Neighboring Plots Research Articles

FORECASTING CHANGE IN THE LEVEL OF FOREST COVERAGE USING THE GLOBAL FOREST WATCH SERVICE AND THE PROGRAMMING AND DATA ANALYSIS LANGUAGE R

The problem of calculating the level of forest cover is considered, including forecasting changes in forest cover in individual forestry. It is stated that the authors previously developed software for calculating forest cover and processing information about forest plantations using the example of the village of Spivakivka in the Izyum district of the Kharkiv region. A comparison of forest cover over a number of years was also made using the Global Forest Watch resource. From this resource, images of Prydonetsk Forestry were taken with conventional designations: areas where new forest plantations are being planted are shown in blue, and areas where cutting is taking place are shown in pink. It is proposed to divide each of the uploaded images of the selected forestry into squares, and then analyze the data for each square. The pink color saturation was calculated and stored in the table. It is noted that forecasting the change in forest stands on the selected site, that is, the change in the percentage of felling, can be done in different ways. First, use regression analysis - apply the regression equation separately to the values of each square, as well as to the entire forestry. Secondly, to form a list of input factors containing indicators on the selected plot in the two previous years and the same indicators on neighboring plots. Thus, the number of factors will be equal to 27: 26 input and 1 output (values on the studied square). Such a forecasting problem can be solved either by the method of multivariate linear regression or by the method of artificial neural networks. The R programming and data analysis language was used to perform calculations using both methods. A script was created that performs calculations by constructing regression lines and an artificial neural network, and also allows determining the best architecture of a neural network and a more effective method of its training for a certain data set. The calculation of the felling dynamics in the entire forestry (the forecast for the last year provides an error of 1 %) and the calculation of the felling dynamics in the selected square (the forecast for the last year provides an error of 3.5 %) are given. After many runs of the script, it was found that the best result is provided by a perceptron with two hidden layers and two neurons in each layer. The results of the calculations indicate a high correlation of the data for determining the percentage of forest that will be cut down in a certain square. Application of this perceptron for forecasting for the last year showed an error of 3 %.

Nano-iron and AM fungi inoculation in dryland wheat field: A sustainable alternative to plastic film mulching

ContextPlastic film mulching is a primary cultivation measure in the dryland agricultural areas of northwest China, but comes with the drawback of plastic pollution. To overcome this issue, the biological inoculants such as arbuscular mycorrhizal (AM) with nanotechnology might be a critical pathway, but their positive effects on plants are context-dependent and vary with species, application method, concentration, size, surface charge, and other physio-chemical properties. There is so far limited information available on the combined effects of AM fungi with nanoparticles in agriculture. ObjectivesThis study aimed to investigate the potential of iron nanoparticles (FeNPs) in combination with AMF regarding wheat productivity maintenance and its driving mechanism. MethodsHerein, we used a completely randomized block design for the field experiments in the years 2018 and 2019. We conducted two field experiments using nanopriming of seeds with iron nanoparticles (FeNPs) and AMF in two growing seasons in 2018 and 2019 on wheat (Triticum aestivum L., cv. Longchun29) in the field. Each plot had a 5 m × 5 m total area having 6 rows of 0.2 m spacing and 0.5 m buffer strip among the neighboring plots. There were 8 treatments in the field experiment, and each treatment was repeated 3 times, including four nano iron concentration seed soaking treatments (0 mg L-1, 5 mg L-1, 10 mg L-1, 15 mg L-1) and two inoculation treatments of arbuscular mycorrhizal fungi (inoculated with Gi and non-inoculated). ResultsCombined treatments with arbuscular mycorrhizal fungi and iron nanoparticles led to significant increases in wheat biomass and yield across 2018 and 2019. When compared with control treatment there was an increase of 111% in biomass for the year 2018 and a 102% increase was observed for the year 2019; while the increase in the yield percent when compared to control was 91% in 2018 and 85% in 2019 respectively. Water use efficiency for yield (WUE) increased by 92% in 2018 and 57% in 2019. The colonization rate of AMF + FeNPs 10 mg L-1 treatment increased by 223%, 88%, and 211%, respectively compared with control at the jointing, anthesis, and maturity stage in 2018; and increased by 48%, 37%, and 56% respectively in the year 2019. FeNPs at 10 mg L-1 led to small increases in total organic carbon (TOC), total nitrogen (TN), microbial biomass carbon and nitrogen (MBC), and (MBN), in both growing seasons, and AMF inoculation further significantly increased these carbon fractions by 2.6%, 20%, 21% and 26% in 2018; while 1.3%, 14.8%, 12.5%, and 35% in 2019 respectively. ConclusionThe combined treatments of FeNPs and AMF at an optimal concentration (10 mg L-1) significantly increased net economic income by 229% in 2018 and 138% in 2019 when compared to the control. In this study, wheat aboveground biomass and yield and other related parameters have been improved under field trials, which verified that AMF inoculation alongside FeNPs, can play a beneficial role in promoting dryland spring wheat. ImplicationsTaken together, the co-inoculation with FeNPs and AMF displayed a promising perspective in green production with the potential replacement of plastic film mulching in semiarid dryland regions.

