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Transient responses to bio-available fractions may have occurred prior to our first measurement

As attested by the reduced MBC0 but increased CminSoil observed at 42 DAI, the community at this point appeared to be slower growing but better able to metabolize organic matter in an acid environment . A high rate of respiration to growth is a well-documented characteristic of stress adapted microbial communities . Stoichiometrically, a lower community metabolic efficiency could also help explain the observed increase in Nmin-Soil . Significant shifts in community tolerance to acidity have been observed within 36 d , making it plausible that some shift in acid tolerance could be observable within the 42 d under strong acid stress. The tendency towards higher net N mineralization in the S+ soils than the S- soils was much more pronounced with the addition of legume residues. The fact that both C and N mineralization responded so much more strongly to residue additions in the S+ than S- soils despite the former’s higher levels of soluble organic matter suggests that the mineralization pulses were not due to relief of substrate limitation. Since legume residues can complex with Al and reduce its activity , as well as temporarily consume protons through decarboxylation and ammonification of soluble organic acid anions , it is possible that the residues stimulated activity by relieving acid cation toxicity which had been limiting metabolism . As decarboxylation and ammonification produce CO2 and NH4 +, respectively , such detoxification products could also have contributed to the observed mineralization pulses. Liming produced mixed effects on C and N cycling processes. The most obvious effect of liming was a very large CO2 pulse from the unamended soil,growing blueberries in containers far exceeding the DSOC0 pool. It is likely that at least part of this was abiotic, issuing from the decomposition of carbonic acid from the liming reaction to CO2 .

While it is not possible to separate biotically and abiotically generated CO2, the fact that additional respiration due to residues was remarkably similar before and after leaching suggests that liming did not increase the capacity for respiration when adequate substrate was present. Contrary to our hypothesis, MBC0 and potential BG0 activity showed no signs of recovering after alleviation. However, the tendency towards higher MBC-Res with equivalent CO2-Res suggests that the community that grew in response to residue additions after liming was more efficient than that which responded at 42 DAI. The high Nmin-Res during stress and decline after liming suggests that high net N mineralization in response to substrate addition was caused by an inefficient community whose growth was limited by the adaptations required to survive in a stressful environment. Our results are in line with several studies which found that net N mineralization was not inhibited by salinity and acidity to the same extent as C mineralization and nitrification . Indeed, both net and gross N mineralization have sometimes been observed to be highest in the most acid soils within an experimental gradient . Similarly, a 400% increase in net N mineralization from vetch residues was measured in response to Al additions, despite reductions in C mineralization and MBC . The most direct explanation for this effect is that immobilization is slower than mineralization at low pH ; however, this does not always seem to be the case . The fact that the increase in MBC-Res after liming was not proportional to the decline in Nmin-Res suggests that reduced immobilization did not entirely explain the mineralization pulse. Other hypothesized mechanisms include increased losses by denitrification or volatilization as pH increases . Contrary to our hypothesis, compost had no effect on stress response and did not affect most indicators, regardless of S treatment. Compost is generally a stable, microbially processed product, rich in condensed, high molecular weight compounds, phenols and lignin and depleted in energetic compounds such as sugars .

This may explain why it did not have a measurable effect on microbial growth or most activity within our experimental time frame.Conversely, compost strongly and consistently increased Nmin-Res across all three sampling dates. As an increased Nmin-Res was likely a stress response, compost appears to have exacerbated the effects of stress, rather than buffering it as hypothesized. This paradoxical result could be explained if the increased net N mineralization under stress was partly due to a community shift towards one with less need for N relative to C. Fungi tend to have a higher C:N ratio than bacteria and are thought to generally be more acid tolerant . Rapid fungal but not bacterial growth rates have been observed within days of a labile residue addition to acid soils , and high fungal: bacterial ratios have been observed in experimentally acidified grassland soils . Since fungi generally have a wider C:N ratio than bacteria, they immobilize less N per unit C fixed. A faster fungal than bacterial growth response to residue additions could help explain why Nmin-Res values in the S+ treatments were on average more than double those in the S- treatments. The presence of a carbon source such as higher SOM or crop inputs often improves community stress adaptation . Adding compost could have facilitated that stress-induced community shift, such that the organisms which responded to residue additions in the C + S+ soil needed less N than their counterparts in the C-S+ soil . Strong community shifts are not necessarily evident in respiration measurements due to functional redundancy. For example, at the Hoosfield acid strip, fungal growth rates increased 30- fold as pH declined from 8.3 to 4.5, while respiration changed by less than one third . A compost-facilitated shift towards a less N-retentive community would be in line with two recent studies which observed that soils which were fungally dominated due to acid stress tended to use substrate less efficiently . This work presents the first data on the ability of a compost to moderate the effects of acid stress on nutrient cycling.

