Assessing soil and land health across two landscapes in eastern Rwanda to inform restoration activities

Land degradation negatively impacts water, food, and nutrition security and is leading to increased competition for resources. While landscape restoration has the potential to restore ecosystem function, understanding the drivers of degradation is critical for prioritizing and tracking interventions. We sampled 300–1000 m2 plots using the Land Degradation Surveillance Framework across Nyagatare and Kayonza districts in Rwanda to assess key soil and land health indicators, including soil organic carbon (SOC), erosion prevalence, vegetation structure and infiltration capacity, and their interactions. SOC content decreased with increasing sand content across both sites and sampling depths and was lowest in croplands and grasslands compared to shrublands and woodlands. Stable carbon isotope values (δ13C) ranged from −15.35 ‰ to −21.34 ‰, indicating a wide range of historic and current plant communities with both C3 and C4 photosynthetic pathways. Field-saturated hydraulic conductivity (Kfs) was modeled, with a median of 76 mm h−1 in Kayonza and 62 mm h−1 in Nyagatare, respectively. Topsoil OC had a positive effect on Kfs, whereas pH, sand, and erosion had negative effects. Soil erosion was highest in plots classified as woodland and shrubland. Maps of soil erosion and SOC at 30 m resolution were produced with high accuracy and showed strong variability across the study landscapes. These data demonstrate the importance of assessing multiple biophysical properties in order to assess land degradation, including the spatial patterns of soil and land health indicators across the landscape. By understanding the dynamics of land degradation and interactions between biophysical indicators, we can better prioritize interventions that result in multiple benefits as well as assess the impacts of restoration options.

Identifying Policy-relevant Indicators for Assessing Landscape Vegetation Patterns to Inform Planning and Management on Multiple-use Public Lands

Understanding the structure and composition of landscapes can empower agencies to effectively manage public lands for multiple uses while sustaining land health. Many landscape metrics exist, but they are not often used in public land decision-making. Our objectives were to (1) develop and (2) apply a process for identifying a core set of indicators that public land managers can use to understand landscape-level resource patterns on and around public lands. We first developed a process for identifying indicators that are grounded in policy, feasible to quantify using existing data and resources, and useful for managers. We surveyed landscape monitoring efforts by other agencies, gathered science and agency input on monitoring goals, and quantified the prevalence of potential indicators in agency land health standards to identify five landscape indicators: amount, distribution, patch size, structural connectivity, and diversity of vegetation types. We then conducted pilot applications in four bureau of land management (BLM) field offices in Arizona, California, and Colorado to refine procedures for quantifying the indicators and assess the utility of the indicators for managers. Results highlighted the dominance of upland and the limited extent of riparian/wetland vegetation communities, moderate connectivity of priority vegetation patches, and lower diversity of native vegetation types on BLM compared to non-BLM lands. Agency staff can use the indicators to inform the development of quantitative resource management objectives in land use plans, evaluate progress in meeting those objectives, quantify potential impacts of proposed actions, and as a foundation for an all-lands approach to landscape-level management across public lands.

EFEKTIVITAS BERBAGAI BAHAN FORMULA PUPUK HAYATI SIANOBAKTERI TERHADAP PERTUMBUHAN DAN HASIL PADI GOGO VARIETAS SITU BAGENDIT

Rice is an important commodity in human life where its production increase must be followed by environmental sustainability and land health. The achievement of increased rice production supported by environmental sustainability can be achieved by utilizing biological fertilizers. One of the microbes that can be used as nutrient providers for rice plants is cyanobacteria. This study was carried out in a greenhouse and soil biology laboratory of the Indonesian Soil Research Institute using a randomized block design with four replications. The treatments tested consisted of F0 (without treatment), F1 (wet cyanobacteria isolate), F2 (dry cyanobacteria isolate), F3 (cyanobacteria + rock phosphate), F4 (cyanobacteria + biochar), F5 (cyanobacteria + kaolin), F6 (cyanobacteria + rock phosphate + kaolin), F7 (cyanobacteria + rock phosphate + biochar), F8 (cyanobacteria + kaolin + biochar). The results showed that the cyanobacteria formula treatment with biochar (F4) carriers showed the highest total population in the parameters of the cyanobacteria population, bacteria, and fungi so that the interaction was said to be positive. The application of cyanobacteria formula to soil chemistry did not significantly affect the post-harvest soil N, P, and K, while the increase in soil pH occurred in the overall treatment of the cyanobacteria formula. Treatment of cyanobacteria formula with biochar carrier (F4) had significantly different results on parameters of number of tillers, number of panicles, grain weight, number of grains.