Sustainable Agriculture in the Face of Climate Change: Exploring Farmers’ Risk Perception, Low-Carbon Technology Adoption, and Productivity in the Guanzhong Plain of China

Agriculture is a significant contributor to global greenhouse gas emissions, and reducing carbon emissions in this sector is essential for mitigating global warming. To achieve China’s targets of carbon peak by 2030 and carbon neutrality by 2060, promoting low-carbon agricultural technology (LCAT) is fundamental. This study examines the impact of farmers’ risk perception on LCAT adoption behavior and its productivity effects with the Ordered Probit regression method, using micro survey data from 531 farmers in Shaanxi Province, China. The results show that farmers with stronger risk perceptions were more likely to adopt LCAT, based on their loss aversion characteristics. Additionally, farmers’ perceptions of yield, market, and climate risks positively influence the adoption of LCAT, with market risk perception having the strongest effect. Adopting LCAT has significant production and spillover effects, improving the output rate of farmers’ operating farmland and neighboring plots by 2.4% and 1.2%, respectively, for each additional measure adopted. This study contributes to the perception and loss aversion literature by examining farmers’ adoption of low-carbon agricultural practices. This study sheds light on the importance of risk perception in the adoption of sustainable agricultural practices and can inform policies aimed at promoting the adoption of LCAT for achieving sustainable agriculture and mitigating climate change, highlighting the crucial role of sustainable environmental management in the agricultural sector.

Circular designs for total effects under interference models

This paper studies circular designs for interference models, where a treatment assigned to a plot also affects its neighboring plots within a block. For the purpose of estimating total effects, the circular neighbor balanced design was shown to be universally optimal among designs which do not allow treatments to be neighbors of themselves. Our study shows that self-neighboring block sequences are actually the main ingredient for an optimal design. Here, we adopt the approximate design framework and study optimal designs in the whole design space. Our approach is flexible enough to accommodate all possible design parameters, that is the block size and the number of blocks and treatments. This approach can be broken down into two main steps: the identification of the minimal supporting set of block sequences and the optimality condition built on it. The former is critical for reducing the computational time from almost infinity to seconds. Meanwhile, the task of finding the minimal set is normally achieved through numerical methods, which can only handle small block sizes. Our approach is of a hybrid nature in order to deal with all design sizes. When block size is not large, we provide explicit expressions of the minimal set instead of relying on numerical methods. For larger block sizes when a typical numerical method would fail, we theoretically derived a reasonable size intermediate set of sequences, from which the minimal set can be quickly derived through a customized algorithm. Taking it further, the optimality conditions allow us to obtain both symmetric and asymmetric designs. Lastly, we also investigate the trade-off issue between circular and noncircular designs, and provide guidelines on the choices.

