A long-term spatiotemporal analysis of biocrusts across a diverse arid environment: The case of the Israeli-Egyptian sandfield

Noy, Klil; Ohana‐Levi, Noa; Panov, Natalya; Silver, Micha; Karnieli, Arnon

doi:10.1016/j.scitotenv.2021.145154

Cited by 11 publications

(8 citation statements)

References 79 publications

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“…As detailed in the Introduction, the historical climatic and anthropogenic processes that have occurred over the years in the north‐western Negev Desert region of Israel, through contrasting forces of various human activities and long‐term droughts, have created a mosaic of biocrust and vegetation cover levels. Since both climatic changes and anthropogenic activity are ongoing processes, the spatial mosaic is dynamic and fluctuates through time (Noy et al., 2021). Our data suggest that this dynamic mosaic may lead to structural differences between host communities.…”

Section: Discussionmentioning

confidence: 99%

“…Accordingly, the small, medium, and large spatial scales were chosen to account for the three species' small home ranges, which cause them to be restricted to a plot-size area for most of their lives, occasional more distant movements (a few hundreds of metres) within sites, and rare, further (a few kilometres) dispersal events. The four temporal scales were chosen to consider, on the one hand, the annual fluctuations in sand stabilization (Noy et al, 2021) and rodents' high turnover rate (short longevity and single reproduction period per year), and on the other hand, the expectation that changes in sand stabilization may need to accumulate to result in a significant habitat change, as suggested by the rodents' historical records (Figure 1c). this part, we had to simplify the models, and thus we used the proportion of the most abundant species as a surrogate for community structure rather than the proportions of all species.…”

Section: Assessments Of Spatial and Temporal Heterogeneities Across Scalesmentioning

confidence: 99%

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Cascading effects of sand stabilization on pathogen communities: Connecting global and local processes

Halle

Garrido

Noy

et al. 2021

Global Ecol Biogeogr

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Aim: To advance our understanding of the mechanisms that mediate the relationships between global climatic and anthropogenic processes and pathogen occurrence, it is crucial to evaluate the exact pathways connecting the ecological mediators and the pathogen responses across spatial and temporal heterogeneities at various scales.We investigated the pathways connecting these two types of heterogeneities in sand stabilization that were created by contrasting forces of various human activities and long-term droughts, and pathogen occurrence in host populations. The considered candidate ecological mediators were various components of host community structure, arthropod vector traits, and the pathogen occurrence in these vectors.Location: North-western Negev Desert's sands in Israel.

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Section: Discussionmentioning

confidence: 99%

Section: Assessments Of Spatial and Temporal Heterogeneities Across Scalesmentioning

confidence: 99%

Cascading effects of sand stabilization on pathogen communities: Connecting global and local processes

Halle

Garrido

Noy

et al. 2021

Global Ecol Biogeogr

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“…the M-K method is a widely-used non-parametric trend test that ranks the magnitude and direction of the trend of a variable over time [54,55]. It is commonly used in spatial and climatic geographical studies [22,56]. The daily rainfall measurements were summed into a yearly cumulative rainfall amounts, according to rain years (a time period of 12 months which starts on the 1st of October and ends on 30th September) and the trend was assessed at a significance level of p≤0.05.…”

Section: Meteorological Rainfall Datamentioning

confidence: 99%

“…Khosravi et al [20] evaluated the correlation between SPI and several vegetation classes indicating that pasture vegetation is highly sensitive to changes in the level of SPI, while farming lands showed less sensitivity in the short term when deep wells are used for irrigation. Previous studies [8,12,21,22] have indicated that the cumulative effect of changes in vegetation cover due to successive drought years or anthropogenic interference must be observed at a multiyear time scale, as perennial plant mortality can be delayed by several years.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Vegetation Dynamics at a Hyper Arid Region Using Remote Sensing, a Case Study from The Arava Valley

