After the fusion of Tic20-proteoliposomes with a lipid bilayer, ion channel activity was observed . The total conductance under symmetrical buffer conditions , 250 mM KCl was dependent on the direction of the applied potential: 1260 pS and 1010 pS under negative and positive voltage values, respectively. The channel was mostly in the completely open state, however, individual single gating events were also frequently observed, varying in a broad range between 25 pS to 600 pS . All detected gating events were depicted in two histograms . Two conductance classes were defined both at negative and positive voltage values with thresholds of 220 pS and 180 pS, respectively . Note that gating events belonging to the smaller conductance classes occurred more frequently. The observed pore seems to be asymmetric, since higher conductance classes notably differ under positive and negative voltages. This is probably due to interactions of the permeating ions with the channel, which presumably exhibits an asymmetric potential profile along the pore. Since small and large opening events were simultaneously observed in all experiments, it is very unlikely that they belong to two different pores. The selectivity of Tic20 was investigated under asymmetric salt conditions , 250/20 mM KCl. Similarly to the conductance values, the channel is intrinsically rectifying ,supporting asymmetric channel properties. The obtained reverse potential is 37.0 ± 1.4 mV . According to the Goldman-Hodgkin-Katz approach, this corresponds to a selectivity of 6.5:1 for K+ :Cl- -ions, thus indicating cation selectivity similar to Tic110. To determine the channel’s orientation within the bilayer, two side-specific characteristics were taken into account: the highest total conductance under symmetrical buffer conditions was measured under negative voltage values, and the channel rectifies in the same direction under asymmetrical buffer conditions . Therefore, it seems that the protein is randomly inserted into the bilayer. The pore size was roughly estimated according to Hille et al.. Considering the highest conductance class , a channel length of 1-5 nm and a resistivity of 247.5 Ω cm for a solution containing 250 mM KCl,frambueso maceta taking into account that the conductivity of the electrolyte solution within the pore is ~5 times lower than in the bulk solution, the pore size was estimated to vary between 7.8-14.1 Å.

This is in good agreement with the size of protein translocation channels such as Toc75 in the outer envelope membrane and Tic110 in the IE. Thus, the size of the Tic20 pore would be sufficient for the translocation of precursor proteins through the membrane. NtTic110, as a negative control, did not show any channel activity during electrophysiological measurements, indicating that the measured channel is not the result of a possible bacterial contamination . Considering our data presented here and those published in previous studies, we can conclude that the Tic translocon consists of distinct translocation channels: On the one hand, Tic110 forms the main translocation pore and therefore facilitates import of most of the chloroplast-targeted preproteins; on the other hand, Tic20 might facilitate the translocation of a subset of proteins. This scenario would match the one found in the inner mitochondrial membrane, where specific translocases exist for defined groups of precursor proteins: the import pathway of mitochondrial carrier proteins being clearly separated from that of matrix targeted preproteins. The situation in chloroplasts does not seem as clear-cut, but an analogous separation determined by the final destination and/or intrinsic properties of translocated proteins is feasible. The severe phenotype of attic20-I mutants prompts us to hypothesize that Tic20 might be specifically required for the translocation of some essential proteins. According to cross-linking results, Tic20 is connected to Toc translocon components. Therefore, after entering the intermembrane space via the Toc complex, some preproteins might be transported through the IE via Tic20. On the contrary, Kikuchi et al.presented that Tic20 migrates on BN-PAGE at the same molecular weight as the imported precursor of the small subunit of Rubisco and that tic20-I mutants display a reduced rate of the artificial precursor protein RbcS-nt: GFP. The authors interpreted these results in a way that Tic20 might function at an intermediate step between the Toc translocon and the channel of Tic110. However, being a substantial part of the general import pathway seems unlikely due to the very low abundance of Tic20. It is feasible to speculate that such abundant proteins as pSSU, which are imported at a very high rate, may interact incidentally with nearby proteins or indifferently use all available import channels.