Design of Agricultural Field Experiments Accounting for both Complex Blocking Structures and Network Effects

We propose a novel model-based approach for constructing optimal designs with complex blocking structures and network effects for application in agricultural field experiments. The potential interference among treatments applied to different plots is described via a network structure, defined via the adjacency matrix. We consider a field trial run at Rothamsted Research and provide a comparison of optimal designs under various different models, specifically new network designs and the commonly used designs in such situations. It is shown that when there is interference between treatments on neighboring plots, designs incorporating network effects to model this interference are at least as efficient as, and often more efficient than, randomized row–column designs. In general, the advantage of network designs is that we can construct the neighbor structure even for an irregular layout by means of a graph to address the particular characteristics of the experiment. As we demonstrate through the motivating example, failing to account for the network structure when designing the experiment can lead to imprecise estimates of the treatment parameters and invalid conclusions.Supplementary materials accompanying this paper appear online.

Экологическая оценка влияния разного состава почвогрунта и травосмеси на состояние модельных газонов в условиях Москвы

The paper presents the results of field experimental studies of model lawns with varying composition of soil and grass mixtures conducted at the Ecological Station of the Timiryazev Agricultural Academy in the Timiryazevsky district of Moscow with an ecological assessment of the effect of soil composition with a different ratio of peat, sand and loam on the growth of grass biomass. The conducted research has shown the real possibility of significant savings of peat (up to 50%) when creating peat-sandy soils without reducing the productivity of the grass stand formed on the lawn. However, a further decrease in the specific volume of peat in the created soil to one third of the total volume negatively affects the productivity of the lawn grasses, reducing it by 20-25%. The use of excavated loam extracted in the neighboring plots to the lawn to create lawn soils in addition to the peat-sand mixture, unfortunately, is not able to compensate for the decrease in soil productivity with a sharp reduction in the use of peat. Additionally, there are observed differences in the content of a set of heavy metals (Cu, Cr, Pb and Zn) with an increase in the proportion of sand and loam in the composition of lawn soil, and also when using deicing reagents. Keywords: BIOMASS GROWTH, ECOLOGICAL ASSESSMENT, ECOLOGICAL MONITORING, DEICING REAGENTS, HEAVY METALS, LAWN ECOSYSTEMS, LAWN SOIL, MOSCOW

Bridging the gap between microclimate and microrefugia: A bottom-up approach reveals strong climatic and biological offsets.

In the context of global warming, a clear understanding of microrefugia-microsites enabling the survival of species populations outside their main range limits-is crucial. Several studies have identified forcing factors that are thought to favor the existence of microrefugia. However, there is a lack of evidence to conclude whether, and to what extent, the climate encountered within existing microrefugia differs from the surrounding climate. To investigate this, we adopt a "bottom-up" approach, linking marginal disconnected populations to microclimate. We used the southernmost disconnected and abyssal populations of the circumboreal herbaceous plant Oxalis acetosella in Southern France to study whether populations in sites matching the definition of "microrefugia" occur in particularly favorable climatic conditions compared to neighboring control plots located at distances of between 50 to 100 m. Temperatures were recorded in putative microrefugia and in neighboring plots for approximately 2 years to quantify their thermal offsets. Vascular plant inventories were carried out to test whether plant communities also reflect microclimatic offsets. We found that current microclimatic dynamics are genuinely at stake in microrefugia. Microrefugia climates are systematically colder compared to those found in neighboring control plots. This pattern was more noticeable during the summer months. Abyssal populations showed stronger offsets compared to neighboring plots than the putative microrefugia occurring at higher altitudes. Plant communities demonstrate this strong spatial climatic variability, even at such a microscale approach, as species compositions systematically differed between the two plots, with species more adapted to colder and moister conditions in microrefugia compared to the surrounding area.

