A probability-based multiscale model to quantify the impact of hydropeaking on mesohabitat suitability in rivers

One of the negative effects of hydropower on river environment includes rapid changes in flow and habitat conditions. Any sudden flow change could force fish to move towards a refuge area in a short period of time, causing serious disturbances in the life cycle of the fish. A probability-based multiscale model was developed to quantify the impact of hydropeaking on habitat suitability for two fish species. The model used habitat preference curves, river flow and depth to develop the suitability maps. The suitability index maps reveal that habitat suitability deteriorates as flow increases in this part of the river. The probability model showed that, on average, suitability indices are higher for adult grayling than juvenile trout in hydropeaking events in the studied area. In addition, the life stages of fish determine their response to the sudden flow change. The method developed shows the potential to be used in river management and the evaluation of hydropeaking impacts in river systems affected by hydropower.

Of Animal Husbandry and Food Production—A First Step towards a Modular Agent-Based Modelling Platform for Socio-Ecological Dynamics

Agent-based models provide detailed, bottom-up approaches to investigate complex socio-ecological systems. This study presents a first step towards a modular agent-based simulation that is based upon empirical data, as well as environmental suitability maps and an assessment of livestock units. To illustrate the capabilities of our simulation, we use a geographically explicit approach to simulate a component of the production of animal products of a rural settlement in the lower Bakırçay catchment, western Turkey. The model structurally couples various agent types representing several elements and processes of the animal husbandry and food production value chain, such as sedentary herders—practising daily, short-distance pastoralism—and their flocks of goats and sheep, as well as milking and slaughtering. The modelling tool captures the fundamental socio-ecological dynamics of animal husbandry and food production in rural settlements. Therefore, the tool is valuable as a basis to discuss hypotheses regarding the number of animals that are needed to cover the requirements of different growing populations.

Study of land suitability for rubber and cashew in the derived savanna zone of Edo State, Nigeria

This study attempted to assess the soil suitability in the derived savanna zone of Edo State, Nigeria for the cultivation of some tree crops. The research specifically aimed to evaluate soil suitability for cashew and rubber supported by suitability maps for both crops. In terms of land suitability evaluation, mapping units 1 and 2, with an area coverage of 27.4 ha of the entire research area (100 ha) were found to be marginally suitable (S3) for rubber cultivation but moderately suitable (S2) for cashew. Mapping unit 3, with area coverage of 38 ha was found to be currently not suitable (N1) for rubber but marginally suitable (S3) for cashew cultivation. Mapping unit 4 representing area coverage of 34.7 ha was found to be permanently not suitable (N2) for rubber cultivation but marginally suitable (S3) for cashew. Thus, technically, rubber can only be cultivated in that land at marginal level with an expected productivity of 27.4 ha (27.4 %). Cashew can be cultivated at moderate and marginal levels with an expected yield of 27.4 ha (27.4 %) and 72.6 ha (72.6 %), respectively, of the total land area. Thus, the preferred crop for the studied is cashew. It is recommended that for any significant investment in cultivation of this crop, the priority is the moderate levels with an expected productivity of 27.4 ha or 27.4 % of total land area.

A distribution model for Glossina brevipalpis and Glossina austeni in Southern Mozambique, Eswatini and South Africa for enhanced area-wide integrated pest management approaches

Background Glossina austeni and Glossina brevipalpis (Diptera: Glossinidae) are the sole cyclical vectors of African trypanosomes in South Africa, Eswatini and southern Mozambique. These populations represent the southernmost distribution of tsetse flies on the African continent. Accurate knowledge of infested areas is a prerequisite to develop and implement efficient and cost-effective control strategies, and distribution models may reduce large-scale, extensive entomological surveys that are time consuming and expensive. The objective was to develop a MaxEnt species distribution model and habitat suitability maps for the southern tsetse belt of South Africa, Eswatini and southern Mozambique. Methodology/Principal findings The present study used existing entomological survey data of G. austeni and G. brevipalpis to develop a MaxEnt species distribution model and habitat suitability maps. Distribution models and a checkerboard analysis indicated an overlapping presence of the two species and the most suitable habitat for both species were protected areas and the coastal strip in KwaZulu-Natal Province, South Africa and Maputo Province, Mozambique. The predicted presence extents, to a small degree, into communal farming areas adjacent to the protected areas and coastline, especially in the Matutuíne District of Mozambique. The quality of the MaxEnt model was assessed using an independent data set and indicated good performance with high predictive power (AUC > 0.80 for both species). Conclusions/Significance The models indicated that cattle density, land surface temperature and protected areas, in relation with vegetation are the main factors contributing to the distribution of the two tsetse species in the area. Changes in the climate, agricultural practices and land-use have had a significant and rapid impact on tsetse abundance in the area. The model predicted low habitat suitability in the Gaza and Inhambane Provinces of Mozambique, i.e., the area north of the Matutuíne District. This might indicate that the southern tsetse population is isolated from the main tsetse belt in the north of Mozambique. The updated distribution models will be useful for planning tsetse and trypanosomosis interventions in the area.