To clarify this question, substrate proteins and interaction partners of Tic20 should be a matter of further investigation. Additionally, a very recent study suggested AtTic20-IV as an import channel working side by side with AtTic20-I. However, detailed characterization of the protein and experimental evidence for channel activity are still missing.Plants have pre-formed and inducible structural and biochemical mechanisms to prevent or arrest pathogen ingress and colonization. These defenses include barriers such as papillae and ligno-suberized layers to fortify cell walls, and low-molecular weight inhibitory chemicals . Plants undergo transcriptional changes upon perception of microbe associated molecular patterns or effectors to induce local and systemic resistance. The oomycete MAMPs, arachidonic acid and eicosapentaenoic acid , are potent elicitors of defense. These eicosapolyenoic acids were first identified as active components in Phytophthora infestans spore and mycelial extracts capable of eliciting a hypersensitive-like response, phytoalexin accumulation, lignin deposition, and protection against subsequent infection in potato tuber discs . Further work demonstrated root treatment with AA protects tomato and pepper seedlings from root and crown rot caused by Phytophthora capsici, with associated lignification at sites of attempted infection . AA has been shown to induce resistance, elicit production of reactive oxygen species, and trigger programmed cell death in members of the Solanaceae and other families . Phaeophyta and Rhodophyta members contain numerous bioactive chemicals that can elicit defense responses in plants . The brown alga, Ascophyllum nodosum, is a rich source of polyunsaturated fatty acids, including AA and EPA, which comprise nearly 25% of its total fatty acid composition . A. nodosum and oomycetes belong to the major eukaryotic lineage, the Stramenopila, and share other biochemical features . Commercial extracts of A. nodosum, used in organic and conventional agriculture as plant bio-stimulants, may also help plants cope with biotic and abiotic stresses. A proprietary A. nodosum extract, Acadian , has been shown to provide protection against bacterial and fungal pathogens . Studies in A. thaliana showed ANE induced systemic resistance to Pseudomonas syringae pv. tomato and Sclerotinia sclerotiorum . Investigation into ANE-induced resistance in A. thaliana and tomato suggest the role of ROS production, jasmonic acid signaling, and upregulation of defense-related genes and metabolites .

As a predominant polyunsaturated fatty acid in ANE, AA may contribute to ANE’s biological activity. In a parallel study we demonstrated AA’s ability to systemically induce resistance and ANE’s capacity to locally and systemically induce resistance in tomato to different pathogens . Further, we showed that AA and ANE altered the phytohormone profile of tomato by modulating the accumulation of defense-related phytohormones . Through RNA sequencing,cultivar frambuesas this same study revealed a striking level of transcriptional overlap in the gene expression profiles of AA- or ANEroot-treated tomato across tested time points . Gene ontology functional analysis of transcriptomic data revealed AA and ANE enriched similar categories of genes with nearly perfect overlap also observed in categories of under-represented genes. Both AA and ANE treatment protected seedings from challenge with pathogens with different parasitic strategies while eliciting expression of genes involved in immunity and secondary metabolism. The shared induced resistance phenotype and extensive transcriptional overlap of AA and ANE treatments suggested similar metabolic changes may be occurring in treated plants. In the current study, untargeted metabolomic analyses were conducted to assess global effects of root treatment with AA and the AA-containing complex extract, ANE, on the metabolome of tomato plants. Fatty acid sodium salts were prepared and stored as previously described . AA stock solution was prepared by dissolving 100 mg of fatty acid salt in 1 mL of 75% ethanol. AA stock solution was subsequently stored in a glass vial at −20°C flushed with N2 to minimize oxidation. A proprietary formulation of A. nodosum extract was diluted with deionized water to a 