Effects of topographic variability and forest attributes on fine-scale soil fertility in late-secondary succession of Atlantic Forest

BackgroundUnderstanding how soil fertility changes due to topographical conditions and forest attributes is an essential premise for local-scale forest management practices. We evaluated the effects of topographic variables and forest attributes on soil fertility along a local topographical gradient in a Brazilian Atlantic Forest. We hypothesised that soil fertility is positively affected by topographic variability and forest attributes (structure and diversity). We used tree species richness, composition, abundance, and aboveground biomass as forest attributes. We analysed two 1-ha forest patches with contrasting topographical conditions. We used different linear mixed effects models (LMMs) to test the main effects of different forest attributes and topography variables on soil fertility.ResultsThe results showed that higher topographic variability determines soil fertility along a fine-scale gradient. The first two axes of the PCA explained 66.8% of the variation in soil data, with the first axis (PCA1) explaining 49.6% of the variation in soil data and positively correlating with fertility-related soil properties. The second axis (PCA2) explained 17.2% of the variation in topographical data and positively correlated with convexity (the elevation of a plot minus the average elevation of all immediate neighbour plots) and elevation. Our best models showed that topographic variables (elevation and convexity) are the main predictors that affect fine-scale soil fertility.ConclusionsOur study demonstrates that the topographic variability, mainly elevation and convexity, determines fine-scale soil fertility in an Atlantic Forest. These results advance our understanding that context-dependent conditions based on topography and soil properties have a high variability at a fine scale, which can influence variations in forest attributes (i.e., species distribution, diversity and structure of tree communities). In addition, the information generated in this research may be important for planning forest restoration activities (passive and active) based on the high variability of environmental variables at a fine scale.

Accumulation of C4‐carbon from Miscanthus in organic‐matter‐rich soils

AbstractTo evaluate the sustainability of biomass plantations, effects on soil organic carbon (SOC) need to be quantified. Miscanthus × giganteus is increasingly used as a bioenergy plant, and it has been hypothesized that, after conversion from cropland, Miscanthus cropping increases SOC storage, whereas conversion from grassland to Miscanthus provides, on average, no sequestration. All field studies hitherto were carried out on mineral soils with topsoil SOC contents of below 3.3%. Here, we analyze in the temperate zone of Switzerland five sites that have been cultivated with Miscanthus for 19–24 years and of which four sites are higher in topsoil SOC content (4.7%–16.2%) and storage (188–262 t SOC) than any previously studied Miscanthus plantation in Europe. We used the difference in carbon isotopic signature between C4 (Miscanthus) and neighboring plots with C3 vegetation (grassland) to quantify the accumulation of new SOC from Miscanthus down to 0.75 m. Annual C4‐C accumulation rates were 1.66 (standard error ± 0.14) t C4‐C ha−1 year−1 (range: 1.26–2.01) in the upper 0.3 m of soil and 1.96 (±0.18) t C4‐C ha−1 year−1 (1.40–2.38) in 0–0.75 m. Average rates for 0–0.3 m were higher than those of mineral soils (n = 37) published previously (0.96 [±0.10] t C4‐C ha−1 year−1). However, high rates of C4‐C accumulation were also reported previously for some mineral soils. Nevertheless, the one mineral soil in our study did not reveal a systematically different accumulation of Miscanthus‐derived carbon compared with the four carbon‐rich soils. We therefore conclude that soils rich in organic matter do not show a different C4‐C accumulation pattern as compared with mineral soils. However, their C4‐C accumulation rates are at the upper end of the data ensemble. Our results further underpin that conversion to Miscanthus, despite C4‐C accumulation, provides no means to increase soil carbon stocks relative to grassland management.

Approximate and exact designs for total effects

This paper considers both approximate and exact designs for estimating the total effects under one crossover and two interference models. They are different from the traditional block designs in the sense that the assigned treatments also affect their neighboring plots, hence a design is understood as a collection of sequences of treatments. A notable result in literature is that the circular neighbor balanced design (CNBD) is optimal among designs, which do not allow treatments to be neighbors of themselves. However, we find it necessary to allow self-neighboring, and further show that it is the best to allocate each treatment in a subblock of adjacent plots with equal or almost equal numbers of replications. This explains why the efficiency of CNBD drops down to 50% as the sequence length, say k, increases. Unlike CNBD or the designs for direct effects, our proposed designs do not try to put as many treatments in a sequence as possible. The optimal number of distinct treatments in a sequence is around 2k for crossover designs and k/0.96 for interference models, whenever they are smaller than the total number of treatments under consideration. We systematically study necessary and sufficient conditions for any design to be universally optimal under the approximate design framework, based on which algorithms for deriving optimal or efficient exact designs are proposed. This hybrid nature of cohesively combining theories with algorithms makes our method more flexible than existing ones in the following aspects. (i) Not only symmetric designs are studied, general procedures for producing asymmetric designs are also provided. (ii) Our method applies to any form of within-block covariance matrix instead of specific forms. (iii) We cover all configurations of the numbers of treatments and sequence lengths, especially for large values of them when purely computational methods are not applicable. (iv) On top of the latter, we cover a continuous spectrum of the number of sequences instead of special numbers decided by combinatorial constraints.