Green waste compost was chosen for this experiment, as it is typical of the type of compost the production and use of which is predicted to rapidly expand in California . It is important to note that these results may not be typical of all compost types. For example, a strong liming effect has been observed when poultry manure from layer hens was applied to an acid soil, likely due to the calcium carbonate in the feed . However, the strong and unexplained effect on N cycling suggests that further investigation with additional soil and compost types should be pursued. In particular, compost effect on microbial community structure under chemical stress should be investigated further. Additionally, the use of isotopically labeled residues would allow for mechanistic exploration of mineralization and immobilization dynamics. California’s agricultural sector critically affects both the national food supply and regional water resources. California has the largest agricultural sector in the country, producing two thirds of the fruits and nuts in the United States and approximately one third of its vegetables . California’s crop supply is also significant to the United States in that many crops grown in the state, such as almonds, garlic, olives, raisin grapes, pistachios, and walnuts,square pots are exclusively produced there . However, while California’s more than 400 commodities are central to US food supplies, they also necessitate high water inputs. High crop production and a semi-arid climate result in agricultural needs using over eighty percent of the state’s managed water supply . This reliance on irrigated inputs means that yearly crop prices and food supplies in the United States are susceptible to changes in the available water supply of California and impacted by local water management decisions . As California’s water supply becomes increasingly unpredictable due to changes in climate, this interconnection of food and water supplies at local to national scales is ever more important to understand. California’s highly variable water supply is a factor of its natural climatology but is further exacerbated by larger climate trends shaped by manmade influences. California has, for centuries, experienced oscillations between wet and dry periods that result in California having the greatest variations in annual precipitation of any state in the country . However, over the past century, an increase in surface temperature by 0.6-0.7° C has led to changes in California that are attributable to human GHG emissions and further affect water availability: earlier spring snow melt , an increase in percent of precipitation as rain rather than snow , warmer winter and spring temperatures , and less snow accumulation over the last fifty years .

Climate change will continue to augment the patterns of precipitation in California and intensify effects on water resources and agriculture. By early in the 21st century, the Bureau of Reclamation predicts that the Central Valley will experience a 1-degree Celsius rise in annual average temperature and a 2-degree C increase by mid-century that will likely be accompanied by a north-to-south trend of decreasing precipitation . This shift in temperature is projected to increase the frequency, intensity, and duration of droughts over the next century that will make our current water system performance levels impossible to sustain in the Central Valley . One way to prepare for the anticipated increase in drought is to study past events as an indicator of future effects. From 2012 to 2016 California experienced its worst drought in history . Water allotments were cut across the board and farmers, as the users of the majority of the state’s water, were especially hard hit . With the State Water Project and the Central Valley Project allocations cut to zero in some areas, agricultural communities in the Central Valley faced surface water reductions of an estimated 8.1 billion cubic meters a year from 2013 to 2014, amounting to a 36% reduction in surface water availability for farms . The study found that a 62% increase in groundwater extraction partially compensated for the reduction in surface water but threatened the health of California’s aquifers and moreover, still left farmers with an overall deficit of 1.9 bcm/y . This extreme event and climatological anomaly presents an opportunity to better understand how managed crops are impacted by water limitation. As lack of water will be a major limiting factor for agricultural production within the next century , patterns of crop water use and their response to reduced water availability need to be carefully analyzed so impacts to long-term food and water security can be better understood as we move into a new climate regime. Remote sensing provides new opportunities to monitor agricultural change with drought and capture spatial variations and trends in plant water use that traditional on-the ground methods like county-level reporting, lysimeters and eddy flux towers are unable to do given their limited spatial scope and significant time and labor inputs . Current crop monitoring initiatives in the United States primarily rely on imagery from earth-observing satellites such as Landsat , Moderate Resolution Imaging Spectroradiometer and the Advanced Spaceborne Thermal Emission and Reflection Radiometer to map crops and assess health and water use information . However, a new satellite, the Surface Biology and Geology Mission, has been proposed as an improvement in both spatial and spectral performance for ecosystem study . The SBG Mission will combine two sensors, a hyperspectral sensor in the visible through shortwave infrared at a 30 m resolution and a thermal sensor at a spatial resolution of 60 m for global coverage and a 5-19 day revisit. This mission has the potential to improve ability to assist crop and water managers in dynamic and diverse environments, such as the Central Valley of California, with resource accounting and drought response by capturing refined spectral information at a spatial scale that is fine enough to resolve individual fields. With the impending launch of this satellite, it is important to determine its scientific capabilities for routine observation of crops in California at a level that is of use to water managers. To test the capabilities of the SBG sensor, the Hyperspectral Infrared Imager Airborne Campaign flew the Airborne Visible/Infrared Imaging Spectrometer and MODIS/ASTER Airborne Simulator sensors on NASA’s ER-2 plane throughout California from 2013 to 2017 to simulate expected datasets from SBG . AVIRIS is a 224 band imaging spectrometer that captures spectral information from 350 to 2500 nm at ~10 nm increments .