Meroz,

Yin,

Levin

2024

Preprint

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The hyper-arid environment is characterized by high inter-annual climatic fluctuations. The yearly average rainfall can change substantially for several years, forming wet or dry sub-periods. Observing rainfall trends over a sub-period can lead to a false perception of a change in the trend but may in fact represent a periodic cycle when examined on a larger time scale. We aimed to better characterize the rainfall regime prevailing in the hyper-arid Arava Valley (Israel/Jordan), and to examine the response of vegetation to annual rainfall. We hypothesized that annual and perennial vegetation would respond differently to wet and dry sub-periods, and that grazing activities will impact vegetation growth. We used a time series of monthly rainfall, from which we calculated Standard Precipitation Index (SPI), and calculated proxies of perennial and annual vegetation over the last four decades using Landsat-derived Normalized Difference Vegetation Index (NDVI). We found no clear trend in rainfall amounts during this period, however we did identify wet and dry sub-periods which were statistically distinct in rain and in vegetation patterns from each other. The highest levels of correlation between rainfall and the NDVI derived proxies were found when examining average rainfall over a period of two- three years for the annual vegetation and over four years for perennial vegetation. Using the Mann-Kendall test, we identified a time lag of two to four years, with the proxies of annual vegetation responding faster than the proxies of perennial vegetation, to shifts between wet and dry sub-period. In addition, we found a consistent difference between natural vegetation cover in Jordan (grazed) and Israel (non-grazed), favoring the development of natural vegetation on the Israeli side. We conclude that integrating between long-term remote sensing satellite imagery and climatic records revealed the greater resilience of perennial vegetation in the hyper-arid region to climatic fluctuation, and enabled us to identify the vegetation’s sensitivity to anthropogenic impact.

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“…The spectral features of BSCs were identified and characterized using multi-and hyperspectral data to differentiate them from co-occurring land cover types (e.g., bare soil and vascular plants), to distinguish between different crust types, and to assess differences between dry and wet BSCs [33][34][35][36][37][38][39][40][41]. Additionally, RS data was used to model various processes and activities of BSCs related to their ecosystem functions [2,19,[42][43][44][45][46][47][48].…”

Section: Introductionmentioning

confidence: 99%

Coverage and Rainfall Response of Biological Soil Crusts Using Multi-Temporal Sentinel-2 Data in a Central European Temperate Dry Acid Grassland

et al. 2021

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Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) in global drylands. They consist of poikilohydric organisms capable of adjusting their metabolic activities depending on the water availability. However, they, and with them, their ecosystem functions, are endangered by climate change and land-use intensification. Remote sensing (RS)-based studies estimated the BSC cover in global drylands through various multispectral indices, and few of them correlated the BSCs’ activity response to rainfall. However, the allocation of BSCs is not limited to drylands only as there are areas beyond where smaller patches have developed under intense human impact and frequent disturbance. Yet, those areas were not addressed in RS-based studies, raising the question of whether the methods developed in extensive drylands can be transferred easily. Our temperate climate study area, the ‘Lieberoser Heide’ in northeastern Germany, is home to the country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating multispectral Sentinel-2 (S2) data, indices derived from them, and topographic information to spatiotemporally map the BSC cover for the first time in Central Europe. We further monitored the BSC response to rainfall events over a period of around five years (June 2015 to end of December 2020). Therefore, we combined datasets of gridded NDVI as a measure of photosynthetic activity with daily precipitation data and conducted a change detection analysis. With an overall accuracy of 98.9%, our classification proved satisfactory. Detected changes in BSC activity between dry and wet conditions were found to be significant. Our study emphasizes a high transferability of established methods from extensive drylands to BSC-covered areas in the temperate climate. Therefore, we consider our study to provide essential impulses so that RS-based biocrust mapping in the future will be applied beyond the global drylands.

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A long-term spatiotemporal analysis of biocrusts across a diverse arid environment: The case of the Israeli-Egyptian sandfield

Cited by 11 publications

References 79 publications

Cascading effects of sand stabilization on pathogen communities: Connecting global and local processes

Cascading effects of sand stabilization on pathogen communities: Connecting global and local processes

Assessment of Vegetation Dynamics at a Hyper Arid Region Using Remote Sensing, a Case Study from The Arava Valley

Coverage and Rainfall Response of Biological Soil Crusts Using Multi-Temporal Sentinel-2 Data in a Central European Temperate Dry Acid Grassland

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