Climate field schools to increase farmers’ adaptive capacity to climate change in the southern coastline of Java

Abstract Demonstration plots (demo plots) have been used as participatory research methods to conduct Climate Field Schools (CFS) with farmers from May to October 2018. CFS aimed at improving the adaptive capacities of the farmers and obtaining appropriate technologies to be adopted in the two villages of Ciganjeng and Rawaapu. The demo plots were set up with a different treatment of organic manure (T1 = 10 ton ha−1 of cattle compost; T2 = 10 ton ha−1 of cattle compost + 10 ton ha−1 of Azolla pinnata; and T3 = 10 ton ha−1 of cattle compost + 2 ton ha−1 of Sesbania rostrata) and different rice varieties. The farmers were fully responsible for the monitoring of the parameters (e.g., plant height, number of tillers, and grain yield). The demo plots results revealed that the application of organic manure T2 has increased the soil C and N content by 64.6 and 40.00%, respectively, and rice yield by 27.8% compared to neighboring plots using inorganic fertilizers. The Mendawak variety at both CFS locations showed better performance compared to the other varieties. Moreover, the capacity of the research farmers involved in the CFS has been increased by 52.74% with a gain factor of 0.42 in Ciganjeng and 41.23% with a gain factor of 0.39 in Rawaapu moderately based on pretest and posttest results. It is concluded from the research process that farmers who built up their capacity on on-farm show a high level of confidence and can convey comprehensive information to other farmers.

Universally Optimal One-sided Circular Neighbour-balanced Designs with k = 5

In many experiments, especially in agriculture and horticulture to some extent, the response from a plot in a block is affected by treatments on forward (backward) neighbour plots in the same block. Under such circumstances, one-sided circular neighbour-balanced design (one-sided CNBD) has wide applications. However, in concern with the universal optimality, there are very limited number of known series of one-sided CNBD’s. The purpose of this article is to present a new series of universally optimal one-sided CNBD with block size 5 where if a treatment appears repeatedly in a block, all of them are in a series of adjacent plots in the block.

Are native and non-native pollinator friendly plants equally valuable for native wild bee communities?

Bees rely on floral pollen and nectar for food. Therefore, pollinator friendly plantings are often used to enrich habitats in bee conservation efforts. As part of these plantings, non‐native plants may provide valuable floral resources, but their effects on native bee communities have not been assessed in direct comparison with native pollinator friendly plantings. In this study, we performed a common garden experiment by seeding mixes of 20 native and 20 non‐native pollinator friendly plant species at separate neighboring plots at three sites in Maryland, USA, and recorded flower visitors for 2 years. A total of 3,744 bees (120 species) were collected. Bee abundance and species richness were either similar across plant types (midseason and for abundance also late season) or lower at native than at non‐native plots (early season and for richness also late season). The overall bee community composition differed significantly between native and non‐native plots, with 11 and 23 bee species being found exclusively at one plot type or the other, respectively. Additionally, some species were more abundant at native plant plots, while others were more abundant at non‐natives. Native plants hosted more specialized plant–bee visitation networks than non‐native plants. Three species out of the five most abundant bee species were more specialized when foraging on native plants than on non‐native plants. Overall, visitation networks were more specialized in the early season than in late seasons. Our findings suggest that non‐native plants can benefit native pollinators, but may alter foraging patterns, bee community assemblage, and bee–plant network structures.

Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers.