10% working concentration, which was used to prepare treatment dilutions. All chemicals were diluted to their treatment concentrations with sterile diH2O. Hydroponically reared, 3-weekold tomato seedlings with two fully expanded true leaves were transferred to 1 L darkened treatment containers with their respective root treatment solutions. Following 24, 48, 72, and 96 hours of root treatment, tomato seedlings were removed from treatment containers, and leaves and roots were excised from shoots and flash frozen in liquid nitrogen. Each sample was the pool of roots or leaves of two seedlings with four replications per tissue, treatment, and time point. Samples were transported on dry ice and stored at −70 °C until metabolite extraction. The issue samples were ground in liquid nitrogen using a mortar and pestle and 100 mg was weighed and transferred to a 2-ml bead-beating tube containing four 2.8-mm ceramic beads. All tools and consumables were pre-chilled in liquid nitrogen. After weighing, each sample was removed from liquid nitrogen and kept at −20 °C until addition of extraction solution.One ml of extraction solution was added to each sample which was then vortexed, followed by bead-beating in a bead mill at a speed of 2.9 m/s for one 3-min cycle. After bead-beating, samples were centrifuged at 12k × g for 10 min at 4 °C . Samples were diluted 5-fold using extraction solution and filtered into LC-MS-grade HPLC vials using 0.22-μm PTFE syringe filters. HPLC vials were kept at 4 °C until LC-MS analysis. A blank was prepared by adding 1 ml extraction solution to a bead-beating tube containing beads that was processed equivalently to the samples. In addition, a quality control sample was prepared by combining 20 μl of each of the extracted samples and processed equivalently.Samples were analyzed via high performance liquid chromatography and electrospray ionization quadrupole time-of-flight mass spectrometry controlled by MassHunter software in centroid data mode. Mobile phase A was ultrapure water with 0.05 % formic acid and mobile phase B was acetonitrile with 0.05 % formic acid. Before starting the run, the column , equipped with a guard column , was conditioned for 20 minutes with 95 % mobile phase A and 5 % B. Column temperature was maintained at 40 °C.

The sample injection order was randomized, with individual samples being run consecutively in positive and negative mode. The quality control sample was injected at the beginning and end of the run, as well as after every 12 samples throughout the run to check signal and elution stability. Source parameters were as follows: drying gas temperature of 325 °C and 350 °C , drying gas flow 12 l/min, nebulizer pressure 35 psi, sheath gas temp 375 °C and 400 °C , sheath gas flow 11 l/min, capillary voltage 3500 V and 3000 V , nozzle voltage 0 V and 1500 V , fragmentor 125 V, skimmer 65 V, and octopole 750 V. Acquisition was performed over a mass range of 50 to 1700 m/z using the all-ions MS/MS technique, cycling three different collision energies at an acquisition rate of 3 spectra/s. Simultaneous infusion of a solution of purine and hexakisphosphazine using the reference nebulizer was used throughout the runs for mass calibration. Positive and negative mode raw data files from MassHunter were analysed separately in MS-DIAL before downstream analysis. Tolerances for MS1 and MS2 were set to 0.025 and 0.075 Da respectively . For peak detection, the mass slice width was set to 0.1 DA and the minimum peak height was set to 15,000 which was approximately 3 times the noise level observed in the total ion chromatogram. A linear weighted moving average method was used for peak smoothing, with a smoothing level of 3 scans and a minimum peak width of 5 scans. Deconvolution was performed with a sigma window value of 0.5 and an MS/MS abundance cutoff of 10. The adducts permitted were [M+H]+, [M+NH4]+, [M+Na] +, [M+K]+, [M+H−H2O]+, and [2M+H]+ in positive mode, and [M−H]−, [M−H2O−H]−, [M+Cl]−, [M+Na−2H]−, and [M+K−2H]− in negative mode.MS-DIAL data was cleaned in MS-CleanR in RStudio using the following parameters: minimum blank ratio of 0.8, maximum relative standard deviation of 30, minimum relative mass deffect of 50, maximum RMD of 3000, maximum mass difference of 0.05 and maximum retention time difference of 0.15.

