Eco-morphodynamic carbon pumping by the largest rivers in the Neotropics

AbstractThe eco-morphodynamic activity of large tropical rivers in South and Central America is analyzed to quantify the carbon flux from riparian vegetation to inland waters. We carried out a multi-temporal analysis of satellite data for all the largest rivers in the Neotropics (i.e, width > 200 m) in the period 2000–2019, at 30 m spatial resolution. We developed a quantification of a highly efficient Carbon Pump mechanism. River morphodynamics is shown to drive carbon export from the riparian zone and to promote net primary production by an integrated process through floodplain rejuvenation and colonization. This pumping mechanism alone is shown to account for 8.9 million tons/year of carbon mobilization in these tropical rivers. We identify signatures of the fluvial eco-morphological activity that provide proxies for the carbon mobilization capability associated with river activity. We discuss river migration—carbon mobilization nexus and effects on the carbon intensity of planned hydroelectric dams in the Neotropics. We recommend that future carbon-oriented water policies on these rivers include a similar analysis

Quantitative habitat models for the conservation of the endangered European crayfish Austropotamobius pallipes complex (Astacoidea: Astacidae)

Crayfish are the largest mobile freshwater invertebrates and are keystone species in European aquatic ecosystems particularly in small streams and rivers. The white-clawed crayfish Austropotamobius pallipes (a species complex) is currently classified by the IUCN Red List as an endangered species (EN), because its populations have decreased significantly over the last decades in a number of European countries including Italy, due mainly to habitat modifications and the introduction and spread of alien species. Data on the ecological requirements of A. pallipes are needed to quantify the effects of habitat alteration, to simulate restoration scenarios, and to implement effective conservation measures for this species. We describe here a new methodology for modelling the habitat requirements for this endangered crayfish using the mesohabitat scale approach based on data from crayfish living in small streams draining the Italian foothills of the Alps (Lombardy region) and in streams in the mountainous areas of the Gran Sasso and Monti della Laga National Park (Abruzzo region). Data from seven morphologically different streams were used to train and validate the habitat models. The Random Forests algorithm was used to identify the best and most parsimonious habitat model, and to define the lowest number of variables to be surveyed in the future. The best habitat models were applied to each stream and used to classify each mesohabitat into suitability categories. Habitat flow-rating curves were developed to analyze spatio-temporal variation of habitat availability, and habitat time series analysis were used to define detailed management schemes for environmental river management. Flow releases and water temperature regimes were assessed for individual water diversions in order (1) to represent how physical habitat changes through time, and (2) to identify stress conditions for A. pallipes created by the persistent limitation of habitat availability. Results indicated that the kind of substrate in the stream bed (such as the proportion of fine-grained substrates), the water depth (whether shallow or deep), and the available cover (such as the presence of boulders, woody debris, and undercut banks) were all significant factors governing the occurrence of crayfish. The habitat models performed well in both calibration and validation phases (with accuracy ranging from 71% to 79% in training and from 69% to 73% in validation) and can be considered to be a valuable tool to predict the distribution of A. pallipes over a wide range of stream types. An example of how to establish environmental standards for small streams is presented. The proposed habitat model provides a useful tool that can be applied even when other commonly used methodologies are unsuitable. As such, this habitat model can be used to develop regional rules for the conservation of the endangered crayfish A. pallipes complex and for defining more site-specific management criteria

An integrated methodology for the riparian vegetation modelling

We propose a methodology to calibrate a stochastic model for riparian vegetation dynamics that is based on real data. The methodology integrates various tools that are often used individually in fluvial investigations and it is here applied to the case of the Cinca river (Spain), aiming to explore how its riparian vegetation responds to changing climate conditions

Calibration of a stochastic model for riparian vegetation dynamics from LiDAR acquisitions