Evaluation of land suitability for Oilseeds crops (Sesame and Groundnut) using GIS and Multi-criteria evaluation: A case study of Diga District, East Wollega Zone, Western Ethiopia

Sesame and groundnut crops are the major oilseeds crops produced for exports and local consumptions in the Ethiopia. This study attempted to evaluate land suitability for oilseeds crops using Geographic Information Systems (GIS) and Multi-criteria evaluation (MCE), in the case of Diga district, East Wollega zone, Western Ethiopia. By integrating GIS and MCE techniques land suitability maps for sesame and groundnut were produced. Climate data (Temperature and rainfall), topography data (Slope), soil data (Soil texture, soil depth and soil drainage), infrastructure data (Road and market) were used in this study. The result of the study revealed that, about 252.1ha (0.4%) and 113.1ha (0.2%) were highly suitable for sesame and groundnut crops, respectively. Our results show that most parts of the study area were moderately suitable for sesame and groundnut production. Specially, the central and western parts of the study area are highly suitable and moderately suitable for sesame production. Findings of this study can support the farming communities and decision makers through providing highly productive areas for sesame and groundnut production.

Economic mapping and assessment of Cymodocea nodosa meadows as nursery grounds for commercially important fish species. A case study in the Canary Islands

Cymodocea nodosa seagrass meadows provide several socio-economically ecosystem services, including nurseries for numerous species of commercial interest. These seagrasses are experiencing a worldwide decline, with global loss rates approaching 5% per year, mainly related to coastal human activities. Cymodocea nodosa, the predominant seagrass in the Canary Archipelago (Spain), is also exposed to these threats, which could lead to habitat loss or even local disappearance. In this case study, we estimated the potential economic value of Cymodocea nodosa seagrass meadows for local fisheries at an archipelago scale. Habitat suitability maps were constructed using MAXENT 3.4.1, a software for modelling species distributions by applying a maximum entropy machine-learning method, from a set of environmental variables and presence and background records extracted from historical cartographies. This model allows characterising and assessing the C. nodosa habitat suitability, overcoming the implicit complexity derived from seasonal changes in this species highly dynamic meadows and using it as a first step for the mapping and assessment of ecosystem services. In a second step, value transfer methodologies were used, along with published economic valuations of commercially-interesting fish species related to C. nodosa meadows. We estimate that the potential monetary value of these species can add up to more than 3 million euros per year for the entire Archipelago. The simplicity of the proposed methodology facilitates its repeatability in other similar regions, using freely available data and hence, being suitable for data-scarce scenarios.

Identification of suitable sites for managed aquifer recharge under semi-arid conditions employing a combination of numerical and analytical techniques

