Laboratorio Internacional Of Cambio Global

Santiago, Chile

Laboratorio Internacional Of Cambio Global

Santiago, Chile
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Ferrero R.,CSIC - Institute for Sustainable Agriculture | Ferrero R.,University of Santiago de Chile | Lima M.,University of Santiago de Chile | Lima M.,Laboratorio Internacional Of Cambio Global | And 3 more authors.
Frontiers in Plant Science | Year: 2017

Managing production environments in ways that promote weed community diversity may enhance both crop production and the development of a more sustainable agriculture. This study analyzed data of productivity of maize (corn) and soybean in plots in the Main Cropping System Experiment (MCSE) at the W. K. Kellogg Biological Station Long-Term Ecological Research (KBS-LTER) in Michigan, USA, from 1996 to 2011. We used models derived from population ecology to explore how weed diversity, temperature, and precipitation interact with crop yields. Using three types of models that considered internal and external (climate and weeds) factors, with additive or non-linear variants, we found that changes in weed diversity were associated with changes in rates of crop yield increase over time for both maize and soybeans. The intrinsic capacity for soybean yield increase in response to the environment was greater under more diverse weed communities. Soybean production risks were greatest in the least weed diverse systems, in which each weed species lost was associated with progressively greater crop yield losses. Managing for weed community diversity, while suppressing dominant, highly competitive weeds, may be a helpful strategy for supporting long term increases in soybean productivity. In maize, there was a negative and non-additive response of yields to the interaction between weed diversity and minimum air temperatures. When cold temperatures constrained potential maize productivity through limited resources, negative interactions with weed diversity became more pronounced. We suggest that: (1) maize was less competitive in cold years allowing higher weed diversity and the dominance of some weed species; or (2) that cold years resulted in increased weed richness and prevalence of competitive weeds, thus reducing crop yields. Therefore, we propose to control dominant weed species especially in the years of low yield and extreme minimum temperatures to improve maize yields. Results of our study indicate that through the proactive management of weed diversity, it may be possible to promote both high productivity of crops and environmental sustainability. © 2017 Ferrero, Lima, Davis and Gonzalez-Andujar.


Torres R.,Austral University of Chile | Pantoja S.,University of Concepción | Harada N.,Japan Agency for Marine - Earth Science and Technology | Gonzalez H.E.,Austral University of Chile | And 11 more authors.
Journal of Geophysical Research: Oceans | Year: 2011

Carbon system parameters measured during several expeditions along the coast of Chile (23°S-56°S) have been used to show the main spatial and temporal trends of air-sea CO2 fluxes in the coastal waters of the eastern South Pacific. Chilean coastal waters are characterized by strong pCO2 gradients between the atmosphere and the surface water, with high spatial and temporal variability. On average, the direction of the carbon flux changes from CO2 outgassing at the coastal upwelling region to CO2 sequestering at the nonupwelling fjord region in Chilean Patagonia. Estimations of surface water pCO2 along the Patagonian fjord region showed that, while minimum pCO2 levels (strong CO 2 undersaturation) occurs during the spring and summer period, maximum levels (including CO2 supersaturation) occur during the austral winter. CO2 uptake in the Patagonia fjord region during spring-summer is within the order of -5 mol C m-2 yr-1, indicating a significant regional sink of atmospheric CO2 during that season. We suggest that the CO2 sink at Patagonia most probably exceeds the CO2 source exerted by the coastal upwelling system off central northern Chile. Copyright 2011 by the American Geophysical Union.


Ferrero R.,CSIC - Institute for Sustainable Agriculture | Lima M.,University of Santiago de Chile | Lima M.,Laboratorio Internacional Of Cambio Global | Gonzalez-Andujar J.L.,CSIC - Institute for Sustainable Agriculture | Gonzalez-Andujar J.L.,Laboratorio Internacional Of Cambio Global
PLoS ONE | Year: 2014

Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent "hot-spots" in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity. © 2014 Ferrero et al.