Can You Grow Blueberries Hydroponically

Yes, it is possible to grow blueberries hydroponically, although it can be a bit more challenging compared to other crops. Blueberries are typically grown in soil, and they have specific requirements for soil pH and nutrient levels. When growing blueberries hydroponically,large plastic pots you’ll need to create an environment that mimics their natural soil preferences. Here are some key considerations:

  1. Acidic pH: Blueberries require acidic soil with a pH level between 4.5 and 5.5. In a hydroponic system, you will need to monitor and adjust the pH of the nutrient solution regularly to keep it within this range.
  2. Nutrient Solution: Blueberries have specific nutrient requirements, including elements like iron and manganese, which they may not readily uptake in hydroponic systems. Using a specialized blueberry nutrient solution or carefully adjusting the nutrient mixture to match their needs is essential.
  3. Growing Medium: In hydroponics, you can use various growing mediums like coconut coir, perlite, or a mix of these. Ensure the chosen medium allows for good aeration and drainage.
  4. Lighting: Blueberries require plenty of light, ideally full sun. If you’re growing them indoors or in a controlled environment, provide high-intensity lighting such as LED grow lights to mimic natural sunlight.
  5. Temperature and Humidity: Blueberries prefer cooler temperatures, generally around 60-70°F (15-24°C). Humidity levels should be moderate.
  6. Pruning: Like traditional blueberry bushes, hydroponically grown blueberries benefit from regular pruning to encourage healthy growth and fruit production.
  7. Variety Selection: Some blueberry varieties may be better suited for hydroponic growth than others. Consider researching and selecting varieties that are known for adaptability to controlled environments.
  8. Pollination: If you are growing blueberries indoors, you may need to hand-pollinate the flowers since there may not be natural pollinators like bees indoors.

It’s important to note that hydroponic blueberry cultivation can be more resource-intensive and may require more attention to detail than traditional soil cultivation. You may need to experiment and fine-tune your hydroponic system to meet the specific needs of blueberries. Additionally,plastic pots for plants some blueberry varieties may be better suited to hydroponic cultivation than others, so consult with experienced growers or agricultural experts for advice and guidance specific to your location and setup.

Suppose that the polygyny threshold in equation were satisfied by an equality

In order to produce analytically tractable results, we simplify by assuming throughout that there are only two types of males, rich and poor, with rich males being a fraction u of the population. All rich are identical, as are all poor. The rich males are indexed by r and the poor by p. We now demonstrate two theoretical results with the potential to resolve the polygyny paradox. First, diminishing returns to additional wives arising from causes other than necessity to share a husband’s rival material wealth will reduce the number of wives acquired by each rich male. Second, because of this fact, a highly unequal wealth distribution with few extraordinarily rich men may produce little polygyny, while a less unequal wealth distribution with a larger fraction of rich men may produce a greater extent of polygyny. Two rich men, for example, can be expected to have more wives in total than one very rich man whose wealth equals their combined wealth. For this same reason, the Gini coefficient—see table 2 for a definition—is not a sufficient statistic for the analysis of the relationship between polygyny and wealth inequality. We take up each of these results, in turn, before assessing if our empirical estimates are consistent with this explanation.If we assume that male demand is limiting, then equation determines the number of wives each rich man will have. It is clear from inspection of equation that a greater extent of diminishing fitness returns to additional wives produces a lower male demand for additional wives. This is demonstrated mathematically in the electronic supplementary material. Determining the effect of greater diminishing returns to additional wives when female supply is limiting is more challenging. As noted above, if female supply is limiting,1 litre square plant pots the value of n* implied by the polygyny threshold inequality in equation has no closed form solution.

