Evaluation of Spatio-Temporal Soil Moisture Variability in Semi-Arid Rangeland Ecosystem, Maasai Mara National Reserve, Kenya

Aim: To evaluate the spatio-temporal soil moisture storage and retention capacities in semi-arid rangeland ecosystem, Maasai Mara National Reserve (MMNR), Kenya Study Design: Randomized complete block design (RCBD) of reference Cosmic Ray Neutron Sensor (CRNS) station, ten-(10) spatially distributed (soil moisture and temperature capacitance) probes (5TM-ECH20) sites. Place and Duration of Study: Kenya, MMNR, the oldest natural semi-arid rangeland ecosystem and globally unique for the great wildebeest migration, between May 2017 and April 2019. Methodology: Soil moisture (SM) variation data was collected using (CRNS) at spatial and point-scale 5TM-ECH2O probes, and gravimetric water content from (10) spatially distributed stations. Both CRNS and 5TM-ECH2O probes were used to monitor near-real time moisture levels at different soil layers ranging between 0-5cm, 5-10cm, 15-20cm, 35-40cm, and 75-80cm. Soil physical and chemical properties were laboratory analyzed. Calibration and validation datasets were obtained from 5TM-ECH2O probe and gravimetric soil samples extracted from respective layers and sites. Results: The pedological characteristics of the investigated ecosystem soil profile indicate decreased bulk density by 2.1% to 11.12% from upper layers (0-5cm) to deeper layers at (75–80 cm). Across the rangeland, 70% of soil textural classes were sandy clay loam (SCL) with higher clay percent and 30% sandy clay (SC) and soil porosity varied between 30.1% and 51% in the ecosystem. Moreover, volumetric 2 water content (VWC) of spatially distributed 5TM-ECH2O probes ranged between 0.11m3m-3 and 0.32m3m-3 during wet season with mean VWC of 0.16m3m-3, however, the VWC ranged between 0.04 m3m-3 and 0.17m3m-3 during the dry season with a mean volume of 0.11m3m-3 across the rangeland ecosystem. Conclusion: In this study, SM exhibited an annual periodicity of seasonal variation of spatial and temporal moisture partitioned as moisture gaining, losing, and a moisture stable period. This probably could be a consequence of increased movement of water to deeper layers caused by high precipitation and less evaporative demand caused by lower temperatures. The calibrated CRNS probe provided good estimates of spatial soil moisture variation when calibrated with 5TM-ECH20 and gravimetric sampling in relation to precipitation events and that deeper soil layers showed higher amount of soil moisture than shallow layers. The findings of the study will provide better formulation of the ecosystem vegetation management policies, conservation and planning for sustainable wildlife tourism industry.

Rangeland Biodiversity and Climate Variability: Supporting the Need for Flexible Grazing Management

Resting or grazing exclusion is an effective practice widely adopted to restore degraded, arid rangelands. To understand its effect on plant diversity, we studied Hill’s diversity indices during two growing seasons (2017–2019). The experiment consisted of a three-level factorial design with four plant communities subjected to different resting durations (one, two, and three years) compared to continuously grazed areas (control). The results showed that rainfall plays an important role in arid rangeland restoration. Under favorable conditions, one-year grazing exclusion considerably enhanced species richness and evenness diversity compared to longer resting durations under dry to average rainfall conditions. The decision to how long livestock grazing exclusion would last should not be decided upfront as it depends on the climatic and the site-specific conditions. The findings of this study will have vital management implications for development agencies. Knowing that short grazing exclusion with adequate rainfall amount and distribution could be enough and offers a cost-effective technical option to ensure the sustainable restoration of arid rangeland. This flexible grazing management would also be more acceptable by the pastoral communities. Longer resting periods could have detrimental effects on arid rangeland vegetation, in addition to adding more pressure on the remaining rangeland areas open to grazing.

Multifractal analysis of spatial heterogeneity in Spanish arid rangelands

<p>Rangeland and agricultural landscapes are complex and multifractal based on the interaction of biotic and abiotic factors such as soil, meteorology, and vegetation. The effects of land-uses on these areas modify their characteristics and dynamics.  The use of Normalized Difference Vegetation Index (NDVI) and NDVI anomalies (NDVIa) from satellite time series can effectively aid on understanding the differences among rangeland uses and types.</p><p>Multifractal detrended fluctuation analysis (MDFA) focuses on measuring variations of the moments of the absolute difference of their values at different scales. This allows us to use different multifractal exponent such as generalized Hurst exponent (H(q)), and the scaling exponent (ζ(q)) to characterize each area.</p><p>We collected the time series using satellite data of MODIS (MOD09Q1.006) from 2002 to 2019. Two areas from southeastern Spain (Murcia province) of 6.25 Km<sup>2</sup> were selected. Each area has 132 pixels with a spatial resolution of 250 x 250 m<sup>2</sup> and a temporal resolution of 8 days. The areas were selected to compare two types of arid rangeland. Area 1 (A1) is mainly covered by a mixed herbaceous cropland and grassland, Area 2 (A2) presents tree crops as well as a small patch of Mediterranean scrubland.</p><p>MDFA was used on every pixel of each area and H(q), and ζ(q) were plotted and compared. Our results report different exponent behaviours for diverse rangeland type or use. Within each area when different vegetation types are present MFDFA can allow us to distinguish among them such as in A2 where the pixels composing the river that crosses the area show less antipersistent character than the surrounding tree crops.<br>Comparing the scaling exponent of NDVI and NDVIa also suggest a difference of influence on the multifractal character of long-range correlations. This influence is much stronger in A4 than the three others, having their multifractal character due more heavily to probability density function.</p><p>We conclude that MDFA is a good tool to characterize arid rangelands spatial heterogeneity, particularly for rangeland with different vegetation types. It can be used to monitor and manage arid rangeland. It can be useful for policy-makers for short- and long-term solutions.</p><p><strong>Acknowledgements: </strong>The authors acknowledge the support of Project No. PGC2018-093854-B-I00 of the Ministerio de Ciencia Innovación y Universidades of Spain, “Garantía Juvenil” scholarship from Comunidad de Madrid, and the financial support from Boosting Agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020EU, DT-SPACE-01-EO-2018-2020.</p>

Assessing Extensive Semi-Arid Rangeland Beef Cow–Calf Welfare in Namibia: Part 1: Comparison between Farm Production System’s Effect on the Welfare of Beef Cows

A proposed animal welfare assessment protocol for semi-arid rangeland-based cow–calf systems in Namibia combined 40 measures from a protocol developed for beef cattle in New Zealand with additional Namibia-specific measures. Preliminary validation of the protocol had been undertaken with five herds in one semi-commercial village. The aim of the current study was to apply this protocol and compare animal welfare across three cow–calf production systems in Namibia. A total of 2529 beef cows were evaluated during pregnancy testing in the yards of 17 commercial, 20 semi-commercial, and 18 communal (total: 55) herds followed by an assessment of farm resources and a questionnaire-guided interview. Non-parametric tests were used to evaluate the difference in the welfare scores between the production systems. The results indicated a discrepancy of animal welfare between the three farm types, with a marked separation of commercial farms from semi-commercial, and communal village farms in the least. The differences in these production systems were mainly driven by economic gains through access to better beef export market for commercial farms and semi-commercial villages, as well as by the differences in the available grazing land, facility designs/quality, and traditional customs in the village systems. The results indicate an advantage of commercialization over communalization.