Overpumping or overexploitation of groundwater is one of the major threats for aquifer systems in arid and semi-arid areas. Managed aquifer recharge (MAR) has been suggested by many researchers as a sustainable and effective method to alleviate negative impacts of overpumping. Optimizing artificial recharge considers the selection of suitable MAR sites in terms of surface and subsurface characteristics. While surface characteristics at potential MAR sites could be modified (e.g. slope, soil texture, etc.), subsurface characteristics cannot be changed through engineering work. Characteristics of the aquifer, such as depth to groundwater, play an important role in determining the capability of an aquifer to store a specific volume of infiltrated water. Currently, only a limited number of quoted researches are available that consider factors related to aquifer characteristics and the range of these factors to identify optimal MAR sites. In this study, a new approach is presented, that employs numerical groundwater modeling to generate MAR suitability maps considering sub-surface characteristics, such as depth-to-groundwater, aquifer transmissivity and specific yield. Multiple model-runs are conducted to simulate groundwater table response with respect to the volume of infiltrated water. Simulation results are used to calibrate a groundwater mound empirical equation that calculates the groundwater level increase as a function of the transmissivity and infiltrated water volume for a given value of aquifer’ specific yield, range of vertical hydraulic conductivities and a specific design and operation conditions of the MAR system. The empirical equation is employed in GIS to spatially calculate the height of groundwater mound beneath a hypothetical MAR site and to generate, based on that, suitability maps for MAR implementation. Assuming that MAR structures capture the median of monthly surface runoff rates at the respective wadi (catchment area), suitability maps are generated for different configurations/scenarios of aquifer hydraulic conductivity in a parameter study. The results highlight the importance of integrating aquifer characteristics (geometry and hydraulic parameters) and expected magnitudes and fluxes of infiltration water in delineating suitable sites for MAR.

Increasing reality of species distribution models of consumers by including its food resources

Species distribution models are not usually calibrated with biotic predictors. Our study question is: does the use of biotic predictors matter in predicting species distribution? We aim to assess the importance of biotic predictors in the output of distribution models of the Brazilian squirrel (Sciurus aestuans) throughout South America based on fruits of Syagrus romanzoffiana – the most consumed food resource. We hypothesized that the distribution model of S. aestuans using its main food resource as a biotic predictor will be more accurate in comparison with the output of the model without the biotic predictor. We built three different distribution models: (i) distribution of S. romanzoffiana; (ii) distribution of S. aestuans without biotic predictor; and (iii) distribution of S. aestuans with biotic predictor. We evaluated performance scores, number of presence pixels and concordance between suitability maps. We found that performance scores may not vary between models with different predictors, but the output map changed significantly. We also found that models with biotic predictors seem to vary less in presence pixels. Furthermore, the main variable in the distribution model was the biotic variable. We conclude that the knowledge of a species’ biology and ecology can make better predictions of species distribution models mainly by avoiding commission errors.

Planning and Suitability Assessment of Large-scale Nature-based Solutions for Flood-risk Reduction

Adverse effects of climate change are increasing around the world and the floods are posing significant challenges for water managers. With climate projections showing increased risks of storms and extreme precipitation, the use of traditional measures alone is no longer an option. Nature-Based Solutions (NBS) offer a suitable alternative to reduce the risk of flooding and provide multiple benefits. However, planning such interventions requires careful consideration of various factors and local contexts. The present paper provides contribution in this direction and it proposes a methodology for allocation of large-scale NBS using suitability mapping. The methodology was implemented within the toolboxes of ESRI ArcMap software in order to map suitability for four types of NBS interventions: floodplain restoration, detention basins, retention ponds, and river widening. The toolboxes developed were applied to the case study area in Serbia, i.e., the Tamnava River basin. Flood maps were used to determine the volume of floodwater that needs to be stored for reducing flood risk in the basin and subsequent downstream areas. The suitability maps produced indicate the potential of the new methodology and its application as a decision-support tool for selection and allocation of large-scale NBS.

Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data

Pogosta disease is a mosquito-borne infection, caused by Sindbis virus (SINV), which causes epidemics of febrile rash and arthritis in Northern Europe and South Africa. Resident grouse and migratory birds play a significant role as amplifying hosts and various mosquito species, including Aedes cinereus, Culex pipiens, Cx. torrentium and Culiseta morsitans are documented vectors. As specific treatments are not available for SINV infections, and joint symptoms may persist, the public health burden is considerable in endemic areas. To predict the environmental suitability for SINV infections in Finland, we applied a suite of geospatial and statistical modeling techniques to disease occurrence data. Using an ensemble approach, we first produced environmental suitability maps for potential SINV vectors in Finland. These suitability maps were then combined with grouse densities and environmental data to identify the influential determinants for SINV infections and to predict the risk of Pogosta disease in Finnish municipalities. Our predictions suggest that both the environmental suitability for vectors and the high risk of Pogosta disease are focused in geographically restricted areas. This provides evidence that the presence of both SINV vector species and grouse densities can predict the occurrence of the disease. The results support material for public-health officials when determining area-specific recommendations and deliver information to health care personnel to raise awareness of the disease among physicians.