To address this challenge, we proceed as follows.Then a reduction in d, holding all other terms constant, would reduce the right-hand side of the equation—the fitness of each of the n wives of a rich man—while having no effect on the left-hand side—the fitness of a singleton wife. Thus, holding all else equal, an offsetting decrease in n would be required to restore the equality. This is demonstrated in the electronic supplementary material by differentiating equation with respect to d. This means that a man who was just barely rich enough so that an unpaired woman would choose to marry him as wife number under the initial d, would, under the lower d, be unable to secure the unpaired woman’s partnership. As such, an increase in the extent of diminishing returns to additional wives will reduce both male demand for, and female supply to, polygynous marriage. Our results imply that if d , 1, a larger quantity of moderately rich men can be expected to have more wives in total than a smaller quantity of even richer men, holding constant the total wealth held by the rich across these cases. This first finding will interact with our second finding, discussed below, concerning the effects of the population density of the rich class of men on the frequency of polygyny and the level of wealth inequality. In the electronic supplementary material, we present an alternative approach to account for diminishing marginal returns to increasing number of wives and find that our insights do not depend on the specific way in which diminishing fitness returns to increasing number of wives are modelled.To address prediction P1, we present empirical estimates of m and d . These values are estimated using a multi-level regression model fit to our individual level data; methodological details are provided in the electronic supplementary material. In all but four of the populations in our sample, the estimated d coefficient is reliably less than 1. This result provides cross-cultural empirical support for the first of the two conditions needed to generate a transition to a greater degree of monogamy with increasing wealth inequality.

Note two further results also shown in figure 5. First, our estimates for m are quite low, particularly across the agricultural economies. Second, our estimates of d 2 m are positive in almost all populations, including those that are concurrently polygynous and those that are serially monogamous. The consistently small values of m across all of our samples, even the monogamous ones, was unexpected. However, these low values reflect changes in male fitness per wife. Because of biological limits to the rate of reproduction in human females, significant increases to wealth are constrained to have less than proportional effects on fitness per wife. The effects observed here are more likely to reflect the ability of males with more than a threshold level of resources per wife to minimize offspring mortality, rather than to significantly enhance their own fertility. Though not discussed in detail here, our data suggest that male wealth impacts male fitness primarily by increasing the rate of wife acquisition rather than by increasing reproductive success per wife . Our second point addresses the possible concern that our estimates of d may be low, in part, because we use times married as our measure of polygyny. While it is true that men can accumulate a greater maximal number of marriage years through concurrent polygyny than serial monogamy, figure 5a demonstrates that the use of times married is an appropriate measure of polygyny for our purposes. Across almost all populations, the elasticity of fitness with respect to times married, d 2 m, is positive and reliably non-zero. Because these estimates measure the population-specific effects of cumulative number of wives on reproductive success, they demonstrate that an increased number of marriages leads to increased reproductive success in both types of marriage systems—concurrently polygynous and serially monogamous.We have established that there exists a strong cross-cultural pattern of decreasing—but reliably non-zero—fitness returns to increasing number of wives for reasons beyond rival wealth sharing.