The distribution of phreatophyte riparian vegetation can be described by a stochastic model for vegetation growth. According to this, vegetation dynamics are influenced by the topography of the riparian transect and the randomness of hydrological fluctuations, acting as a dichotomous Markov noise. Also, the response of vegetation to this forcing, i.e. its rate of growth and decay, depends of its intrinsic biological features, which are represented in the model by specific input parameters. Although most of these parameters has already been set and literature values provided for the most common tree species in riparian environments, the one representing the vegetation decay still needs to be properly calibrated. To this purpose, a segment of Cinca River (Spain) is here modelled, aiming to obtain a calibration of the decay rate of riparian vegetation in temperate climate. The choice of the study river was done according to the availability of hydrological and LiDAR data. The processing of LiDAR raw data allowed to define the digital terrain model of the study area, providing the geometrical input data of the model. Moreover, LiDAR acquisitions returned a measure of vegetation height and its spatial density, thus leading to the estimation of riparian above-ground biomass, which represents the model output. As the decay rate was the sole unknown parameter for the modelling of the study river, its calibration was possible. Furthermore, as LiDAR provided a highly detailed geometry, the outcome of calibration was not a single value of decay rate for the entire riparian corridor, but a set of values for increasing altitude bands, thus allowing the investigation of its relation with topographic positio

Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.)

The impacts of invasive species are recognised as a major threat to global freshwater biodiversity. The risk of invasion (probability of presence) of two avowed invasive species, the northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.), was evaluated in the upper part of the Cabriel River (eastern Iberian Peninsula). Habitat suitability models for these invasive species were developed with Support Vector Machines (SVMs), which were trained with data collected downstream the Contreras dam (the last barrier impeding the invasion of the upper river segment). Although SVMs gained visibility in habitat suitability modelling, they cannot be considered widespread in ecology. Thus, with this technique, there is certain controversy about the necessity of performing variable selection procedures. In this study, the parameters tuning and the variable selection for the SVMs was simultaneously performed with a genetic algorithm and, contradicting previous studies in freshwater ecology, the variable selection proved necessary to achieve almost perfect accuracy. Further, the development of partial dependence plots allowed unveiling the relationship between the selected input variables and the probability of presence. Results revealed the preference of northern pike for large and wide mesohabitats with vegetated shores and abundant prey whereas bleak preferred deep and slightly fast flow mesohabitats with fine substrate. Both species proved able to colonize the upper part of the Cabriel River but the habitat suitability for bleak indicated a slightly higher risk of invasion. Altogether may threaten the endemic species that actually inhabit that stretch, especially the Jucar nase (Parachondrostoma arrigonis; Steindachner), which is one of the most critically endangered Iberian freshwater fish species. (C) 2016 Elsevier B.V. All rights reserved.The study has been partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economia y Competitividad) and by the Confederacion Hidrografica del Jucar (Spanish Ministry of Agriculture, Food and Environment). We also want to thank all the colleagues who worked in the field data collection, especially Rui M. S. Costa and Aina Hernandez. Finally, we are especially grateful to Esther Lopez Fernandez who kindly and selflessly posed for the graphical abstract.Muñoz Mas, R.; Vezza, P.; Alcaraz-Hernández, JD.; Martinez-Capel, F. (2016). Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.). Ecological Modelling. 342:123-134. https://doi.org/10.1016/j.ecolmodel.2016.10.006S12313434

Transferability Of Mesohabitat Suitability Criteria In Northern Italy

In the framework of water resources planning and management, the MesoHABSIM (MesoHABitat SImulation Model) approach demonstrated high potential to assess suitable environmental conditions for freshwater fish species. In the present study, the transferability capabilities of mesohabitat suitability criteria were evaluated in nine streams across Northern Italy. In particular, the Random Forest (RF) technique was used to calibrate and validate suitability criteria for adult and juvenile life stages of brown trout (Salmo trutta), marble trout (Salmo marmoratus), bullhead (Cottus gobio) Italian barbel (Barbus plebejus), and Italian vairone (Telestes muticellus). Presence/absence binary models were calibrated at the mesohabitat scale (i.e., the geomorphic unit scale) using field data collected in reference sites, selected for their natural hydro-morphological conditions and habitat characteristics. Model transferability tests were performed in streams located in different regions within the distribution area of the fish and not included in the model calibration dataset. Predictive capacities of the models were very good in terms of accuracy (ranging from 75% to 82%) and true skill statistic (ranging from 52% to 75%). The high predictive performances can be related to (i) the use of an ecologically relevant spatial resolution (mesohabitat) to predict fish presence, (ii) a robust and adequate hydro-morphological characterization of the analyzed geomorphic units, and (iii) the large number of mesohabitat descriptors provided by the MesoHABSIM approach. Results showed that mesohabitat suitability criteria based on RF can be considered transferable among streams located in different regions of Northern Italy, especially when river channels are characterized by similar hydro-morphological characteristics