Society may seek to provide assistance to the farmer both for protecting the environment and for maintaining the rural way of life. This desire to maintain the scenic and recreational amenities of agricultural areas can also translate to private incentives for conservation of agricultural activities and the environment. For example, vineyards in northern California’s wine country are sources of tourist revenue as well as income from wine production. The wineries benefit directly from the crowds of visitors who crowd the tasting rooms every weekend, and the region is home to numerous bed and breakfasts to house these guests. Such examples of “agri-tourism” can be pursued anywhere that farm activities are scenic, rather than noxious, from the point of view of the potential visitor. In California, agri-tourism activities also include dude ranches, self-pick berry and apple farms, corn mazes, and farm-animal petting zoos . The potential economic impact of these activities is unknown, but it may be informative to note that golf courses, a quasi-agricultural land use, resulted in a total sales impact in California of $7.8 billion in 2000, directly supporting over 62,000 jobs . In the preceding discussion of dairy production, we noted that the negative externalities involved in dairy production counteract the other benefits of having these facilities located close to population centers. In contrast,frambueso maceta the positive externalities associated with the recreational and environmental amenities of some farming activities are magnified when these operations are located closer to urban areas. Although Napa Valley wine would still taste as sweet if it were located 200 miles further from San Francisco, there would be far fewer people enjoying a drive through wine country on any given Sunday. Everything being equal, farmers who are closer to population centers will be able to reap greater private benefit from provision of new agri-tourism opportunities.

The California Organic Foods Act , signed into law in 1990, provides protection to producers, processors, handlers and consumers in that foods produced and marketed as organic must meet specified standards. As part of the regulatory process, COFA requires annual registration of all processors, growers and handlers of commodities labeled as organic. State registration is separate from, and does not act as a substitute for, organic certification. Registration is mandated by state law and is administered by CDFA while certification is mandated by federal law and is conducted by certification organizations accredited by USDA. The Organic Foods Production Act of 1990 requires the United States Department of Agriculture to develop national organic standards for organically produced agriculture and to develop an organic certification program. The final regulations for implementation of the OFPA were published in the Federal Register in December, 2000. The new rule took effect April 21, 2001 and marked the beginning of the transition period. Full compliance with the rule was required by October 20, 2002 at which time products began to use the National Organic Program organic label. The final rule includes a list of allowed synthetic and prohibited non-synthetic materials as well as labeling requirements. Unlike COFA, OFPA requires all growers grossing $5,000 or more to obtain certification from a USDA accredited certification organization.Interest in organic agricultural production has never been greater due to the continuous and rapid rate of expansion and the relatively higher prices commanded for organic products. This chapter quantifies the current size and growth of the organic industry in California with respect to acres, farm gate sales, and number of growers. The chapter looks at size and growth with respect to major commodity groups and sub-regions of California. The state’s counties are divided into eight geographic regions based on similar groupings used by the California Department of Food and Agriculture in their annual statistical reports . The six major commodity group classifications presented also parallel the CDFA reports and include: field crops; fruit crops; nut crops; livestock, poultry and products; nursery, forestry and flowers; and vegetable crops . The most important individual commodities will also be discussed.