We now turn our attention to testing if the transition to agriculture is associated with a decreasing fraction of wealthy males. In our theoretical model, we assume a discrete two-class wealth distribution, but empirical wealth data typically have continuous distributions. To deal with this issue, we consider two proxy measures for per cent rich in our empirical data: the minimum percentage of men that account for a fraction f of the total wealth and the frequency of men with more than c wealth, where c is the empirical midpoint in each population between the average wealth of males with one wife and the average wealth of males with two wives. More details about these metrics are included in the electronic supplementary material. Table 3 provides population-level posterior estimates of the completed wealth and completed polygyny measures, with the mean estimates by subsistence type shown in the bottom panel. To address prediction P2, we calculate empirical estimates of the fraction of rich men by production system . We find that agricultural populations have a significantly reduced frequency of wealthy individuals relative to horticultural populations. All four panels show reliable differences in mean per cent rich between the horticultural and agricultural subsistence modes. This lesser fraction of wealthy individuals suggests a decreased number of men both able and willing to take second wives. This in turn leads to reduced levels of per cent female polygyny in contexts where large wealth differentials are not able to underwrite large differentials in wives due to the existence of diminishing fitness returns to such additional wives. A limitation of this last result is that it is based on data from only four agricultural populations, three of them concentrated in a restricted region and time period . Moreover, a more informative dataset would come not from agricultural populations in the time period between the 1700s and 2000s, but rather from the agricultural populations in which monogamy actually began to emerge denovo. In our main analysis, we use estimates derived from the individual-level records available in the populations shown in table 1; in the electronic supplementary material,macetas por mayor we present comparable analyses that include 14 additional wealth distributions from historical agricultural populations. The results of this supplementary analysis are consistent with our arguments here—and in fact show stronger and more reliable effects in the direction predicted by P2. These supplementary data, however, are based on sometimes contested reconstructions of the historical wealth distributions pieced together by archaeologists and economic historians;they must be appreciated within the constraints associated with such forms of data.Using individual-level data from 29 populations, we show evidence of a general cross-cultural pattern of decreasing marginal fitness returns to increasing number of marriages. Further, using these same 29 datasets , we demonstrate the existence of an increasingly skewed distribution of material wealth in class-based agricultural societies . Both of these empirical findings are consistent with our model-based explanation for the decline of polygyny in societies engaged in agricultural production.We use cross-cultural data and a new mutual mate choice model to propose a resolution to the polygyny paradox. Following Oh et al., we extend the standard polygyny threshold model to a mutual mate choice model that accounts for both female supply to, and male demand for, polygynous matchings, in the light of the importance of, and inequality in, rival and non-rival forms of wealth.

The empirical results presented in figures 5 and 6 demonstrate two phenomena that are jointly sufficient to generate a transition to more frequent monogamy among populations with a co-occurring transition to a more unequal, highly stratified, class-based social structure. In such populations, fewer men can cross the wealth threshold required to obtain a second wife, and those who do may be fabulously wealthy, but—because of diminishing marginal fitness returns to increasing number of marriages—do not acquire wives in full proportion to their capacity to support them with rival wealth. Together, these effects reduce the population-level fraction of wives in polygynous marriages. Our model demonstrates that a low population-level frequency of polygyny will be an equilibrium outcome among fitness maximizing males and females in a society characterized by a large class of wealth-poor peasants and a small class of exceptionally wealthy elite. Our mutual mate choice model thus provides an empirically plausible resolution to the polygyny paradox and the transition to monogamy which co-occurred with the rise of highly unequal agricultural populations. We, however, cannot yet explain the causes of the unexpectedly substantial decreasing marginal fitness returns to increasing number of marriages. A purely statistical explanation of our results could be that we have missed some important rival form of wealth, which if accounted for would result in a larger estimate for m and hence a reduced estimate of the degree of diminishing returns to additional wives for reasons other than the sharing of rival wealth. Another possibility, already mentioned, is that in some of our datasets the very wealthy could be deliberately limiting their reproductive success , which would also drive m downwards. In addition to these possible statistical effects, there are a number of other plausible causes of the diminishing returns to additional wives observed in our populations. One possibility is that a male’s time and attention are rival inputs to his own fitness. This situation is likely to arise when paternal investment is essential to offspring survival and well-being. A male’s time can also be rival in other fitness relevant ways. For example, it may be difficult for a single wealthy man to effectively mate guard a large number of wives. With a wealth ratio of mr ¼ 2 and a per cent rich of u ¼ 0.5, a single rich man will have to monopolize his two wives in the face of challenges from a single unmarried man on average; however, with a wealth ratio of mr ¼ 10 and a per cent rich of u ¼ 0.1, a single rich man will have to defend his 10 wives from nine unmarried men on average. As the wealth ratio grows even more skewed, this situation could become increasingly difficult to manage . A related possibility is that a growing number of unmarried men could socially censure wealthy polygynous males, imposing costs on them that reduce male demand for and/or female supply to polygynous marriage. A third possibility is that sexually transmitted infection burden could diminish returns to polygyny, if polygyny enhances infection rates.