Microboring traces in carbonate skeletal fragments deposited in aphotic depths of the oceans are studied, evaluated, and described with respect to their marine ecology and palaeoecology as well as ichnotaxonomy. Sand-size deep sea sediment particles dredged from depths ranging between 600 and 3266 m of the Bermuda Pedestal, Central Atlantic Ocean, the Florida Escarpment, the Mediterranean Sea, the Red Sea and the Indian Ocean were studied. Following ichnological rules, trace fossils are described as ichnogenera and ichnospecies, defined as products of organismal behaviour. This, in our view, refers to the growth habit of microboring organisms in response to environmental stimuli within the substrate they penetrate. The problem of palaeobathymetry is discussed in conjunction with the distinction between light-dependent and light independent microboring organisms, with the emphasis on the latter. We considered this distinction to be important because only the light-dependent microborers have been recognized as indicators of ancient depositional depths, whereas the light-independent ones are expected to occur at any depth, subject to the availability of organic nutrients. Microboring organisms often leave morphologically similar traces due to convergent evolution. Their responses may change during their life cycle; they may produce different traces when pursuing their vegetative vs. reproductive functions. New ichnotaxa are described. All are regarded as organotrophs given their aphotic zone deep sea origin. This work presents the most complete set of deep sea microbial euendolith traces, to date.

The participation of microorganisms in construction and destruction of sedimentary structures is widely recognized, and so is the importance of studying such geological processes in modern systems, where the conditions, participating forces, and the results can be observed and recorded. This information is important for understanding and interpreting corresponding processes if their effects were preserved as part of the fossil record. The present contribution refers to topics discussed during the 9th International Bioerosion Workshop in Rome on Oct. 23–27, 2017, dedicated to the evaluation of microbial traces as paleoecological and paleobathymetric indicators. The paper reviews the habitats, methods of collection, and preparation of samples, followed by observation of extracted microbial euendoliths. This approach is complemented by producing images of three-dimensional display of inhabited microborings in their original positions using resin-casting and double embedding of the microbially invaded substrates. This contribution stresses the value of recognizing the microboring organisms’ identities as a key aspect of the interpretation of their traces. It discusses different and complementary ways of how to achieve such parallel assessments. It reports on the importance of photo-documentation and morphometric evaluation of microbial populations, while avoiding possible artefacts caused by the methods used. The study also briefly summarizes the distribution patterns of microboring organisms and their boring and etching traces along depth profiles. Problems arising in the naming of complex traces and the relation to biological nomenclature are discussed.

Bell pepper (Capsicum annuum L.) plants have a high demand for water and nutrients. Water stress on bell pepper is associated with reduced yields and incidence of blossom-end rot (BER). High irrigation rates are commonly applied to maximize yields. Excessive irrigation rates, however, may negatively affect bell pepper plants. The objective of this study was to evaluate the effects of irrigation rates and calcium fertilization on plant growth and fruit yield and quality. Trials were conducted in the spring of 2001, 2003, and 2005 at the University of Georgia, Tifton Campus. Drip-irrigated bell pepper ('Camelot' or 'Stiletto') plants were grown on black plastic mulch. Plants were irrigated with rates that ranged from 33% to 167% of the rate of crop evapotranspiration (ETc). Results showed that irrigation at 70% ETc (2001), 67% ETc (2003), and 50% ETc (2003) were sufficient to maximize vegetative growth and fruit yield and provided yields similar to those at 100% ETc. Leaf net photosynthesis and stomatal conductance (g(S)) were reduced, and incidence of BER was increased with reduced irrigation rates (33% and 67% ETc). Incidences of soilborne diseases (Pythium spp. and Phytophtora capsici) tended to increase in plants receiving excessive irrigation rates (167% ETc). Irrigation rate also affected fruit quality; incidence of BER and fruit soluble solids were both increased at 33% ETc. Calcium fertilization had no effect on soil water content (SWC), plant growth, and incidence of soilborne diseases, and an inconsistent effect on fruit yield and incidence of BER. In conclusion, there is potential for use of irrigation at rates below 100% ETc. Reduced irrigation diminished the volumes of water applied and provided fruit yields similar to those at 100% ETc. Excessive irrigation rates (167% ETc or above) wasted water and resulted in both higher incidences of soilborne diseases and reduced bell pepper yields.

