Potential and Limits of Pesticide Free Apple Growing by a Self-Regulating Orchard Set-Up: Project Presentation and First Experiences

Different research groups have already proven that flowering plants in orchards can enhance beneficial arthropods. Even within the tree rows different beneficial can be supported by selected plant species. In most experimental work done to stabilize the apple production system only single interaction effects were tested. However until now, no research group has quantified the additive effects of multiple measures on systembiodiversity and on the production economy. Our experiment combines all known measures of indirect pest and disease control measures in a near-to practical production model orchard without the use of any pesticide (not even organic ones). The orchard is split in 4 blocks: in two of them bio-control measures e.g. application of Granulosis Virus against codling moth (C. Pomonella) are applied; in the other two blocks no bio-control is applied. Standard commercial organic and integrated orchards with the disease-susceptible cultivar Gala in the vicinity of the model orchard are assessed by the same methods and serve as reference. Our intermediate results reveal that the self-regulating orchard developed already in the 2nd and 3rd leaf a clearly higher flora and fauna biodiversity compared to the reference orchards. The same happened in relation to the specific fruit beneficial e.g. the populations of aphid predators. In the self-regulating orchard they were capable to keep the aphid damages – in particular of the powdery apple aphid (D. plantaginea) - on trees and fruits under a commercially relevant level although the initial abundance of aphid colonies in spring was by far over the common threshold value. It is planned to continue the experiment until 2016

California Almond Yield Prediction at the Orchard Level With a Machine Learning Approach.

California's almond growers face challenges with nitrogen management as new legislatively mandated nitrogen management strategies for almond have been implemented. These regulations require that growers apply nitrogen to meet, but not exceed, the annual N demand for crop and tree growth and nut production. To accurately predict seasonal nitrogen demand, therefore, growers need to estimate block-level almond yield early in the growing season so that timely N management decisions can be made. However, methods to predict almond yield are not currently available. To fill this gap, we have developed statistical models using the Stochastic Gradient Boosting, a machine learning approach, for early season yield projection and mid-season yield update over individual orchard blocks. We collected yield records of 185 orchards, dating back to 2005, from the major almond growers in the Central Valley of California. A large set of variables were extracted as predictors, including weather and orchard characteristics from remote sensing imagery. Our results showed that the predicted orchard-level yield agreed well with the independent yield records. For both the early season (March) and mid-season (June) predictions, a coefficient of determination (R 2) of 0.71, and a ratio of performance to interquartile distance (RPIQ) of 2.6 were found on average. We also identified several key determinants of yield based on the modeling results. Almond yield increased dramatically with the orchard age until about 7 years old in general, and the higher long-term mean maximum temperature during April-June enhanced the yield in the southern orchards, while a larger amount of precipitation in March reduced the yield, especially in northern orchards. Remote sensing metrics such as annual maximum vegetation indices were also dominant variables for predicting the yield potential. While these results are promising, further refinement is needed; the availability of larger data sets and incorporation of additional variables and methodologies will be required for the model to be used as a fertilization decision support tool for growers. Our study has demonstrated the potential of automatic almond yield prediction to assist growers to manage N adaptively, comply with mandated requirements, and ensure industry sustainability

Evaluating the adaptive capacity of cultural landscapes to climate change: Incorporating site-specific knowledge in National Park Service vulnerability assessments

Cultural landscapes are complex systems of natural and cultural resources that are affected by changes in climatic and non-climatic factors. The National Park Service, Pacific West Region, has developed a vulnerability assessment (VA) model for identifying, evaluating, and responding to the effects of climate change to cultural landscapes by utilizing peer-reviewed data and local knowledge to inform management strategies that can reduce the vulnerability of cultural landscapes to deterioration and loss. Key to developing site-specific adaption plans is a VA based on analysis of the significance, exposure, and sensitivity of landscape characteristics and features, and identification of the management capacity to reduce the sensitivity of the cultural landscape to change. The resulting assessment compares the level of projected vulnerability of the landscape as a whole and of each characteristic or feature under evaluation, and the identification of methods for minimizing the sensitivity of the cultural landscape to climate change. This paper provides an overview of the VA model through case studies from the state of Washington, the territory of Guam, and Tinian, commonwealth of the Northern Marianas Islands

Soil water use by apple trees : a thesis presented in partial fulfillment of the requirements for the Master of Agricultural Science in Soil Science at Massey University, New Zealand

The study investigated the soil water use of an unirrigated tree and an irrigated apple tree in Hawke's Bay, New Zealand in the middle of the summer of 1988/1989. A rainout shelter was used to eliminate any water inputs from both irrigation and rain to the unirrigated tree. The irrigated tree received water inputs from both irrigation and rain. The soil water content was measured by neutron probing and time domain reflectometry. The heat pulse technique was used to measure the sap-flow in the apple trunks. Both leaf water pressure potential and stomatal resistance were measured by the pressure chamber and porometer respectively. A measuring cylinder was used to monitor the apple growth during the study. The results of the water use measurements were that - the neutron probing and time domain reflectometry showed the soil water use was about 77 litres (4.3 mm) per day taken from 0 - 1900 mm depth around the irrigated tree. However soil water extraction around the unirrigated tree was only 19 litres (1 mm) per day at the beginning of the study, and no water extraction was measured from the top 1900 mm later in the study. - the heat pulse technique showed that the unirrigated tree extracted slightly more soil water than the irrigated tree. The average sap-flow measured was 66 litres per day. Probably the unirrigated tree extracted much of its water from below 1900 mm depth, or from beyond the covered area. - the amount of water use by the apple trees was similar to regional evaporation estimates obtained using the Priestley - Taylor formula, when 0.66 fractional canopy cover was assumed. The water stress monitoring showed that a pressure chamber technique was a more sensitive way to monitor ress than was porometry. e leaf water pressure potential values showed a significant difference between the irrigated and the unirrigated apple tree ring the latter part of the study. The readily available soil water storage capacity from 0 to 400 depth (the most active part of the root zone) , from 0 - 1000 mm h, and from 0 to 1900 mm, was about 36 mm, 89 mm and 170 mm actively. When there was a lack of available soil water on the oil, the root system was forced to extract soil water from deep in soil profile. The comparison of apple fruit growth showed that during the last days of the study, the apples on the unirrigated tree grew more ly than those on the irrigated tree

