancing the management of endangered ecosystems. This study investigated the response of Hedysarum criniferum Boiss, an endemic and endangered species to 25 environmental variables within its habitats with an area of 2.95×10^(5) km^(2) in arid and semi-arid rangelands of Iran. The purpose of this research is to identify the key environmental factors affecting the distribution and habitat preferences of H. criniferum for further conservation and restoration of the species. To predict the occurrence of H. criniferum and explore its relationship with environmental factors, we employed the best subset regression analysis, the hierarchical classification, and the extended Huisman-Olf-Fresco(eHOF) model. The results showed that four environmental variables, i.e., gravel content, pH, annual minimum temperature, and mean annual temperature showed significant correlations with the canopy cover of H. criniferum(P<0.05). The probability of H. criniferum occurrence increased with higher precipitation and elevation, while it decreased with higher mean annual temperature, annual minimum temperature, and gravel content. The species' response curves and their optimal values, as assessed by the eHOF model, indicated that the response to mean annual temperature, ranging from 12℃ to 16℃, was optimal at 13℃. The response to mean annual precipitation, within a range of 150–650 mm, was optimal at 650 mm. Elevation responses, spanning from 1546 to 2450 m, showed an optimum at 2450 m. Regarding soil characteristics, the response to gravel content, ranging from 13.0%–48.0%, demonstrated an optimal value at 20.0%. The pH levels, varying from 7.5 to 8.2, prompted a sine-shaped response with an optimal pH of 8.0. These findings provide valuable insights for predicting species occurrence and identifying suitable locations for restoration programs. Our study underscores the importance of considering multiple environmental variables in habitat suitability assessments. By incorporating these broader considerations, we can further refine predictive models and enhance conservation efforts aimed at restoring habitats conducive to the luxuriance of endangered species like H. criniferum.

Quantifying relations between altered hydrology and fish community responses for streams in Minnesota

Background:Altered hydrology is a stressor on aquatic life,but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota.Best sub-sets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic metrics(i.e.,duration,frequency,magnitude,rate-of-change,and timing)computed from streamgage records and six categories of biological metrics(i.e.,composition,habitat,life history,reproductive,tolerance,trophic)computed from fish-community samples,as well as fish-based indices of biotic integrity(FIBI)scores and FIBI scores normalized to an impairment threshold of the corresponding stream class(FIBI_BCG4).Relations between hydrology and fish community responses were examined using three hydrologic datasets that represented periods of record,long-term changes,and short-term changes to flow regimes in streams of Minnesota.Results:Regression models demonstrated significant relations between hydrologic explanatory metrics and fish-based biological response metrics,and the five regression models with the strongest linear relations explained over 70%of the variability in the biological metric using three hydrologic metrics as explanatory variables.Tolerance-based biological metrics demonstrated the strongest linear relations to hydrologic metrics.The most commonly used hydrologic metrics were related to bankfull flows and aspects of flow variability.Conclusions:Final regression models represent paired streamgage records and biological samples throughout the State of Minnesota and encompass differences in stream orders,hydrologic landscape units,and watershed sizes.Presented methods can support evaluations of stream fish communities and facilitate targeted efforts to improve the health of fish communities.Methods also can be applied to locations outside of Minnesota with continuous streamgage data and fish-community samples.