The mechanisms sustaining myocardial fibrillation remain disputed, partly due to a lack of mapping tools that can accurately identify the mechanism with low spatial resolution clinical recordings. Granger causality (GC) analysis, an econometric tool for quantifying causal relationships between complex time-series, was developed as a novel fibrillation mapping tool and adapted to low spatial resolution sequentially acquired data. Ventricular fibrillation (VF) optical mapping was performed in Langendorff-perfused Sprague-Dawley rat hearts (n=18), where novel algorithms were developed using GC-based analysis to (1) quantify causal dependence of neighboring signals and plot GC vectors, (2) quantify global organization with the causality pairing index, a measure of neighboring causal signal pairs, and (3) localize rotational drivers (RDs) by quantifying the circular interdependence of neighboring signals with the circular interdependence value. GC-based mapping tools were optimized for low spatial resolution from downsampled optical mapping data, validated against high-resolution phase analysis and further tested in previous VF optical mapping recordings of coronary perfused donor heart left ventricular wedge preparations (n=12), and adapted for sequentially acquired intracardiac electrograms during human persistent atrial fibrillation mapping (n=16). Global VF organization quantified by causality pairing index showed a negative correlation at progressively lower resolutions (50% resolution: P=0.006, R2=0.38, 12.5% resolution, P=0.004, R2=0.41) with a phase analysis derived measure of disorganization, locations occupied by phase singularities. In organized VF with high causality pairing index values, GC vector mapping characterized dominant propagating patterns and localized stable RDs, with the circular interdependence value showing a significant difference in driver versus nondriver regions (0.91±0.05 versus 0.35±0.06, P=0.0002). These findings were further confirmed in human VF. In persistent atrial fibrillation, a positive correlation was found between the causality pairing index and presence of stable RDs (P=0.0005,R2=0.56). Fifty percent of patients had RDs, with a low incidence of 0.9±0.3 RDs per patient. GC-based fibrillation analysis can measure global fibrillation organization, characterize dominant propagating patterns, and map RDs using low spatial resolution sequentially acquired data.

Property Rights Without Transfer Rights: A Study of Indian Land Allotment

Governments often place restrictions on the transferability of property rights to protect property owners from making “mistakes” such as selling their property under value. However, these restrictions entail costs: they reduce the property’s value as collateral in credit markets, limit owners’ ability and incentives to invest in the land, and create various transaction costs that constrain optimal land use. We investigate these costs over the long run, using a natural experiment whereby millions of acres of reservation lands were allotted to Native American households under differing land-titles between 1887–1934. We compare non-transferable land plots to neighboring plots held with full property rights, using fine-grained satellite imagery to study differences in land development and agricultural activity from 1974–today.

Pseudomonas simiae effects on the mycotoxin formation by fusaria and alternaria in vitro and in a wheat field.

Fluorescent pseudomonads colonizing wheat ears have a high antagonistic potential against phytopathogenic fungi. To check this hypothesis, the bacterial antagonist Pseudomonas simiae 9 rif+/kan+ was spray-inoculated onto the ears of winter wheat in a locally demarcated experimental field plot. Fusarium and Alternaria fungi naturally occurring on the ears and the formation of their mycotoxins in the ripe grains were investigated. Inoculated bacteria were recovered from the plants in the inoculation cell, but not in the untreated neighboring plots or in the air above the plants. Growth of fusaria and alternaria on the ears was not influenced by the bacterial antagonist. Wheat kernels were co-inoculated in vitro with the antagonist and one mycotoxin-producing strain of Fusarium and Alternaria, respectively. Mycotoxin production was almost completely suppressed in these approaches. Concentrations of zearalenone, deoxynivalenol, alternariol, and tenuazonic acid were also significantly reduced in ripe grains in the field, but to a lesser extent than in vitro. The results of this and previous studies suggest that widespread biological control of the growth of fusaria and alternaria and their mycotoxin formation by naturally occurring pseudomonads with antagonistic activity is rather unlikely.