Vegetation indices based solely on visible reflectance may simplify and decrease the cost of crop growth estimates compared to visible and near-infrared (NIR) indices. Ground-based and aerial visible and visible/NIR vegetation indices based on aerial images were compared for sensitivity to ground cover fraction (GCF) of cotton (Gossypium hirsutum L.) under four irrigation treatments in 2004 and five treatments in 2005 and 2006. In-season cotton imagery was collected using an unmodified Nikon COOLPIX 4300 camera and a COOLPIX 4300 camera modified for NIR imaging attached to a tethered blimp. GCF imagery was collected at 45 to 60 m and compared with normalized difference vegetation index (NDVI) and green/red ratio values from imagery collected at 180 to 250 m. Ground-based (1.5 m) spectrometer NDVI measurements using multiple spectral regions were also evaluated. Spectrometer (r(2) = 0.40 to 0.80) and camera (r(2) = 0.68 to 0.90) indices were highly correlated with season-wide GCF between fractions of 0.20 and 0.80 and were sensitive to irrigation treatments. Camera green/red ratio was linearly correlated with GCF throughout the 3 yr. The pooled comparison for the 3 yr was strongly linear (r(2) = 0.86). Our results suggest that the green/red ratio index might allow quick, simple, and accurate crop growth estimates for production.

State water plans require an assessment of agricultural water demand with enough specificity that regional water planners can anticipate when, where and how much will be needed to support irrigation. Planning for withdrawals with this level of detail begins with an assessment of current withdrawals. While several efforts have been made to identify irrigated areas, each has fallen short of defining a comprehensive map. Widely conflict- ing estimates and maps have created uncertainty and mis- trust. As part of Georgia Environmental Protection Divi- sion-led efforts to conduct assessments of water use for regional planning groups, we sought to pull together re- sults from past efforts into a common irrigation area base- line. Additionally, using 2007 aerial imagery, we have identified additional irrigation systems that were not in- cluded on either record set. Each irrigated area was con- nected with a water source allowing determination propor- tion of withdrawals from surface and groundwater sup- plies by watershed and county. The comprehensive map- ping shows Georgia farmers currently irrigate about 1,400,000 acres of land, mostly in the Coastal Plains.

Although subsurface drip (SSD) is used as a water-efficient alternative to overhead irrigation in many crops, the effects of SSD on the distribution of bolls on cotton plants (Gossypium hirsutum L.) have not been thoroughly examined. The purpose of this study was to add to the current knowledge about the effects of SSD on cotton yield dynamics. Cultivar DP 488 BG/RR was grown in three studies during 2 yr with irrigation treatments consisting of overhead irrigation (Overhead), a nonirrigated control (Non irrigated), SSD matched to overhead irrigation amounts and frequency (SSD Matched), and SSD based on soil moisture (SSD Fed) irrigated cotton. The cotton was grown in two locations in 2004 and one location in 2005 in Georgia. Crop height, maturity, and soil moisture status were monitored throughout the growing season in each location. At harvest, a subplot consisting of one harvest row measuring 3 m in length was removed from each plot and handpicked to determine cotton boll distribution in each plot. Irrigation method had a significant impact on boll distribution on the plants, with the overhead irrigation treatment consistently having less cotton near the bottom of the plant and more cotton near the top than either of the SSD methods. We conclude that SSD irrigation decreases early-season fruit loss, resulting in heavier carbohydrate sinks and decreasing overall growth and upper boll filling on the crop.

Off-the-shelf consumer digital cameras are convenient and user-ftiendly. However, the use of these cameras in remote sensing is limited because convenient methods for concurrently determining visible and near-infrared (NIR) radiation using these cameras have not been developed. Two Nikon Coolpix 4300 digital cameras were evaluated in tandem to determine the effectiveness of a cross-camera calibration procedure that would allow concurrent use of all unmodified digital camera and a NIR-sensitive digital camera without preset shutter speeds or aperture settings. The NIR-sensitive camera was modifted to detect NIR radiation by replacing the internal hot mirror with a Hoya RM72 fillet: Each camera was calibrated at five exposure levels using a Gretag-Macbeth ColorChecker (TM) reflectance panel, and raw camera brightness values were converted to relative reflectance by exposure compensation equations. The method was tested oil a series of 26 diffuse reflectance targets, which also yielded the same exposure compensation relationships. The relationship between camera channel brightness and target re reflectance was nonlinear within each exposure, but sensitivity, was linear between exposures. The procedure was tested oil 36 cotton plots (Gossypium hirsutum) in all irrigation study in 2006. Images obtained oil eight dates during the season were corrected for exposure and converted to relative reflectance values. The normalized difference vegetation index (NDVI) values from the plots were then compared with ground-based spectrometer measurements of NDVI. Corrected camera-based NDVI values were closely correlated with the spectrometer NDVI values (r(2) = 0.72), suggesting that the camera system can more consistently estimate crop reflectance characteristics if exposure compensation is applied.

