The genera and subgenera of the subtribe Aspilotina are reviewed. A new illustrated key to all accepted supraspecies taxa is provided. Grandilota Fischer, 2002, stat. nov. is proposed as subgenus of Aspilota Foerster, 1863. Carinthilota Fischer, 1975, syn. nov. is synonymised with Alitha Cameron, 1906, stat. nov. and the latter is treated as subgenus of Dinotrema Foerster, 1863; Eudinostigma Tobias, 1986, syn. nov. is considered a synonym of Dinotrema Foerster, 1863. Moreover, the new subgenus Pseudoprosaphasubgen. nov. (type species: Dinostigma stenosoma van Achterberg, 1988) is described. Additionally, Synaldotrema Belokobylskij & Tobias, 2002, stat. nov. is treated as a separate genus. The following new combinations are proposed: Aspilota (Aspilota) ruficollis Stelfox & Graham, 1950, comb. nov., Dinotrema (Alitha) lada (Belokobylskij, 1998), comb. nov., D. (A.) longipennis (Cameron, 1906), comb. nov., D. (A.) mavka (Belokobylskij, 1998), comb. nov., D. (A.) parapsidalis (Fischer, 1975), comb. nov., D. (A.) vechti (van Achterberg, 1988), comb. nov., Dinotrema (Dinotrema) alox (van Achterberg, 1988), comb. nov., D. (D.) entabeniense (Fischer, 2009), comb. nov., D. (D.) latum (Chen & Wu, 1994), comb. nov., D. (D.) planiceps (Fischer, Tormos & Pardo, 2006), comb. nov., D. (D.) subpulvinatum (Fischer, 2009), comb. nov., D. (Pseudoprosapha) stenosoma (van Achterberg, 1988), comb. nov., D. (Synaldis) bienesae (Fischer, Tormos & Pardo, 2006), comb. nov., D. (S.) fischeri (Tobias, 1986), comb. nov., D. (S.) latistigma (Fischer, 1962), comb. nov., D. (S.) planiceps (Fischer, Tormos & Pardo, 2006), comb. nov., D. (Synaldis) cespitator (Belokobylskij, 2004), comb. nov., D. (S.) perfidum (Fischer, 1970), comb. nov., D. (S.) trematosum (Fischer, 1967), comb. nov. and Panerema fulvicornis (Haliday, 1838), comb. nov.

The rhizosphere is a hot spot of soil microbial activity and is largely fed by root exudation. The carbon (C) exudation flux, coupled with plant growth, is considered a strategy of plants to facilitate nutrient uptake. C exudation is accompanied by a release of nutrients. Nitrogen (N) and phosphorus (P) co-limit the productivity of the plant-microbial system. Therefore, the C:N:P stoichiometry of exudates should be linked to plant nutrient economies, plant functional traits (PFT) and soil nutrient availability. We aimed to identify the strongest links in C:N:P stoichiometry among all rhizosphere components. A total of eight grass species (from conservative to exploitative) were grown in pots under two different soil C:nutrient conditions for a month. As a result, a wide gradient of plant–microbial–soil interactions were created. A total of 43 variables of plants, exudates, microbial and soil C:N:P stoichiometry, and PFTs were evaluated. The variables were merged into four groups in a network analysis, allowing us to identify the strongest connections among the variables and the biological meaning of these groups. The plant–soil interactions were shaped by soil N availability. Faster-growing plants were associated with lower amounts of mineral N (and P) in the soil solution, inducing a stronger competition for N with microorganisms in the rhizosphere compared to slower-growing plants. The plants responded by enhancing their N use efficiency and root:shoot ratio, and they reduced N losses via exudation. Root growth was supported either by reallocated foliar reserves or by enhanced ammonium uptake, which connected the specific leaf area (SLA) to the mineral N availability in the soil. Rapid plant growth enhanced the exudation flux. The exudates were rich in C and P relative to N compounds and served to release surplus metabolic products. The exudate C:N:P stoichiometry and soil N availability combined to shape the microbial stoichiometry, and N and P mining. In conclusion, the exudate flux and its C:N:P stoichiometry reflected the plant growth rate and nutrient constraints with a high degree of reliability. Furthermore, it mediated the plant–microbial interactions in the rhizosphere.