When interpreting the results, the following points should be considered. The numbers contained in this chapter are derived solely from information provided in the annual registration forms of organic growers. In other words, the numbers are presented as reported to CDFA by growers. Only sales from products marketed as organic are required to be reported to CDFA. This means that income from sales of organically grown products sold in the conventional market may not be included. Similarly, income from government payments is not reported. Further, the registration information does not reveal whether or not a farm also has conventional production. Therefore, the size of the farm operation is not known from the registration data; only the size of the organic enterprise is known. There are a number of conventional growers in California who devote only a portion of their total acreage to organic crop production. Therefore, some of the growers that are categorized as “small” or “medium-sized” organic farmers may actually be larger conventional growers experimenting or diversifying with some organic acreage. Under CDFA regulations, producers of organic commodities pay graduated registration fees based on an operation’s total sales. However, registrants grossing over $5 million annually were not obligated to report sales above that amount prior to 2003. While most registrants reported actual amounts over $5 million, some registrants reported at the ceiling. Therefore, the total value of production in this chapter is undoubtedly underestimated because income realized by some high-revenue producers may not have been fully accounted for.Produce includes the commodity groups of most consequence to registered organic agriculture in California. In 2002, produce was grown by the majority of organic farms and acreage . Compared to all of California agriculture, produce is an even greater proportion of organic marketings than conventional marketings, representing 84 percent of total organic sales and 60 percent of total sales from California’s agricultural commodities. In contrast, livestock, poultry and products represent only 8 percent of organic sales in 2002 but routinely contribute more than one fourth of statewide income from agriculture. In 2002 there were 45 different commodities with over $1 million in organic sales. The highest grossing commodity was grapes followed by lettuces, carrots, strawberries and tomatoes . Of the top 20 grossing commodities, eight were fruit crops , seven vegetable crops , two livestock commodities and one nut crop . The top 20 commodities represented 60 percent of total sales.Produce growers represented 78 percent of the total number of growers in 2002 . Almost half of all organic growers produced fruit crops, about one fourth grew vegetable crops and 11 percent grew nut crops.

Field crops were grown by 11 percent of producers, nursery and flowers by 8 percent and livestock, poultry and products by only 3 percent. These percentages don’t add to 100 because over one third of organic growers reported sales in more than one commodity group,cultivar frambuesas most typically vegetable crops and fruit crops. Over half of the registered organic growers grossed under $10,000 in 2002 while three percent grossed over a million dollars . Ninety percent of sales were from the 17 percent of growers grossing $100,000 or more. The remaining 10 percent of sales was captured by the 83 percent of growers grossing under $100,000 in annual sales. Over one third of the state’s total organic acreage was located in the San Joaquin Valley in 2002 . Vegetable crops comprised 42 percent of that acreage, fruit and nut crops 27 percent, and field crops 26 percent. The Sacramento Valley recorded 17 percent of the state’s organic acreage, with three fourths of the region’s acreage planted to field crops and the rest mostly divided among fruit, nut, and vegetable crops. The Central Coast represented 13 percent of the total acreage . Eighty percent of that acreage was planted to vegetable crops. The South Coast had another 10 percent of the acreage of which almost three fourths was fruit crops. The North Coast and Cascade-Sierra each had 9 percent of the acreage. Half of the North Coast acreage was devoted to fruit crops while 91 percent of the acreage in the CascadeSierra was in field crops.The San Joaquin Valley was the leading region for fruit production with 32 percent of the acreage and 26 percent of sales. The South Coast followed closely with 30 percent of the acreage and 25 percent of the sales. The North Coast had 17 percent of the acreage and 16 percent of the sales. Two thirds of the nut acreage was in the San Joaquin Valley and Sacramento Valleys with 89 percent of the sales split between these two regions. The remaining nut production was split between the Central Coast and North Coast. Three fourths of the vegetable crop production took place in the Central Coast and San Joaquin Valley. These two regions accounted for 58 percent of sales. The Central Coast had 30 percent of the acreage and 37 percent of the sales while the San Joaquin Valley had 43 percent of the acreage but only 21 percent of sales. Field crops were grown primarily in the Sacramento Valley and San Joaquin Valley with two thirds of the acreage and three fourths of the sales. Livestock and poultry production took place primarily in the North Coast and San Joaquin Valley with 95 percent of the acreage and 97 percent of the sales.The number of registered organic farms in California increased by over 50 percent during the eleven-year period 1992-2002 from 1,273 to 1,949 growers . But the growth has not been even, with the largest growth in 1994, 1998, and 2000.The numbers actually declined from the previous year in 1993 and 2002. By far the largest absolute change in number of growers has been in fruit and nut crops, increasing by over 700 growers.The number of growers increased by a much smaller percentage than the number of farmed acres, suggesting that established growers increased crop acreage and/or that some new growers entered the program with above average farm size . This is consistent with the observation that almost 40 percent of the growth in acreage was in field crops which tend to have much higher acreage per farming unit than produce crops. Acreage also grew at a faster rate than gross sales.

