At one border point in Malawi, FEWS NET monitors estimate the volume of informal maize trade tolerated by officials to be 200 metric tons per month. This compares to formal export volumes that have occasionally been as high as 10,000 metric tons or more through this border point in non-ban months. At an unofficial border crossing I visited elsewhere, a single dugout canoe with a capacity of 0.7 metric tons is available to ferry maize between trucks across a river border during bans, allowing for the transport of approximately 1,000 metric tons per month. Theoretically, if capacity constraints are binding during bans, the price gaps between pairs of affected cross-border markets should increase, which I do not observe in the data. However, anecdotal evidence suggests that bans are often lifted in response to complaints from farmers and traders about a lack of trading opportunities following bumper harvests, precisely the time when capacity constraints may start to bind. To assess this possibility, I divide the nine export bans for which I have start-to-finish data into quarters, drop observations from the other four bans, and redo my main specification with separate indicator variables for the first, second, third,fodder system for sale and fourth quarters of export bans. Results in table 2.5 indicate that while price gaps are unchanged in the first three quarters of bans, they do exhibit a small but statistically significant increase in the final quarter of bans.

This suggests that capacity constraints on informal cross-border trade generally only bind at the very end of bans, when large new harvests may make governments amenable to lifting the bans anyway.Of potentially greater concern is that market participants report that the climate of uncertainty created by discretionary export bans with ad hoc enforcement and the diversion of trade away from formal, regulated traders to informal channels during export bans destabilize markets. Faced by fluctuations in bans, permit issuing, and enforcement, both formal and informal traders choose to engage less in long-term storage for future trade, in contractual agreements with cross-border purchasers , and in long-distance trade across far-off borders where they have fewer connections and less local knowledge about informal channels. Instead, they prioritize short term, non-contractual, local transactions. This potentially weakens the capacity of markets to respond efficiently to the harvest shortfalls or price increases that characterize export ban periods. To see whether these destabilizing effects show up in the data, I compute the standard deviation of prices during export ban and non-export ban periods for each origin and destination market and re-run the regressions in equations 2.2 and 2.3 using the standard deviation of prices as my dependent variable . In the data, the standard deviation of prices for origin markets is 36% higher during export bans than its average in non-ban periods , whereas model simulations indicate no significant difference in standard deviation between ban and non-ban periods if the bans had not been implemented.

The point estimate for the standard deviation of prices for destination markets is also much larger in the data than in the “no bans” simulation , but it is not statistically significant at conventional levels and is smaller than the effect in model simulations when bans are implemented and fully enforced. Taken together, my results suggest that export bans are having very different effects than those intended by implementing country governments in East and Southern Africa. Rather than cutting off trade, export bans divert it to the informal sector. Rather than widening price gaps, export bans do not affect them. Rather than maintaining or lowering domestic prices and domestic price volatility, export bans appear to increase both. Export bans may thus be contributing to high and volatile domestic maize prices in a cycle that makes governments all the more inclined to implement them. Pressure from burgeoning population and increasing demand for agricultural production has affected nearly every biome on Earth, and human activity has resulted in detrimental effects in many sensitive ecosystems including important river deltas and peat lands. Peat lands are landscapes characterized by organic soils at least 30–40 cm thick that form over millennia from accumulated biotic materials under conditions of slow decomposition, such as cold temperatures and or prolonged inundation. Because of the unique conditions under which they form, peat lands are sensitive ecosystems highly susceptible to disturbance from climate change and from human use. While peat lands occupy only 3% of the global terrestrial area, their soils contain >25% of the global soil C stocks, making disturbed peat lands a significant source of greenhouse gas emissions.

When organic soils are drained, the land surface subsides due to soil compaction and as a direct result of SOM oxidation and gaseous C losses, with the relative importance of oxidation increasing as the main driver of continued subsidence over time. Despite this potential for severe degradation, 14–20% of peat lands are used for agricultural production worldwide. Subsidence in agricultural peat lands has been reported in New Zealand, Southeast Asia, Florida, USA, Northern Europe, and in the Sacramento-San Joaquin Delta, California, USA among others. Since first being drained in the mid-1800s, the organic soils found in the central part of the Delta have been used primarily for maize , forage, and vegetable production, and have subsided as much as 8 m in many places. Current rates of subsidence in the Delta are generally between 1–3 cm yr-1 and can largely be attributed to microbial oxidation of SOM after soils are permanently drained with further consolidation of the remaining mineral soil concurrent to this oxidation . Cultivation of irrigated paddy rice in the Delta has recently been found to slow soil subsidence—more closely mimicking the naturally flooded state of the peat—relative to currently dominant upland crops such as maize. In addition, temperature buffering effects of flooded soils are particularly valuable during summer, the period of highest potential microbial respiration. However, observations from a rice N fertilizer study on these soils found that N uptake exceeded 200 kg N ha-1 in N fertilizer omission plots, a rate of uptake >30% higher than average N uptake values in fertilized plots for typical California rice. Therefore,fodder growing system we hypothesized that the majority of N uptake was derived from SOM, meaning that mineralization and loss of soil C and N is still occurring under flooded rice production in the Delta. This study was designed to assess an N budget approach for estimating soil C loss rates of peat land soils under flooded rice production. Experiments were designed to isolate and quantify the different sources of N supporting plant uptake—namely SOM, irrigation water, shallow groundwater, and crop residue—to determine the amount of N mineralization from the soil. In turn, net soil C loss was estimated based on the soil C:N ratio and adjusted for C inputs from crop residues.We conducted a study to determine sources of plant available N on Twitchell Island, CA, in the western part of the Delta . The study site is owned by the California Department of Water Resources and leased to farmers for agricultural production. California Department of Water Resources allowed the use of the rice fields on Twitchell Island for this study as well. Twitchell Island currently lies as much as 6 m below sea level and is protected on all sides by artificial levees. The climate is Mediterranean with mild, wet winters and dry summers. From 1998–2013 the mean annual temperature was 9°C minimum and 22°C maximum. Soils at the site are classified as Euic, thermic, TypicHaplosaprists. Total soil C in the experimental sites ranged from 129–154 g kg-1 . In the Delta, rice is typically drill seeded from mid-April to mid-May each season. Due to the relatively cool temperatures compared to the main rice growing region in California’s Sacramento Valley, short duration rice varieties are grown. Fields are flooded approximately 1 month after planting and kept flooded until August/September when they are drained in preparation for harvest.