A neighbor balanced design and its optimal certainty contribution

Specially in an agricultural design of experiment, the nature of the treatments may be such that the treatment received by a plot may influence the responses on the neighboring plots or the following plot in the same block. As an example of the second condition, the tall varieties may affect the other crops grown on the neighbor plots by their shades. Bailey ((2003). Designs for one-sided neighbor effect, Jour. Ind. Soc. Ag. Statistics, 56(3), 302–314) has developed such design concerned with the study of one sided neighbor effect, under the above mentioned second condition. This paper gives a new series of Universally Optimal One-Sided Circular Neighbor Balanced Designs.

Aerial Imagery Analysis - Quantifying Appearance and Number of Sorghum Heads for Applications in Breeding and Agronomy.

Sorghum (Sorghum bicolor L. Moench) is a C4 tropical grass that plays an essential role in providing nutrition to humans and livestock, particularly in marginal rainfall environments. The timing of head development and the number of heads per unit area are key adaptation traits to consider in agronomy and breeding but are time consuming and labor intensive to measure. We propose a two-step machine-based image processing method to detect and count the number of heads from high-resolution images captured by unmanned aerial vehicles (UAVs) in a breeding trial. To demonstrate the performance of the proposed method, 52 images were manually labeled; the precision and recall of head detection were 0.87 and 0.98, respectively, and the coefficient of determination (R2) between the manual and new methods of counting was 0.84. To verify the utility of the method in breeding programs, a geolocation-based plot segmentation method was applied to pre-processed ortho-mosaic images to extract >1000 plots from original RGB images. Forty of these plots were randomly selected and labeled manually; the precision and recall of detection were 0.82 and 0.98, respectively, and the coefficient of determination between manual and algorithm counting was 0.56, with the major source of error being related to the morphology of plants resulting in heads being displayed both within and outside the plot in which the plants were sown, i.e., being allocated to a neighboring plot. Finally, the potential applications in yield estimation from UAV-based imagery from agronomy experiments and scouting of production fields are also discussed.

Is Land Fragmentation Facilitating or Obstructing Adoption of Climate Adaptation Measures in Ethiopia?

Land fragmentation is high and increasing in the Gamo Highlands of southwest Ethiopia. We postulate that this substantial land fragmentation is obstructing the adoption of sustainable land management practices as climate adaptation measures. To explore this, a mixed method study was conducted with emphasis on a multivariate probit model. The results indicate that farmers adapt to climate change and variability they perceive. According to the probit model, there is no clear answer to the question whether land fragmentation facilitates or obstructs adoption of sustainable land management practices. Yet, a qualitative analysis found that farmers perceive land fragmentation as an obstacle to land improvement as adaptation strategy. Moreover, farmers invest more in land improvement on plots close to their homestead than in remote plots. However, the higher land fragmentation also promoted crop diversification, manure application and terracing. Although exogenous to farmers, we therefore suggest that land fragmentation can be deployed in climate change adaptation planning. This can be done through voluntary assembling of small neighboring plots in clusters of different microclimates to encourage investment in remote fields and to collectively optimize the benefits of fragmentation to adaptation.

Sustained Bauxite Residue Rehabilitation with Gypsum and Organic Matter 16 years after Initial Treatment.

Bauxite residue is a high volume byproduct of alumina manufacture which is commonly disposed of in purpose-built bauxite residue disposal areas (BRDAs). Natural waters interacting with bauxite residue are characteristically highly alkaline, and have elevated concentrations of Na, Al, and other trace metals. Rehabilitation of BRDAs is therefore often costly and resource/infrastructure intensive. Data is presented from three neighboring plots of bauxite residue that was deposited 20 years ago. One plot was amended 16 years ago with process sand, organic matter, gypsum, and seeded (fully treated), another plot was amended 16 years ago with process sand, organic matter, and seeded (partially treated), and a third plot was left untreated. These surface treatments lower alkalinity and salinity, and thus produce a substrate more suitable for biological colonisation from seeding. The reduction of pH leads to much lower Al, V, and As mobility in the actively treated residue and the beneficial effects of treatment extend passively 20-30 cm below the depth of the original amendment. These positive rehabilitation effects are maintained after 2 decades due to the presence of an active and resilient biological community. This treatment may provide a lower cost solution to BRDA end of use closure plans and orphaned BRDA rehabilitation.