This is again attributable to an increasing importance of field crops that have lower sales per acre than any of the other commodity groups.Comparing the organic sub-sector to the whole of California agriculture, gross sales of organically grown commodities tripled between 1992 and 2002 while overall agricultural sales in California increased by 30 percent over the same period. Growth in organic sales averaged 20 percent a year between 1993 and 1998 but slowed to an average of eight percent from 1998 to 2002. In the five year period 1998-2002, organic sales increased by 33 percent while state total sales were stagnant. Organic crop acreage increased four-fold between 1992 and 2002 despite a decrease in land in farms for the state over the same period. Organic agriculture nevertheless represented only 1 percent of total cash income for California by 2002. Organic produce was slightly more prominent, with 2 percent of vegetable sales and 1.4 percent of fruit and nut sales in 2002.From 1998-2002, vegetable crops posted a 48 percent increase in the number of acres but only a 22 percent increase in total sales , although this varied widely across regions. Over 90 percent of the increase in vegetable crop acreage took place in the Central Coast and the San Joaquin Valley. Vegetable crops with the greatest increase in sales include spinach, celery, endive, mushrooms, lettuces, and fresh market tomatoes. Salad mix sales actually decreased over the period. Commodities with the largest increase in acreage include salad mix, lettuces, spinach, carrots and mustard. The acreage data can be somewhat misleading in that the greatest increase came from fallow acreage and acreage in cover crops for rotation purposes.Considering all salad crops as lettuces the greatest increase in acreage attributed to a vegetable commodity came from lettuces expanding from 2,600 acres in 1998 to 6,500 acres in 2002. In fact, lettuces account for over one third of the increase in vegetable acreage. However, sales did not increase in proportion to the acreage, increasing by 23 percent due, primarily, to the decrease in sales from salad mix.

The key thesis to be explored is that for some kinds of wealth and some economic systems the parents’ wealth strongly predicts the wealth of the offspring. In particular, the cattle, land and other types of material wealth of pastoral and agricultural economies are directly transmitted by simple transfers, often buttressed by social conventions of inheritance. By contrast the somatic wealth and skills and the social network ties central to foraging and horticultural livelihoods are more subject to the vagaries of learning, genetic recombination, and childhood development. Moreover, in foraging and horticultural economies, such material wealth as exists tends to circulate through broad social networks rather than being vertically transmitted to offspring. A corollary of the thesis is that, if our model is correct, economies in which material wealth is important will show substantial levels of wealth inequality. Both the thesis and the corollary find strong support in our data. We focus on small-scale societies because they offer the greatest variation in both the technologies by which a livelihood is gained and the basic institutions that provide the incentives and constraints regulating economic life, including the dynamics of inequality and the inheritance process. . These societies thus provide the most powerful lens for exploring hypotheses concerning the importance of technologies and institutions in explaining the dynamics of inequality and, thus, may also illuminate long-term trends in contemporary and future economies. The connection between wealth inheritance and wealth inequality is the following: If wealth is strongly transmitted across generations, chance shocks to the economic fortunes of a household due to disease or accident,frambueso maceta luck in a hunt or harvest, and other environmental disturbances or windfalls will be reproduced in the next generation.

These effects will thus accumulate over time and thereby counteract the widely observed inequality dampening tendency of regression to the mean . We seek to understand the effects of this process by examining how the offsetting effects of random shocks and imperfect transmission across generations jointly determine a steady state distribution of wealth for differing kinds of wealth and across the four different economic systems . The institutions and norms that characterize distinct economic systems and the nature of the wealth class alike will affect the degree of inter generational transmission.For a number of modern economies, there are quantitative estimates and comparisons of the inter generational transmission of education, occupational prestige, nonhuman physical capital, and other forms of embodied and material wealth . For small-scale populations, associations between reproductive success and material forms of wealth have been studied , and there exist piecemeal estimates of inter generational transmission of, for example, fertility and height . But there are no estimates allowing a comparison across populations of the inheritance of the distinctive kinds of wealth that are central to the livelihoods of small-scale communities of foragers, horticulturalists, herders, and farmers. Here we present a new set of data and conduct a quantitative comparative analysis of the transmission of distinct types of wealth among the 21 populations shown in Fig.1 and Table 1. Further information is provided in .Since the development of human capital theory a half-century ago, it has been conventional to treat wealth as a multidimensional attribute, as evidenced by the adjectives now routinely applied to the word “capital,” namely, social, somatic, material, cultural, and network . We identified three broad classes of wealth in our populations, namely, embodied; material ; and relational . We have no measures of other heritable determinants of well-being such as ritual knowledge, an important source of institutionalized inequality in some populations.

By linking the level of wealth of parents and adult offspring, measured as appropriate for individuals or households , we are able to estimate the degree of inter generational persistence for particular types of wealth and then to create averages for each broad class of wealth. We classify economic systems according to the conventions of anthropology . Hunter gatherer economic systems are those that make minimal use of domesticated species , whereas pastoralists rely heavily, though rarely exclusively, on livestock kept for subsistence and sometimes commercial purposes. Although both horticulturalists and agriculturalists use domesticated plants and animals, horticulturalists do not typically use ploughs, their cultivation is labor- not land-limited, and land markets are absent or limited. As with all classificatory systems, there are some ambiguities of assignment of our populations to these classes, but the least improbable reclassifications do not affect our results [see , section 4]. Transmission of wealth across generations need not take the form of bequests, or the literal passing on of physical objects . What matters for the long-run dynamics of inequality is anything that results in a statistical association between the wealth of parents and children. This statistical association may be enhanced by positive assortment in mating or in economic pursuits as occurs when skilled hunters pursue prey together, or when successful herders cooperate in livestock management. The same is true of increasing returns or other forms of positive feed backs, for example when those who invest a substantial amount earn higher than average returns, or when childhood developmental effects associated with modest genotypic differences result in substantial phenotypic differences. Negative feed backs, such as sharing norms that extract substantial transfers from the wealthy, or wealth shocks that are inversely correlated with one’s wealth , by contrast, heighten regression to the mean by reducing b, thereby attenuating the persistence of inequality over time and hence reducing steady-state inequality.

Our three wealth classes differ in the extent to which these transmission mechanisms—transfers, assortment, and positive feed backs in development or accumulation—are at work. Material wealth is readily transferred to the next generation by bequests sanctioned by cultural rules. Moreover, because it is typically observable, material wealth can facilitate deliberate marital or economic assortment. For some types of material wealth , the correlation of material wealth levels across generations is further enhanced by the presence of increasing returns to scale or other positive feed backs. Network ties can easily be passed from parent to child, but the offspring of less well-connected parents can usually gain access to allies and helpers more readily than a landless son in a farming community can acquire land, for example, through savings or systems of patronage. As a result we expect the inter generational transmission of relational wealth to be limited, at least by comparison with material wealth. Embodied wealth is transmitted by a combination of genetic inheritance, socialization, and parent-offspring similarity in the conditions affecting childhood development. The knowledge component of embodied wealth is readily transmitted to offspring, but,cultivar frambuesas unless restricted by religious or other constraints, it is typically available to other members of a population as well . Genetic and psychometric evidence from industrial societies suggests that parent-offspring transmission of economically relevant personality and behavioral characteristics, such as risk-taking, trustworthiness, conscientiousness, and extroversion is limited . We do not have similar evidence across generations in the small-scale populations under study, but industrial-society estimates support our expectation that the degree of inter generational transmission will differ markedly among our three wealth classes, with substantial transmission of material wealth and more limited transmission of relational and embodied wealth. Ethnographic evidence suggests that the four economic systems also differ in the importance of the three classes of wealth. A successful hunter gatherer or horticulturalist depends heavily on his or her strength, practical knowledge, and social networks, while making little use of material resources that are not in the public domain. By contrast, the well-being of a herder or farmer is closely tied to the amount of stock or land under his or her command, which makes material wealth a more important influence on livelihoods in these economic systems.To estimate our model of wealth transmission, we need two pieces of information: the degree of inter generational transmission for each wealth type and the importance of each wealth class in a given economic system . Note that we do not require identification of the causal paths by which transmission takes place, as might be represented in a multi-equation structural model . Our model instead requires a single estimate of the magnitude of the statistical association between parental and offspring wealth for each data set. This requirement, along with the absence of robust evidence of non-linearities, motivated our consistent use of linear models. Functional forms, estimation procedures, robustness checks, weighting procedures, and other aspects of our statistical techniques and results are described in , section 1. Note that the populations studied were not selected at random; instead, we included all populations we were aware of for which inter generational wealth transmission estimates are feasible and the researchers agreed to share data. Table 1 presents our individual estimates of b; Table 2 presents the summary statistics for both the inter generational transmission and the importance of the three wealth classes in the four economic systems.