Smart Farming using IoT

Rural and urban areas in India face a variety of comparable problems within the domain of agriculture, which calls for certainly comparative answers for being coordinated towards finding these issues. The purpose of this concept is to analyze the ability of IoT techniques in relation to impoverishment in these areas, besides the requirements known in these commodities and with stress on farming. This work analyzes samples of an internet of things to modify the farming desires of the commodities for the region to maximize the yield production. In India, most of the peoples relay on agriculture and a big part of nation’s income originate from the agriculture. Automation of agriculture method is one in all the crucial steps to our country, which needs to import immense quantity of crops from different nations to satisfy the need of peoples. The main challenge of the rural and urban agriculture area is that the correct observation of the land health, the environment, and arrange the spraying.

Earth Observation for Accurate Mapping of Soil Functional Properties, Land Health and Soil Infiltrability in Rwanda

<p>Earth observation (EO) has a large potential for mapping of soil functional properties such as soil organic carbon, soil pH or acidity, soil fertility parameters and soil texture. Recent advances in the application of EO data in combination with systematic field data sampling, standardized soil data reference analysis and the use of soil spectroscopy have shown these approaches to be both robust and scalable. We present a case study from Rwanda where we apply EO data in combination with field and laboratory data collected using the Land Degradation Surveillance Framework (LDSF) to map functional soil properties, soil erosion prevalence and land cover at fine spatial resolution. Digital soil maps were produced at a spatial resolution of 30m with an accuracy of 85 to 90%, while soil erosion prevalence was mapped with an accuracy of 86% using Landsat satellite imagery and machine learning models. </p><p>We also assess interactions between spatial assessments of soil organic carbon, soil erosion prevalence and land cover at a spatial resolution of 30m in order to identify land degradation hotspots and better target interventions to restore degraded land across four districts in Rwanda. We further explore the effects of soil erosion, root-depth restrictions and soil organic carbon content on saturated hydraulic conductivity in three LDSF sites in Nyagatare, Kayonza and Bugesera districts, respectively. Saturated hydraulic conductivity was modeled based on single-ring measurements of infiltration capacity using a modified Reynolds & Elrick steady-state single ring model for 48 LDSF plots per site. The results show significant spatial variation in infiltrability within sites.</p><p>The results of the study show the importance of rigorous protocols for sampling and analyses of soil properties and indicators of land health across landscapes. By simultaneously assessing soil properties, indicators of land degradation and soil infiltrability we demonstrate the utility of these approaches in understanding drivers of land degradation across multiple spatial scales for targeting of options for land restoration and monitoring of the effectiveness of these interventions over time across multiple dimensions of land health.</p>

A commentary on land, health, and Indigenous knowledge(s)

This commentary explores the relationships between land, knowledge, and health for Indigenous peoples. Indigenous knowledge is fundamentally relational, linked to the land, language and the intergenerational transmission of songs, ceremonies, protocols, and ways of life. Colonialism violently disrupted relational ways, criminalizing cultural practices, restricting freedom of movement, forcing relocation, removing children from families, dismantling relational worldviews, and marginalizing Indigenous lives. However, Indigenous peoples have never been passive in the face of colonialism. Now more than ever, Indigenous knowledge in three critical areas—food and water security, climate change, and health—is needed for self-determination and collective survival in a rapidly changing world.