Remote sensing of specific climatic and biogeographical parameters is an effective means of evaluating the large-scale desertification status of drylands affected by negative human impacts. Here, we identify and analyze desertification trends in Iran for the period 2001-2015 via a combination of three indices for vegetation (NPP-net primary production, NDVI-normalized difference vegetation index, LAI-leaf area index) and two climate indices (LST-land surface temperature, P-precipitation). We combine these indices to identify and map areas of Iran that are susceptible to land degradation. We then apply a simple linear regression method, the Mann-Kendall non-parametric test, and the Theil-Sen estimator to identify long-term temporal and spatial trends within the data. Based on desertification map, we find that 68% of Iran shows a high to very high susceptibility to desertification, representing an area of 1.1 million km2 (excluding 0.42 million km2 classified as unvegetated). Our results highlight the importance of scale in assessments of desertification, and the value of high-resolution data, in particular. Annually, no significant change is evident within any of the five indices, but significant changes (some positive, some negative) become apparent on a seasonal basis. Some observations follow expectations; for instance, NDVI is strongly associated with cooler, wet spring and summer seasons, and milder winters. Others require more explanation; for instance, vegetation appears decoupled from climatic forcing during autumn. Spatially, too, there is much local and regional variation, which is lost when the data are considered only at the largest nationwide scale. We identify a northwest-southeast belt spanning central Iran, which has experienced significant vegetation decline (2001-2015). We tentatively link this belt of land degradation with intensified agriculture in the hinterlands of Iran's major cities. The spatial and temporal trends identified with the three vegetation and two climate indices afford a cost-effective framework for the prediction and management of future environmental trends in developing regions at risk of desertification.

• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Understanding the relationship between biodiversity and ecosystem functioning has been a core ecological research topic over the last decades. Although a key hypothesis is that the diversity of functional traits determines ecosystem functioning, we do not know how much trait diversity is needed to maintain multiple ecosystem functions simultaneously (multifunctionality). Here, we uncovered a scaling relationship between the abundance distribution of two key plant functional traits (specific leaf area, maximum plant height) and multifunctionality in 124 dryland plant communities spread over all continents except Antarctica. For each trait, we found a strong empirical relationship between the skewness and the kurtosis of the trait distributions that cannot be explained by chance. This relationship predicted a strikingly high trait diversity within dryland plant communities, which was associated with a local maximization of multifunctionality. Skewness and kurtosis had a much stronger impact on multifunctionality than other important multifunctionality drivers such as species richness and aridity. The scaling relationship identified here quantifies how much trait diversity is required to maximize multifunctionality locally. Trait distributions can be used to predict the functional consequences of biodiversity loss in terrestrial ecosystems.

• Publikační typ
• časopisecké články MeSH

Changes in vegetative and reproductive phenology rank among the most obvious plant responses to climate change. These responses vary broadly among species, but it is largely unknown whether they are mediated by functional attributes, such as size or foliar traits. Using a manipulative experiment conducted over two growing seasons, we evaluated the responses in reproductive phenology and output of 14 Mediterranean semiarid species belonging to three functional groups (grasses, nitrogen-fixing legumes and forbs) to a ~3°C increase in temperature, and assessed how leaf and size traits influenced them. Overall, warming advanced flowering and fruiting phenology, extended the duration of flowering and reduced the production of flowers and fruits. The observed reduction in flower and fruit production with warming was likely related to the decrease in soil moisture promoted by this treatment. Phenological responses to warming did not vary among functional groups, albeit forbs had an earlier reproductive phenology than legumes and grasses. Larger species with high leaf area, as well as those with small specific leaf area, had an earlier flowering and a longer flowering duration. The effects of warming on plant size and leaf traits were related to those on reproductive phenology and reproductive output. Species that decreased their leaf area under warming advanced more the onset of flowering, while those that increased their vegetative height produced more flowers. Our results advance our understanding of the phenological responses to warming of Mediterranean semiarid species, and highlight the key role of traits such as plant size and leaf area as determinants of such responses.

• Klíčová slova
• Climate change, Drylands, Functional group, Functional traits, Open top chambers, Phenology,
• Publikační typ
• časopisecké články MeSH