An in-depth descriptive approach to the dynamics of the urban population is fundamental as a first step towards promoting effective planning and designing processes in cities. Understanding the behavioral aspects of human activities can contribute to their effective management and control. We present a framework, based on statistical methods, for studying the spatio-temporal distribution of geolocated tweets as a proxy for where and when people carry out their activities. We have evaluated our proposal by analyzing the distribution of collected geolocated tweets over a two-week period in the summer of 2017 in Lisbon, London, and Manhattan. Our proposal considers a negative binomial regression analysis for the time series of counts of tweets as a first step. We further estimate a functional principal component analysis of second-order summary statistics of the hourly spatial point patterns formed by the locations of the tweets. Finally, we find groups of hours with a similar spatial arrangement of places where humans develop their activities through hierarchical clustering over the principal scores. Social media events are found to show strong temporal trends such as seasonal variation due to the hour of the day and the day of the week in addition to autoregressive schemas. We have also identified spatio-temporal patterns of clustering, i.e., groups of hours of the day that present a similar spatial distribution of human activities.

We evaluated the effectiveness of statistical operators Moran's I, Geary's C and Getis and Ord Gi in Landsat ETM satellite images to measure and analyze the spatial dependence of the spectral characteristics of the affected areas, comparing these results with those obtained in the use of spectral indices for discrimination of burned areas. The study was carried out using a multitemporal analysis (before and after the fire) in some areas located in the Tuparro National Park in the department of Vichada, in the northeastern part of the Orinoco region in Colombia, which were affected by the presence of this phenomenon. To perform the analysis used tools provided by the software R version 2.11.1, packages spdep and rgdal for handling raster data and calculation of spatial autocorrelation tests. The use of statistical operators provide better results with the band of near infrared (NIR) and allow better identification of burned areas, which facilitates the detection of spatial and spectral changes. This methodology provides information that can improve the monitoring of the effects of fire in time and helps to prevent possible disruption and the inventory of locations where this phenomenon has been presented.

(1) Modern, intensive agricultural practices have been attributed to the loss of insect biodiversity and abundance in agroecosystems for the last 80 years. The aim of this work is to test whether there are statistically significant differences in insect abundance between different zones and over time on the vineyard field. (2) The study was carried out in five intensive wine farms in Spain over a three-year period (2013–2015). Each field was divided into two zones, one where cover plants were planted, and another remained unchanged (without cover). (3) A clear trend to increase the average number of insect species and individuals throughout the years in all farms was observed. Moreover, the zones with cover plants showed a significant difference with respect to the zones without. (4) The use of permanent cover plants allows creating areas of refuge for the insects favouring their conservation and reducing the agriculture impact in the insect decline.

Starting in the 1950s, agricultural production has been remarkably intensified, resulting in modern management systems where a severe increase in field size led to an elimination of edges and other ecologically valuable structural elements. The resulting habitat loss caused dramatic changes in natural communities. The aim of this work is to test whether there are statistically significant differences in insect abundance over time by using multifunctional margins that are seed mixtures of autochthonous species planted in combined strips, which are the fastest way to provide significant biodiversity benefits within farmed landscapes, enhancing the diversity and abundance of insects, birds, and small mammals, offering resources and reservoirs. This study was carried out in three intensive fruit farms in Spain over a three-year period (2013–2015). Each field was divided into two zones: the margin where a multifunctional margin was planted, and another that remained unchanged in the field. A clear trend to increase RTE species throughout the years in all farms was observed. Moreover, the margin showed a significant difference with respect to the field in the average number of insect species and individuals. The use of margins improves the appearance of RTE species in mean percentages ranging between 12.06 and 25.26% according to the sampling area. Margins also favour the increase in species (148.83–232.84%) and individuals (207.24–586.70%) in agricultural landscapes. These results clearly show that margins are an essential tool to fight insect decline in intensive farming areas.