Following harvest the rice residue is chopped and left on the soil surface over the winter fallow season. To facilitate straw decomposition and provide wildfowl habitat, fields are flooded again from November through February before being drained for land preparation the following spring.An annual N budget was constructed to estimate the amount SOM-N mineralization during the growing and winter fallow seasons . Total mineralization was used to estimate annual soil C loss under rice cultivation. The total annual N budget was comprised of SOM-N mineralized during the growing and winter fallow seasons. Growing season N was determined based on N uptake of total aboveground biomass in N fertilizer omission plots. Several experiments were conducted to determine the contribution of different environmental sources to N uptake. Annual SOM-N mineralization was the sum of growing season SOM-N, and the winter fallow SOM-N mineralization. The soil C:N ratio was used to calculate an annual soil C loss based on the total annual SOM-N mineralized, and net soil C loss was determined by accounting for C inputs from crop residues.Field experiments were conducted during the 2012 growing season at two sites. Throughout the experimental period, the rice variety M-104 was grown and the fields were managed by the farmer following normal rice cultivation practices as described earlier. One difference between Site 1 and 2 was an early season irrigation flush lasting approximately seven days at Site 1 that did not occur at Site 2. N uptake in fertilizer N omission plots. Baseline N uptake was determined from four fertilizer N omission plots at each site. Phosphorous and potassium fertilizer were applied to these plots at 50 kg P2O5 ha-1 and 100 kg K2O ha-1 to ensure these nutrients were not limiting plant growth. For determination of above ground biomass and grain yield, the crop was harvested at physiological maturity by cutting at ground level from a 1.1 to 1.2 m2 area. After weighing, sub-samples were collected, weighed, and dried to a constant weight at 60°C. Grain and straw fractions were separated, ground and analyzed for N content. N derived from residue. The amount of plant N uptake during the 2012 growing season contributed by the previous year’s crop residue was determined using 15N-labeled residue incorporated into the soil in spring 2012. 15N-enriched rice residue was generated by growing rice over winter 2011–2012 in a greenhouse where plants were fertilized with 10 atom % 15N-enriched 2SO4. Above ground biomass was harvested when the plants reached maturity. The grains were removed and the residue was cut into 5–6 cm long pieces to mimic straw chopping in the field. The residue was partially decomposed in deionized water inoculated with Twitchell Island field soil, receiving the same total heat units during decomposition as the corresponding field residue to ensure the 15N-labeled residue approximated the residue that remained on the soil surface under field conditions over the winter fallow. After partial decomposition, the 15N-labeled residue was rinsed with deionized water and air-dried for ease of handling prior to incorporation in the field. The 15N enrichment of labeled rice residue was 9.0693 atom %, and the C:N ratio of the 15N-labeled residue was 41, similar to the field residue which had a C:N of 35 . Before incorporation in the field, 15N-labeled residue was mixed with unlabeled field residue to generate enough total material equivalent to residues remaining in the field after normal winter decomposition. The total application rate was 1310 kg 15N-labeled residue ha-1 and 3700 kg unlabeled field residue ha-1. At the beginning of the 2012 rice season, field residues were removed from the experimental sites by manually raking before tillage. Microplots were delineated and the 15N residue mix was incorporated at a depth of 20 cm after tillage and prior to planting. No-residue, 15N-residue, and 15N-residue + 14N-fertilizer treatments were included, replicated four times in a randomized complete block design at each site. Fertilizer P and K were applied to all treatments at 50 kg P2O5 ha-1 and 100 kg K2O ha-1 to ensure these nutrients did not limit plant growth. At the end of the season, ten tillers were harvested from the center of each microplot for 15N enrichment measurements. Above ground biomass yield samples were harvested from a 0.64 m2 area in the center of each microplot and processed as described above. Four replicate 10-tiller samples were also collected from the area >5 m away from the residue treatment plots in each field to determine background 15N in the crop.