Detection of active oxalate-carbonate pathway ecosystems in the Amazon Basin: Global implications of a natural potential C sink

The oxalate-carbonate pathway (OCP) is a biogeochemical process, which has been described in Milicia excelsa tree ecosystems of Africa. This pathway involves biological and geological parameters at different scales: oxalate, as a by-product of photosynthesis, is oxidized by oxalotrophic bacteria leading to a local pH increase, and eventually to carbonate accumulation through time in previously acidic and carbonate-free tropical soils. Former studies have shown that this pedogenic process can potentially lead to the formation of an atmospheric carbon sink. Considering that 80% of plant species are known to produce oxalate, it is reasonable to assume that M. excelsa is not the only tree that can support OCP ecosystems. The search for similar conditions on another continent led us to South America, in an Amazon forest ecosystem (Alto Beni, Bolivia). This area was chosen because of the absence of local inherited carbonate in the bedrock, as well as its expected acidic soil conditions. Eleven tree species and associated soils were tested positive for the presence of carbonate with a more alkaline soil pH close to the tree than at a distance from it. A detailed study of Pentaplaris davidsmithii and Ceiba speciosa trees showed that oxalotrophy impacted soil pH in a similar way to at African sites (at least with 1 pH unit increasing). African and South American sites display similar characteristics regarding the mineralogical assemblage associated with the OCP, except for the absence of weddellite. The amount of carbonate accumulated is 3 to 4 times lower than the values measured in African sites related to M. excelsa ecosystems. Still, these secondary carbonates remain critical for the continental carbon cycle, as they are unexpected in the acidic context of Amazonian soils. Therefore, the present study demonstrates the existence of an active OCP in South America. The three critical components of an operating OCP are the presence of: i) local alkalinization, ii) carbonate accumulations, and iii) oxalotrophic bacteria, which were identified associated to the oxalogenic tree C. speciosa. If the question of a potential carbon sink related to oxalotrophic-oxalogenic ecosystems in the Amazon Basin is still pending, this study highlights the implication of OCP ecosystems on carbon and calcium biogeochemical coupled cycles. As previously mentioned for M. excelsa tree ecosystems in Africa, carbonate accumulations observed in the Bolivian tropical forest could be extrapolated to part or the whole Amazon Basin and might constitute an important reservoir that must be taken into account in the global carbon balance of the Tropics.

Representativeness of terrestrial ecosystems in Chile's protected area system

Because protected areas are a major means of conservation, the extent to which ecosystems are represented under different protection regimes needs to be ascertained. A gap analysis approach was used to assess the representativeness of Chile's terrestrial ecosystems in differing kinds of protected areas. Terrestrial ecosystems were described in terms of potential vegetation, employing three protection scenarios. Scenario 1 was based exclusively on the Chilean National System of Protected Wild Areas (SNASPE). Scenario 2 included all types of public protected areas, namely SNASPE, nature sanctuaries and Ministry of National Heritage lands. Scenario 3 included all items in Scenario 2, but also included private protected areas and biodiversity priority sites. There is insufficient protection of terrestrial ecosystems under the Scenario 2. In addition to the low level of ecosystem protection provided by state protected areas (only 42 of the 127 terrestrial ecosystems had >10% of their area protected), 23 terrestrial ecosystems were identified as having no protection at the national level. Gaps in protection were concentrated in the North (both coastal and inland desertic scrub), Central (thorny scrub, thorny forests, sclerophyllous forests and deciduous coastal forests) and Austral (steppe ecosystems) regions of Chile. These gaps include ecosystems that are of global conservation importance.

A spatial modelling framework for assessing climate change impacts on freshwater ecosystems: Response of brown trout (Salmo trutta L.) biomass to warming water temperature

Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-

Validation of and comparison between a semidistributed rainfall-runoff hydrological model (PREVAH) and a spatially distributed snow-evolution model (SnowModel) for snow cover prediction in mountain ecosystems

Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder.

Predicting the future effectiveness of protected areas for bird conservation in Mediterranean ecosystems under climate change and novel fire regime scenarios

AimGlobal environmental changes challenge traditional conservation approaches based on the selection of static protected areas due to their limited ability to deal with the dynamic nature of driving forces relevant to biodiversity. The Natura 2000 network (N2000) constitutes a major milestone in biodiversity conservation in Europe, but the degree to which this static network will be able to reach its long-term conservation objectives raises concern. We assessed the changes in the effectiveness of N2000 in a Mediterranean ecosystem between 2000 and 2050 under different combinations of climate and land cover change scenarios. LocationCatalonia, Spain. MethodsPotential distribution changes of several terrestrial bird species of conservation interest included in the European Union's Birds Directive were predicted within an ensemble-forecasting framework that hierarchically integrated climate change and land cover change scenarios. Land cover changes were simulated using a spatially explicit fire-succession model that integrates fire management strategies and vegetation encroachment after the abandonment of cultivated areas as the main drivers of landscape dynamics in Mediterranean ecosystems. ResultsOur results suggest that the amount of suitable habitats for the target species will strongly decrease both inside and outside N2000. However, the effectiveness of N2000 is expected to increase in the next decades because the amount of suitable habitats is predicted to decrease less inside than outside this network. Main conclusionsSuch predictions shed light on the key role that the current N2000may play in the near future and emphasize the need for an integrative conservation perspective wherein agricultural, forest and fire management policies should be considered to effectively preserve key habitats for threatened birds in fire-prone, highly dynamic Mediterranean ecosystems. Results also show the importance of considering landscape dynamics and the synergies between different driving forces when assessing the long-term effectiveness of protected areas for biodiversity conservation.