During 2006, the Flint River Basin Water Conservation and Development Plan (FRBP) and the Coastal Georgia Water and Wastewater Permitting Plan for Managing Saltwater Intrusion (CZP) were adopted by Georgia Environmental Protection Division. Both had big impacts on permitting of agricultural water withdrawals. Moratoria had been in place postponing new permits. With acceptance of the plans, a flood of backlogged appli- cations, some as old as six years, had to be processed. Permit rule changes in the plans or brought about by con- comitant new legislation had to be implemented. The newly formed Agriculture Permitting Unit was relocated to Tifton, and UGA personnel assisted in transforming EPD permitting processes to speed up processing to han- dle the backlog and implement new regional plans. Exist- ing permits and new applications were incorporated into a geodatabase since most permitting decisions are location specific. GIS tools and models were developed to system- atically and objectively evaluate applications, and proce- dures were established to improve the communication between EPD and agricultural applicants.

The amount of water used for irrigation varies as a function of the local weather conditionsand soil type, crop and cultivar selection, crop management, and irrigation strategies, including thetiming and amount of irrigation applications. Among these factors, weather conditions and the soilwaterholding characteristics are often the most important factors that define the spatial variability ofirrigation in a specific region. In Georgia, the amount of water used by agriculture for irrigation islargely unknown because of the lack of reporting requirements. Recent droughts and a water disputewith the neighboring states, including Alabama and Florida, highlighted the need for an accurateestimate of water use by agriculture. The goal of this study was to characterize the spatial variabilityof the monthly irrigation water use for cotton in Georgia using the Cropping System Model (CSM) ofthe Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.0. Farmers' monthlyirrigation applications for cotton during the 2002 growing season were obtained from selected sites ofthe Agricultural Water Pumping program. We selected farmers fields that were located within 15 kmfrom the nearest weather station of the Georgia Automated Environmental Monitoring Network or theCooperative Observer Program (COOP) network of the National Weather Service. We thencompared the spatial and temporal distribution of irrigation amounts predicted by the CSM modelwith the amount of water that the farmers actually applied. The most successful model for spatialestimation of monthly total irrigation was the Spherical model, followed by the Exponential model.The smaller number of sample sites in certain parts of the study area had a significant impact onspatial estimates of monthly total irrigation. This study demonstrated the potential of using a cropmodel combined with geostatistical techniques for estimation of regional water use.

The management of on-farm irrigation systems involves the choice of irrigationmethod, timing, and the quantity of water applications. In Georgia, farmers' irrigationapplications are largely unknown because of no reporting requirement. Recent droughts and awater dispute with the neighboring statesAlabama and Florida highlighted the need for anaccurate estimate of water use by agriculture. An accurate simulation of irrigation water use isneeded to help improve yield predictions and contribute to the resolution of the tri-state waterdispute. The objective of this study was to evaluate the performance of the CSM-CROPGROPeanutmodel in simulating irrigation applications and its impact on peanut yield in farmers'fields in southwest Georgia. A set of different irrigation thresholds was used to run the CSMCROPGRO-Peanut model. We then compared the simulated irrigation applications for each of the irrigation thresholds with the amount of water that the farmers actually applied during the2003 growing season. We found the best agreement between simulated and observed irrigation applications with the50% irrigation threshold. However, the irrigation applications by farmers could be much higherthan with the 50% irrigation threshold during critical stages of crop growth and developmentwhen no adequate rainfall occurs. Similarly, peanut yield was simulated well by the model withthe 50% irrigation threshold. This study showed that the CSM-CROPGRO-Peanut model can bea useful tool for estimating farmers' irrigation applications and its impact on yield. Potential usersof this model could include policy makers, planners, and regulators that deal with water issues.

Crop yield and water demand for irrigation under rainfed and irrigated conditions for fourmajor crops in Georgia were estimated using the Environmental Policy Integrated Climate (EPIC)model. Seasonal yield and irrigation data during 1990-2001 for Tifton, Plains and Midville in theCoastal Plain region, Griffin and Athens in the Piedmont region, and Calhoun in North Georgia wereused for evaluating simulated yield and irrigation. Under rainfed conditions, the model performs fairlywell for different crops, weather and soil conditions across Georgia. In general, the model tends tooverpredict for low yielding conditions and underpredict for high yielding conditions. Under irrigatedconditions, the model overpredicted to a greater extent for low yielding conditions andunderpredicted to a greater extent for high yielding conditions. Only for cotton, the model simulatedthe year-to -year variability in measured irrigation fairly well.