Predicting soil erosion after land use changes for irrigating agriculture in a large reservoir of southern Portugal

The construction of the Alqueva reservoir in a semi-arid Mediterranean landscape brought new opportunities for irrigated farming. Land use changes and climate change may alter the risk of soil erosion that was not predicted in the initial development plans and decrease the lifetime of the investment. A comprehensive methodology that integrates the Revised Universal Soil Loss Equation (RUSLE) and geographic information system was adopted to study the effect on soil erosion of different land-uses of the Alqueva reservoir region. Analysing the soil erosion of each land-use it was obtained the following land use erosion vulnerability: Olive orchard>Vineyard>Montado>Alfalfa. The strong erosion variances that were observed in the study area show the importance of locating the 'hot spots' of soil erosion. Simulated scenarios for the entire area can be used as a basis for site-specific soil conservation plans, to promote sustainable land management practices and to facilitate localized erosion control practices and environmentally friendly farming. (C) 2015 The Authors. Published by Elsevier B.V

Assessing Short‐Term Impacts of Management Practices on N2O Emissions From Diverse Mediterranean Agricultural Ecosystems Using a Biogeochemical Model

Croplands are important sources of nitrous oxide (N2O) emissions. The lack of both long‐term field measurements and reliable methods for extrapolating these measurements has resulted in a large uncertainty in quantifying and mitigating N2O emissions from croplands. This is especially relevant in regions where cropping systems and farming management practices (FMPs) are diverse. In this study, a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC), was tested against N2O measurements from five cropping systems (alfalfa, wheat, lettuce, vineyards, and almond orchards) representing diverse environmental conditions and FMPs. The model tests indicated that DNDC was capable of predicting seasonal and annual total N2O emissions from these cropping systems, and the model\u27s performance was better than the Intergovernmental Panel on Climate Change emission factor approach. DNDC also captured the impacts on N2O emissions of nitrogen fertilization for wheat and lettuce, of stand age for alfalfa, as well as the spatial variability of N2O fluxes in vineyards and orchards. DNDC overestimated N2O fluxes following some heavy rainfall events. To reduce the biases of simulating N2O fluxes following heavy rainfall, studies should focus on clarifying mechanisms controlling impacts of environmental factors on denitrification. DNDC was then applied to assess the impacts on N2O emissions of FMPs, including tillage, fertilization, irrigation, and management of cover crops. The practices that can mitigate N2O emissions include reduced or no tillage, reduced N application rates, low‐volume irrigation, and cultivation of nonleguminous cover crops. This study demonstrates the necessity and potential of utilizing process‐based models to quantify N2O emissions from regions with highly diverse cropping systems

Ecosystem (dis)benefits arising from formal and informal land-use in Manchester (UK); a case study of urban soil characteristics associated with local green space management

Urban soils are subject to anthropogenic influences and, reciprocally, provide benefits and dis-benefits to human wellbeing; for example carbon storage, nutrient cycling and the regulation trace element and contaminant mobility. Collective stewardship of urban green commons provides contemporary examples of the diversity of uses and management of green space in cities and represents a growing movement in user participation in, and awareness of, the importance of urban ecological health. Exploring the range of social-ecological benefits exemplified in the urban environment has generally focused on above-ground processes, with few studies examining the potential for (dis)benefits arising from edaphic characteristics of collectively-managed spaces. An investigation into the influence of formal and informal green space management on carbon fluxes and heavy metal concentrations in urban soils was carried out in Manchester (UK) finding that carbon storage in soils of collectively managed urban green commons (7.15 ±1.42 kg C m⁻²) was significantly greater than at formally managed sites (for example city parks: 5.08 ±0.69 kg C m⁻²), though the latter exhibited reduced losses through CO2 emission. Variation in heavy metal concentrations and mobility were likewise observed, exemplified by the acidification of surface soils by leaf litter at orchard sites, and the resultant increase in the mobility of lead (Pb) and zinc (Zn). The results of this study indicate the importance of small-scale contemporary urban green space management on selected ecosystem services provided by the limited soil resource of cities. Thus, a greater consideration of the effects of horticultural and amenity activities with regards to soil quality/functionality is required to ensure available urban green commons retain or increase their ecological quality over time

Spatial variability of soil properties and soil erodibility in the Alqueva reservoir watershed

The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this end, three areas representative of different land uses (agroforestry grassland, lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while the K factor increased with intensive cultivation. The HJ-Biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. The K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion