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Despite the appeal of the iso/anisohydric framework for classifying plant drought responses, recent studies have shown that such classifications can be strongly affected by a plant's environment. Here, we present measured in situ drought responses to demonstrate that apparent isohydricity can be conflated with environmental conditions that vary over space and time. In particular, we (a) use data from an oak species (Quercus douglasii) during the 2012-2015 extreme drought in California to demonstrate how temporal and spatial variability in the environment can influence plant water potential dynamics, masking the role of traits; (b) explain how these environmental variations might arise from climatic, topographic, and edaphic variability; (c) illustrate, through a "common garden" thought experiment, how existing trait-based or response-based isohydricity metrics can be confounded by these environmental variations, leading to Type-1 (false positive) and Type-2 (false negative) errors; and (d) advocate for the use of model-based approaches for formulating alternate classification schemes. Building on recent insights from greenhouse and vineyard studies, we offer additional evidence across multiple field sites to demonstrate the importance of spatial and temporal drivers of plants' apparent isohydricity. This evidence challenges the use of isohydricity indices, per se, to characterize plant water relations at the global scale.

Many recent studies on drought-induced vegetation mortality have explored how plant functional traits, and classifications of such traits along axes of, for example, isohydry-anisohydry, might contribute to predicting drought survival and recovery. As these studies proliferate, the consistency and predictive value of such classifications need to be carefully examined. Here, we outline the basis for a systematic classification of plant drought responses that accounts for both environmental conditions and functional traits. We use non-dimensional analysis to integrate plant traits and metrics of environmental variation into groups that can be associated with alternative drought stress pathways (hydraulic failure and carbon limitation), and demonstrate that these groupings predict physiological drought outcomes using both synthetic and measured data. In doing so, we aim to untangle some confounding effects of environment and trait variations that undermine current classification schemes, advocate for more careful treatment of the environmental context within which plants experience and respond to drought, and outline a pathway towards a general classification of drought vulnerability.

Large areas in the tropics and at mid-latitudes experience pronounced seasonality and inter-annual variability in rainfall and hence water availability. Despite the importance of these seasonally dry ecosystems (SDEs) for the global carbon cycling and in providing ecosystem services, a unifying ecohydrological framework to interpret the effects of climatic variability on SDEs is still lacking. A synthesis of existing data about plant functional adaptations in SDEs, covering some 400 species, shows that leaf phenological variations, rather than physiological traits, provide the dominant control on plant-water-carbon interactions. Motivated by this result, the combined implications of leaf phenology and climatic variability on plant water use strategies are here explored with a minimalist model of the coupled soil water and plant carbon balances. The analyses are extended to five locations with different hydroclimatic forcing, spanning seasonally dry tropical climates (without temperature seasonality) and Mediterranean climates (exhibiting out of phase seasonal patterns of rainfall and temperature). The most beneficial leaf phenology in terms of carbon uptake depends on the climatic regime: evergreen species are favoured by short dry seasons or access to persistent water stores, whereas high inter-annual variability of rainy season duration favours the coexistence of multiple drought-deciduous phenological strategies. We conclude that drought-deciduousness may provide a competitive advantage in face of predicted declines in rainfall totals, while reduced seasonality and access to deep water stores may favour evergreen species. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

To understand how climate change affects crop yields, we need to identify the climatic indices that best predict yields. Grain yields are most often predicted using precipitation and temperature in statistical models, assuming linear dependences. However, soil water availability is more influential for plant growth than precipitation and temperature, and there is ecophysiological evidence of intermediate yield maximizing conditions. Using rainfed maize and soybean yields for 1970–2010 across the USA, we tested whether the aridity index, that is, the ratio of precipitation and potential evapotranspiration seasonal totals and a proxy of soil water availability, better predicts yield than growing season precipitation total, average temperature and their interaction. We also tested for non‐monotonic responses allowing for intermediate yield‐maximizing conditions. The aridity index alone explained 77% and 72% of maize and soybean yield variability, compared with 78% and 73% explained by temperature, precipitation and their interaction. Yield responses were non‐monotonic, with yields maximized at intermediate precipitation and temperature as well as at intermediate aridity index of 0.79 for maize and 0.98 for soybean. The yield maximizing precipitation also increased with growing season average temperature, faster in maize than soybean. The intermediate yield maximizing conditions show that rainfed maize and soybean yields could both increase and decrease depending on whether climatic conditions come closer to or deviate from the yield maximizing conditions in the future. In most counties, during 1970–2010, the precipitation and aridity index were lower and temperature higher compared with those maximizing yields, suggesting that climate change will reduce yields. [ABSTRACT FROM AUTHOR]

The main content of this article is gambling and the pathology it can bring on. In order to introduce the subject I have examined national gambling organizations and the legislative body responsible for gambling. Then I have analysed the clinical picture of the pathology and personality and behavioural characteristics of the pathological gambler. After a short analysis of the main treatments of pathological gambling. I have examined closely the particular therapy of “Gamblers Anonymous”. This is the clinical context where I have done research involving 10 members of Florence Gamblers Anonymous in order to examine two particular aspects of pathological gamblers: their wrong thinking about games and their decision to take part in the association. In short, in view of the gravity of this pathology, I have analysed some important measures to prevent and to protect pathological gamblers. Le sujet de cet article est le jeu de hasard et, en particulier, la pathologie qui s’y rapporte. Tout d’abord, on examine l’organisation des jeux d’argent réservée aux opérateurs publics italiens et sa réglementation. Pour continuer, on analyse d’un point de vue clinique la pathologie, les caractéristiques et les comportements typiques des joueurs problématiques. Après un bref aperçu des différents traitements de la pathologie, on considère celui du groupe d’entraide mutuelle des « Joueurs Anonymes ». Dans ce contexte clinique, on a mené une recherche sur 10 membres d’un groupe de Joueurs Anonymes de Florence, afin d’approfondir les deux aspects suivants concernants les joueurs problématiques : leurs idées erronées sur le jeu et leur décision de se joindre au groupe de soutien des « Joueurs Anonymes ». Pour conclure, en raison de la gravité de cette pathologie inconnue de la plupart des gens, on réfléchit à certaines mesures de prévention importantes ainsi que de protection des personnes dépendantes du jeu de hasard.Argomento centrale di questo articolo è il gioco d’azzardo ed in particolare la patologia che esso può indurre. Al fine di introdurre il tema, viene esaminata l’organizzazione del gioco pubblico in Italia ed il contesto normativo in cui la materia è inserita. E’ poi analizzato l’inquadramento clinico della patologia e le caratteristiche di personalità e comportamentali tipiche del giocatore d’azzardo problematico. Dopo una breve disamina dei diversi programmi di trattamento della patologia, viene approfondita la particolare forma di terapia del gruppo di auto-aiuto dei “Giocatori Anonimi”. Essa rappresenta il contesto clinico all’interno del quale si è svolta una ricerca, che ha coinvolto 10 membri di un gruppo dell’associazione Giocatori Anonimi di Firenze, volta ad approfondire due aspetti peculiari dei giocatori d’azzardo patologici, cioè quelli relativi alle loro modalità erronee di pensiero concernenti il gioco ed alla loro decisione di partecipare al programma. In conclusione, data la gravità di questa patologia ai più sconosciuta, sono analizzate alcune importanti misure di prevenzione e di tutela dei giocatori d’azzardo problematici.

In arable systems, large amounts of nutrients, particularly of nitrogen (N) and phosphorus (P), are not efficiently converted into harvestable products and are lost from agricultural systems, with negative consequences for agricultural productivity and the environment. These nutrient losses are mediated by hydroclimatic processes causing nutrient leaching and volatilization. We quantify over the period 1987–2012 how water availability through the evaporative ratio (actual evapotranspiration divided by precipitation) and irrigation, agricultural practices, and edaphic conditions jointly affect nutrient use efficiencies in 110 agricultural catchments in the United States. We consider N and P use efficiencies (nitrogen use efficiency [NUE] and phosphorous use efficiency [PUE]) defined as ratios of catchment-scale N and P in harvested products over their respective inputs, as well as the NUE/PUE ratio, as an indication of catchment-scale N and P imbalance. Both efficiencies increase through time because of changes in climate and agronomic practices. Setting all else at the median value of the data set, NUE and PUE increased with evaporative ratio by 0.5% and 0.2% when increasing the evaporative ratio by 20% and by 4.9% and 18.8% in the presence of irrigation. NUE was also higher in catchments where maize and soybean were dominant (increasing by 2.3% for a 20% increase in maize and soybean fractional area). Soil properties, represented by mineral soil texture and organic matter content, had only small effects on the efficiencies. Our results show that both climatic conditions and crop choice are important drivers of nutrient use efficiencies in agricultural catchments. [ABSTRACT FROM AUTHOR]

In this stochastic rainfall scenario, we can exchange the long-term average in Equation 3 with the ensemble average so that the long-term mean net carbon gain rate defined with Equation 3 becomes (Lu et al., 2016) 10 HT ht Implementation In the single dry-down scenario (but not in the stochastic rainfall scenario), the simulations were run in discrete time with all the state variables updated daily. Stomatal regulation is a cornerstone process that links the exchange of carbon and water between vegetation and atmosphere, and how it is affected by plant water stress. [Extracted from the article]

Elevated atmospheric CO 2 concentration is expected to increase leaf CO 2 assimilation rates, thus promoting plant growth and increasing leaf area. It also decreases stomatal conductance, allowing water savings, which have been hypothesized to drive large-scale greening, in particular in arid and semiarid climates. However, the increase in leaf area could reduce the benefits of elevated CO 2 concentration through soil water depletion. The net effect of elevated CO 2 on leaf- and canopy-level gas exchange remains uncertain. To address this question, we compare the outcomes of a heuristic model based on the Partitioning of Equilibrium Transpiration and Assimilation (PETA) hypothesis and three model variants based on stomatal optimization theory. Predicted relative changes in leaf- and canopy-level gas exchange rates are used as a metric of plant responses to changes in atmospheric CO 2 concentration. Both model approaches predict reductions in leaf-level transpiration rate due to decreased stomatal conductance under elevated CO 2 , but negligible (PETA) or no (optimization) changes in canopy-level transpiration due to the compensatory effect of increased leaf area. Leaf- and canopy-level CO 2 assimilation is predicted to increase, with an amplification of the CO 2 fertilization effect at the canopy level due to the enhanced leaf area. The expected increase in vapour pressure deficit (VPD) under warmer conditions is generally predicted to decrease the sensitivity of gas exchange to atmospheric CO 2 concentration in both models. The consistent predictions by different models that canopy-level transpiration varies little under elevated CO 2 due to combined stomatal conductance reduction and leaf area increase highlight the coordination of physiological and morphological characteristics in vegetation to maximize resource use (here water) under altered climatic conditions. [ABSTRACT FROM AUTHOR]

Droughts affect ecosystems at multiple time scales, but their sub‐seasonal legacy effects on vegetation activity remain unclear. Combining the satellite‐based enhanced vegetation index MODIS EVI with a novel location‐specific definition of the growing season, we quantify drought impacts on sub‐seasonal vegetation activity and the subsequent recovery in the Northern Hemisphere. Drought legacy effects are quantified as changes in post‐drought greenness and sensitivity to climate. We find that greenness losses under severe drought are partially compensated by a ∼+5% greening within 2–6 growing‐season months following the droughts, both in woody and herbaceous vegetation but at different timings. In addition, post‐drought sensitivity of herbaceous vegetation to hydrological conditions increases noticeably at high latitudes compared with the local normal conditions, regardless of the choice of drought time scales. In general, the legacy effects on sensitivity are larger in herbaceous vegetation than in woody vegetation. Plain Language Summary: Droughts are increasingly severe and widespread globally, but their impacts on the global carbon cycle remain unclear due to the complexity of vegetation response to climate under and after droughts. In particular, how much plant activity decreases during drought and how quickly it recovers in the following months or years is not well understood. Here, by employing large‐scale satellite‐derived vegetation information, we identify the existence of widespread drought legacy effects on vegetation activity in the Northern Hemisphere ecosystems. We find that vegetation becomes greener in 2–6 growing‐season months after severe droughts with a stronger response to climate. These findings are in general more prominent at mid‐ and high‐latitudes, in particular for the grass‐dominated ecosystems compared with the tree‐dominated ones. Our analyses extend the picture for understanding how vegetation responds to severe droughts and could provide useful information to assist the development of dynamic vegetation models toward assessing changes in ecosystem resilience under changing climates. Key Points: Prominent increases in the sensitivity of herbaceous vegetation to hydrological conditions after severe droughts in the high‐latitudesSignificant vegetation greening in the 2–6 growing‐season months following severe droughtsLarger drought legacy effects on the sensitivity of herbaceous vegetation to climate compared with woody vegetation [ABSTRACT FROM AUTHOR]

Elevated atmospheric CO2 concentration is expected to increase leaf CO2 assimilation rates, thus promoting plant growth and increasing leaf area. It also decreases stomatal conductance, allowing water savings that have been hypothesized to drive large-scale greening, in particular in arid and semiarid climates. However, the increase in leaf area could reduce the ameliorating effect of elevated CO2 concentration on soil water depletion. The net effect of elevated CO2 on leaf- and canopy-level gas exchange thus remains unclear. To address this question, a heuristic model based on the Partitioning of Equilibrium Transpiration and Assimilation (PETA) hypothesis and a model based on stomatal optimization theory are used and their outcomes compared. Predicted relative changes in leaf- and canopy-level gas exchange rates are used as a metric of responses to changes in atmospheric CO2 concentration. Both models predict reductions of leaf-level transpiration rate due to decreased stomatal conductance under elevated CO2, but negligible (PETA) or no (optimization) changes in canopy-level transpiration due to the compensatory effect of increased leaf area. Leaf-and canopy-level CO2 assimilation are predicted to increase, with an amplification of the CO2 fertilization effect at the canopy-level due to the enhanced leaf area. The expected increase in vapor pressure deficit (VPD) under warmer conditions is predicted to decrease the sensitivity of gas exchange to atmospheric CO2 concentration in both models except at growth temperatures lower than the photosynthetic thermal optimum. The consistent predictions by different models that canopy-level transpiration varies little under elevated CO2 due to combined stomatal conductance reduction and leaf area increase highlights the coordination of physiological and morphological characteristics in vegetation to maximize resource use (here water) under altered atmospheric conditions. [ABSTRACT FROM AUTHOR]

Intercropping of two or more species on the same piece of land can enhance biodiversity and resource use efficiency in agriculture. Traditionally, intercropping systems have been developed and improved by empirical methods within a specific local context. To support the development of promising intercropping systems, the individual species that are part of an intercrop can be subjected to breeding. Breeding for intercropping aims at resource foraging traits of the admixed species to maximize niche complementarity, niche facilitation, and intercrop performance. The breeding process can be facilitated by modeling tools that simulate the outcome of the combination of different species' (or genotypes') traits for growth and yield development, reducing the need of extensive field testing. Here, we revisit the challenges associated with breeding for intercropping, and give an outlook on applying crop growth models to assist breeding for intercropping. We conclude that crop growth models can assist breeding for intercropping, provided that (i) they incorporate the relevant plant features and mechanisms driving interspecific plant–plant interactions; (ii) they are based on model parameters that are closely linked to the traits that breeders would select for; and (iii) model calibration and validation is done with field data measured in intercrops. Minimalist crop growth models are more likely to incorporate the above elements than comprehensive but parameter-intensive crop growth models. Their lower complexity and reduced parameter requirement facilitate the exploration of mechanisms at play and fulfil the model requirements for calibration of the appropriate crop growth models. [ABSTRACT FROM AUTHOR]

Seed predation can reduce the abundance and spread of unwanted vegetation in agricultural and other semi‐natural ecosystems. However, knowledge of how variations in seed predation rates affect plant species population dynamics is needed for decision making and knowledge‐based ecosystem management.We developed a stage‐classified stochastic matrix population model for Alopecurus myosuroides Huds. (blackgrass), an annual plant species thriving as a weed in temperate agroecosystems of Western and Northern Europe. The model was parameterised using empirical demographic data from long‐term experiments in Swedish winter wheat fields, including information on post‐dispersal seed losses by vertebrate and invertebrate seed predators.For agroecosystems with highly effective weed control measures (e.g. chemical and mechanical weed control), model simulations showed that seed losses via seed predation need to reach at least 78% at peak seed shedding to suppress population growth of A. myosuroides.The field experiment showed that vertebrates were most important for seed predation in July, at peak seed shedding. In August, after crop harvest, invertebrates were responsible for almost all seed predation. The model indicated that weed seed predation was much more important for weed regulation when it occurred before crop harvest in July. Vertebrates most strongly reduced population growth of A. myosuroides, although both vertebrates and invertebrates were needed to prevent it entirely.Synthesis and applications. We showed that weed seed predation by vertebrate and invertebrate seed predators is key for reducing the population growth of winter annual weeds like A. myosuroides in intensively managed agroecosystems. Therefore, protection of weed seed predators is essential for making management of unwanted vegetation less dependent on chemical and mechanical measures. [ABSTRACT FROM AUTHOR]

When modelling forest growth, capturing the effects of climate change is needed for reliable long-term predictions and management choices. This remains a challenge because commonly used mensurational forest growth and yield models, relying on inventory data, cannot account for climate change effects. We developed hybrid physiological/mensurational basal area growth and yield models, which combine physiological response to climatic conditions and empirical relations. We included climate and site effects by replacing time with light sums of photosynthetically active radiation and modifying the latter with monthly soil water, vapour pressure deficit, temperature, and frost days. When parameterised with permanent sample plot data for Scots pine and Norway spruce across Sweden, the hybrid models could reproduce observations well, although with no increase in precision compared with time-based mensurational models. When considering different climate scenarios, a significant impact on productivity from climate change emerged. For example, a 2 °C warming enhanced Scots pine production by up to 14% in regions where temperatures were originally cooler and soil water deficit was low (i.e. northwest Sweden), but depressed it, up to 9%, elsewhere. Hence, climate-sensitive models that take local variations into account are necessary for accurate predictions and sustainable forest management. [ABSTRACT FROM AUTHOR]

Summary: Stomatal optimization models can improve estimates of water and carbon fluxes with relatively low complexity, yet there is no consensus on which formulations are most appropriate for ecosystem‐scale applications. We implemented three existing analytical equations for stomatal conductance, based on different water penalty functions, in a big‐leaf comparison framework, and determined which optimization principles were most consistent with flux tower observations from different biomes.We used information theory to dissect controls of soil water supply and atmospheric demand on evapotranspiration in wet to dry conditions and to quantify missing or inadequate information in model variants. We ranked stomatal optimization principles based on parameter uncertainty, parsimony, predictive accuracy, and functional accuracy of the interactions between soil moisture, vapor pressure deficit, and evapotranspiration.Performance was high for all model variants. Water penalty functions with explicit representation of plant hydraulics did not substantially improve predictive or functional accuracy of ecosystem‐scale evapotranspiration estimates, and parameterizations were more uncertain, despite having physiological underpinnings at the plant level.Stomatal optimization based on water use efficiency thus provided more information about ecosystem‐scale evapotranspiration compared to those based on xylem vulnerability and proved more useful in improving ecosystem‐scale models with less complexity. [ABSTRACT FROM AUTHOR]

The climate‐vegetation coupling exerts a strong control on terrestrial carbon budgets and will affect the future evolution of global climate under continued anthropogenic forcing. Nonetheless, the effects of climatic conditions on such coupling at specific times in the growing season remain poorly understood. We quantify the climate‐vegetation coupling in Europe over 1982–2014 at multiple spatial and temporal scales, by decomposing sub‐seasonal anomalies of vegetation greenness using a grid‐wise definition of the growing season. We base our analysis on long‐term vegetation indices (Normalized Difference Vegetation Index and two‐band Enhanced Vegetation Index), growing conditions (including 2m temperature, downwards surface solar radiation, and root‐zone soil moisture), and multiple teleconnection indices that reflect the large‐scale climatic conditions over Europe. We find that the large‐scale climate‐vegetation coupling during the first two months of the growing season largely determines the full‐year coupling. The North Atlantic Oscillation and Scandinavian Pattern phases one‐to‐two months before the start of the growing season are the dominant and contrasting drivers of the early growing season climate‐vegetation coupling over large parts of boreal and temperate Europe. The East Atlantic Pattern several months in advance of the growing season exerts a strong control on the temperate belt and the Mediterranean region. The strong role of early growing season anomalies in vegetative activity within the growing season emphasizes the importance of a grid‐wise definition of the growing season when studying the large‐scale climate‐vegetation coupling in Europe. Plain Language Summary: Climate and terrestrial ecosystems interact and affect the global climate. Such a climate‐vegetation relationship can be effectively quantified by using satellites to measure how leafy and active the vegetation is, and numerical indices reflecting large‐scale climate patterns over a given region. Previous studies generally focused on changes in mean vegetation indices over the full growing season, which is usually defined by a fixed range of astronomical months for large geographical regions. This overlooks the fact that growing seasons differ in space and vegetation responds differently to the climate in different growing season periods. In this study, we explore how vegetation and climate interact within a growing season, here defined specifically for the local conditions. We find that there are strong relationships between the large‐scale climate patterns and vegetation indices during the first two months of the growing season. Our findings highlight the important role of the vegetation activity during the early growing season for the year‐to‐year vegetation changes in Europe. Hence, for a better understanding of the climate‐vegetation relationships, it is necessary to consider the spatial differences in the growing season, in particular for large geographical regions. Key Points: Climate‐vegetation coupling in Europe is quantified by decomposing sub‐seasonal greenness anomalies using grid‐wise defined growing seasonsLarge‐scale climate‐vegetation coupling during the first two months of the growing season largely determines the full‐year couplingThe North Atlantic Oscillation, Scandinavian Pattern, and East Atlantic patterns emerge as the most relevant large‐scale drivers for this coupling [ABSTRACT FROM AUTHOR]

Crop yield is reduced by heat and water stress and even more when these conditions co-occur. Yet, compound effects of air temperature and water availability on crop heat stress are poorly quantified. Existing crop models, by relying at least partially on empirical functions, cannot account for the feedbacks of plant traits and response to heat and water stress on canopy temperature. We developed a fully mechanistic model, coupling crop energy and water balances, to determine canopy temperature as a function of plant traits, stochastic environmental conditions, and irrigation applications. While general, the model was parameterized for wheat. Canopy temperature largely followed air temperature under well-watered conditions. But, when soil water potential was more negative than -0.14 MPa , further reductions in soil water availability led to a rapid rise in canopy temperature – up to 10 ∘ C warmer than air at soil water potential of -0.62 MPa. More intermittent precipitation led to higher canopy temperatures and longer periods of potentially damaging crop canopy temperatures. Irrigation applications aimed at keeping crops under well-watered conditions could reduce canopy temperature but in most cases were unable to maintain it below the threshold temperature for potential heat damage; the benefits of irrigation in terms of reduction of canopy temperature decreased as average air temperature increased. Hence, irrigation is only a partial solution to adapt to warmer and drier climates. [ABSTRACT FROM AUTHOR]

Climate change is predicted to hamper crop production due to precipitation deficits and warmer temperatures inducing both water stress and increasing herbivory due to more abundant insect pests. Consequently, crop yields will be impacted simultaneously by abiotic and biotic stressors. Extensive yield losses due to such climate change stressors might, however, be mitigated by ecosystem services such as insect pollination. We examined the single and combined effects of water stress, insect herbivory and insect pollination on faba bean yield components and above‐ and belowground plant biomass under realistic field conditions. We used rainout shelters to simulate a scenario in line with climate change projections, with adequate water supply at sowing followed by a long period without precipitation. This induced a gradually increasing water stress, culminating around crop flowering and yield formation. We found that gradually increasing water stress combined with insect herbivory by aphids interactively shaped yield in faba beans. Individually, aphid herbivory reduced yield by 79% and water stress reduced yield by 52%. However, the combined effect of water stress and aphid herbivory reduced yield less (84%) than the sum of the individual stressor effects. In contrast, insect pollination increased yield by 68% independently of water availability and insect herbivory. Our results suggest that yield losses can be greatly reduced when both water stress and insect herbivory are reduced simultaneously. In contrast, reducing only one stressor has negligible benefits on yield as long as the crop is suffering from the other stressor. We call for further exploration of interactions among ecosystem services and biotic and abiotic stressors that simulate realistic conditions under climate change. [ABSTRACT FROM AUTHOR]

When rainfall does not meet crop water requirements, supplemental irrigation is needed to maintain productivity. On-farm ponds can prevent excessive groundwater exploitation – to the benefit of the whole community – but they reduce the cultivated area and require investments by each farmer. Thus, choosing the source of water for irrigation (groundwater vs on-farm pond) is a problem of collective action. An agent-based model is developed to simulate a smallholder farming system; the farmers' long-/short-view orientation determines the choice of the water source. We identify the most beneficial water source for economic gain and its stability, and how it can change across communities and under future climate scenarios. By using on-farm ponds, long-view-oriented farmers provide collective advantages but have individual advantages only under extreme climates; a tragedy of the commons is always possible. Changes in farmers' attitudes (and hence sources of water) based on previous experiences can worsen the economic outcome. [ABSTRACT FROM AUTHOR]