Across the four economic systems, the estimated b for 14 measures of material wealth, including agricultural and horticultural land, livestock, shares in sea mammal–hunting boats, quality of housing, and household utensils averages 0.37 . For farm land , the degree of transmission is substantial, averaging 0.45 , thus equaling or exceeding the inter generational transmission of most forms of wealth in modern industrial economies . Livestock are even more highly transmitted across generations . Our 23 estimates of the transmission of embodied wealth across generations average 0.12. The highest estimates are for body weight . We also find a very modest level of inter generational transmission of reproductive success ; it is entirely absent in three societies, has a maximum value of 0.21, and averages 0.09, similar to low correlations between parental and offspring fertility in many pre-demographic transition populations . Grip strength is weakly transmitted across generations. The transmission of hunting success is highly variable , averaging 0.17. Knowledge and skill, such as the production and management of horticultural crops in the Pimbwe or proficiency in subsistence tasks and cultural knowledge in the Tsimane, are only weakly transmitted from parents to offspring. The six estimates of relational wealth transmission indicate that the extent to which network links are transmitted across generations is modest, averaging b = 0.19. To measure the importance of each wealth class in the four economic systems we used ethnographers’ judgments of the percentage difference in household well-being associated with a 1% difference in the amount of a given wealth class, holding other wealth classes constant at the average for that population, and requiring these percentage effects to sum to one. The average values of a by wealth class and economic system also appear in Table 2. Consistent with descriptive ethnographies of these and other populations, embodied and relational wealth are relatively important for hunter-gatherers, whereas material wealth is key in pastoral and agricultural populations. Statistical estimates of the importance of each class of wealth across the economic systems would have been preferable, but are precluded by the absence for most populations of a single relatively homogeneous measure of well-being. However, we were able to econometrically estimate m—the importance of material wealth—from an equation similar to using data from populations not represented in our study, including one horticultural, two pastoral, and seven small-scale agricultural economies. These estimates [see section 1] are close to our ethnographers’ estimates and suggest that, if anything, we have understated the difference in the importance of material wealth between pastoral and agricultural economies, on the one hand, and horticultural economies on the other. Correcting this understatement would only strengthen our main conclusions.Our first finding is that the a-weighted averages of the b values for the four economic systems differ markedly . Inter generational transmission of wealth is modest in hunter-gatherer and horticultural systems and substantial in agricultural and pastoral systems. However, even the smaller b values of the former imply that being born into the top 10% of the wealth distribution confers important advantages. In these societies, a child of parents in the highest wealth decile is on average more than three times as likely to end up in the top decile as is the child of the bottom decile. Although hardly a level playing field, inter generational transmission in these economic systems is modest when compared with the agricultural systems, where the child of the top decile is on average about 11 times more likely than the child of the poorest decile to end up in the richest decile, or to the pastoral systems, where the ratio exceeds 20.