ABSTRACT: Lab studies provide an opportunity to isolate processes influencing water, sediment, and agrichemical transport under standard conditions. However, extending this information to field or watershed scales is often difficult. We compared runoff (R) and sediment (E) losses from a lab study with field data from a Tifton loamy sand (3% slope). Three plot scales/length-rainfall simulator methodologies were used-1.) 0.32 m2 lab pan (L = 0.6m) under an oscillating nozzle rainfall simulator; 2.) 5.5 m2 field plot (L = 3 m) under a Wobbler nozzle rainulator, and 3.) 600 m2 field plots (L = 43 m) under the same rainulator used in method 2. For field plots (methods 2 and 3), R and E losses were measured from six simulated rainfall events (I = 25.4 mm hr−1, 2 hr duration) during two corn growing seasons (five days before agrichemical application and 1, 14, 23, 43, and 108 days after agrichemical application). Similar rainfall intensity and duration were used in the lab study. R and E losses from lab pan (method 1) and 5.5 m2 field plots (method 2) were measured at 5 minute intervals, whereas R and E delivery for 600 m2 plots (method 3) were measured continuously and at selected times, respectively. R and E rates from all method generally increased during each event with similar maximum rates. Total R and E for method 2 was at least an order of magnitude greater than those for method 1, and total R and E for method 3 were at least 1 order of magnitude greater than those for method 2. R and E were related to slope length (R2 = 0.94–0.99). Exponents (b) for R and E were 0.50–1.63. Detachment and transport processes varied spatially. Once a critical slope length was exceeded, rilling occurred Rilling was non existent in method 1 and was present but not dominant in method 2. For method 3, slope length was sufficient to cause rilling, therefore E was greater than that for methods 1 and 2.

High‐intensity storms that occur shortly after chemical application have the greatest potential to cause chemical runoff. We examined how effectively current chemical transport models GLEAMS, Opus, PRZM2β, and PRZM3 could predict water runoff and runoff losses of atrazine [6‐chloro‐ N ‐ethyl‐ N ′‐(1‐methylethyl)‐1,3,5‐triazine‐2,4‐diamine] under such conditions, as compared with observations from a controlled field runoff experiment. The experiment was conducted for 2 yr using simulated rainfall on two 14.6‐ by 42.7‐m plots within a corn ( Zea mays L.) field on Tifton loamy sand (fine‐loamy, kaolinitic, thermic Plinthic Kandiudults) under conventional tillage practices. For each plot‐year, atrazine was applied as surface spray immediately after planting and followed by a 50‐mm, 2‐h simulated rainfall 24 h later. A similar preapplication rainfall and four subsequent rainfalls during the growing season were also applied. Observed water runoff averaged 20% of the applied rainfall. Less runoff occurred from freshly tilled soil or under full canopy cover; more runoff occurred when nearly bare soil had crusted. Observed total seasonal atrazine runoff averaged 2.7% of that applied, with the first posttreatment event runoff averaging 89% of the total. GLEAMS, Opus, PRZM2β and PRZM3 adequately predicted water runoff amounts, with normalized root mean square errors of 29, 29, 31, and 31%, respectively. GLEAMS and PRZM3 predicted atrazine concentrations in runoff within a factor of two of observed concentrations. PRZM2β overpredicted atrazine concentrations. Opus adequately predicted atrazine concentrations in runoff when it was run with an equilibrium adsorption submodel, but significantly underestimated atrazine concentrations when it was run with a kinetic sorption submodel.

Environmental fate models are increasingly used to evaluate potential impacts of agrochemicals on water quality to aid in decision making. However, errors in predicting processes like evapotranspiration (ET), which is rarely measured during model validation studies, can significantly affect predictions of chemical fate and transport. This study compared approaches and predictions for ET by GLEAMS, Opus, PRZM-2, and RZWQM and determined effects of the predicted ET on simulations of other hydrology components. The ET was investigated for 2 years of various fallow–corn growing seasons under sprinkler irrigation. The comparison included annual cumulative daily potential ET (ETp), actual ET, and partitioning of total ET between soil evaporation (Es) and crop transpiration (Et). When measured pan evaporation was used for calculating ETp (the pan evaporation method), Opus, PRZM-2, and RZWQM predicted 74, 65, and 59%, respectively, of the 10-year average ET reported for a nearby site. When the energy-balance equations were used for calculating ETp (the combination methods), GLEAMS, Opus, PRZM-2, and RZWQM predicted 84, 105, 60, and 72% of the reported ET, respectively. The pan evaporation method predicted a similar amount of ET to the combination methods for bare soil, but predicted less ET when both Es and Et occurred. RZWQM reasonably predicted partitioning of ET to Es, while GLEAMS and Opus over-predicted this partitioning. A close correlation between soil water storage in the root zone and ET suggests that accurate soil water content predictions were fundamental to ET predictions. ©