Baselga A.,CSIC - National Museum of Natural Sciences | Baselga A.,University of Santiago de Compostela | Araujo M.B.,CSIC - National Museum of Natural Sciences | Araujo M.B.,Laboratorio Internacional Of Cambio Global | Araujo M.B.,University of Évora
Journal of Biogeography | Year: 2010

Aim: The aim of community-level modelling is to improve the performance of species distributional models by taking patterns of co-occurrence among species into account. Here, we test this expectation by examining how well three community-level modelling strategies ('assemble first, predict later', 'predict first, assemble later', and 'assemble and predict together') spatially project the observed composition of species assemblages. Location: Europe. Methods: Variation in the composition of European tree assemblages and its spatial and environmental correlates were examined with cluster analysis and constrained analysis of principal coordinates. Results were used to benchmark spatial projections from three community-based strategies: (1) assemble first, predict later (cluster analysis first, then generalized linear models, GLMs); (2) predict first, assemble later (GLMs first, then cluster analysis); and (3) assemble and predict together (constrained quadratic ordination). Results: None of the community-level modelling strategies was able to accurately model the observed distribution of tree assemblages in Europe. Uncertainty was particularly high in southern Europe, where modelled assemblages were markedly different from observed ones. Assembling first and predicting later led to distribution models with the simultaneous occurrence of several types of assemblages in southern Europe that do not co-occur, and the remaining strategies yielded models with the presence of non-analogue assemblages that presently do not exist and that are much more strongly correlated with environmental gradients than with the real assemblages. Main conclusions: Community-level models were unable to characterize the distribution of European tree assemblages effectively. Models accounting for co-occurrence patterns along environmental gradients did not outperform methods that assume individual responses of species to climate. Unrealistic assemblages were generated because of the models' inability to capture fundamental processes causing patterns of covariation among species. The usefulness of these forms of community-based models thus remains uncertain and further research is required to demonstrate their utility. © 2010 Blackwell Publishing Ltd.


Castellanos-Frias E.,CSIC - Institute for Sustainable Agriculture | Castellanos-Frias E.,Laboratorio Internacional Of Cambio Global | Garcia De Leon D.,CSIC - Institute for Sustainable Agriculture | Garcia De Leon D.,Laboratorio Internacional Of Cambio Global | And 4 more authors.
Annals of Applied Biology | Year: 2014

Avena sterilis (sterile oat) is one of the most extended and harmful weeds in Mediterranean cereal crops. A process-based niche model for this species was developed using CLIMEX. The model was validated and used to assess the potential distribution of A. sterilis in Europe under the current climate and under two climate change scenarios. Both scenarios represent contrasting temporal patterns of economic development and CO2 emissions. The projections under current climate conditions indicated that A. sterilis does not occupy the full extent of the climatically suitable habitat available to it in Europe. Under future climate scenarios, the model projection showed a gradual advance of sterile oat towards Northeastern Europe and a contraction in Southern Europe. The infested potential area increases from the current 45.2% to 51.3% in the low-emission CO2 scenario and to 59.5% under the most extreme scenario. These results provide the necessary knowledge for identifying and highlighting the potential invasion risk areas and for establishing the grounds on which to base the planning and management measures required. The main actions should be focused on controlling the large-scale seed scattering, preventing seed dispersal into potentially suitable areas. © 2014 Association of Applied Biologists.


Lima M.,University of Santiago de Chile | Lima M.,Laboratorio Internacional Of Cambio Global | Navarrete L.,Instituto Madrileno Of Investigacion Y Desarrollo Rural | Gonzalez-Andujar J.L.,CSIC - Institute for Sustainable Agriculture | Gonzalez-Andujar J.L.,Laboratorio Internacional Of Cambio Global
PLoS ONE | Year: 2012

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements. © 2012 Lima et al.


Lima M.,University of Santiago de Chile | Lima M.,Laboratorio Internacional Of Cambio Global
Ecology and Evolution | Year: 2014

Population dynamics, economy, and human demography started with Malthus, the idea that population growth is limited by resources and "positive checks" occur when population growth overshoots the available resources. In fact, historical evidence indicates that long-term climate changes have destabilized civilizations and caused population collapses via food shortages, diseases, and wars. One of the worst population collapses of human societies occurred during the early fourteenth century in northern Europe; the "Great Famine" was the consequence of the dramatic effects of climate deterioration on human population growth. Thus, part of my motivation was to demonstrate that simple theoretical-based models can be helpful in understanding the causes of population change in preindustrial societies. Here, the results suggest that a logistic model with temperature as a "lateral" perturbation effect is the key element for explaining the population collapse exhibited by the European population during the "Great Famine". © 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

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