Search

Tourist disturbance in semi–arid springs was analysed; birds and fish were selected as bioindicators. Media Luna spring is the biggest and most spatially complex system in the region, with the highest biodiversity levels and tourist use. Areas with the highest bird species richness and abundances showed highest structural heterogeneity and least direct human impact. No differences in species richness of fish were observed between sectors and the most abundant species were found in the sectors least perturbed by human activity. Factors that explained the bird distribution were the species´ tolerance to the effects of direct tourism (noise and direct presence of people) and habitat quality, mainly riparian vegetation. Aquatic vegetation condition was very important for fish. Six bird species and two fish species were relevant as indicators of the habitat quality related to human impact. Anthropic disturbance such as tree plantation favoured some bird species, whereas aquatic vegetation removal was favourable for some fish species, such as the endemic Cichlasoma bartoni, however, both types of disturbance were unfavourable for other species; riparian vegetation removal was negative for both groups. Controlled tourism promotes good conditions for C. bartoni establishment. Efficient conservation measures such as limiting touristic distribution are necessary for all species, especially for the fish community, in order to conserve biodiversity in general.

Global warming is producing negative effects on agriculture, changing the distribution and production of vulnerable crops. This phenomenon could also modify the production and distribution of plant species. Agroecosystems are highly diverse systems which could potentially reduce the impact of climate change. The following research work is founded due to this situation. The main objective of this study is to assess the impact of climate change on an unconventional agricultural system. Agroecosystems in the State of Puebla (Mexico) were analyzed under the horizons of the present, 2020, 2050 and 2080 under different socioeconomic scenarios (A1B, A2A, B1 and B2), to identify which areas could present changes in the distribution of at least 3 species in the State of Puebla. Three races of maize: Conico, Elotes conicos y Tuxpeno (Zea mays ssp. mays) were selected, and the most important crops from the state of Puebla: bean (Phaseolus vulgaris), amaranth (Amaranthus hypochondracus), courgette (Cucurbita pepo), coffee (Coffea arabica), chili (Capsicum frutescens), sugar cane (Saccharum officinarum), potato (Solanum tuberosum), avocado (Persea americana), apple (Malus domestica), peach (Prunus persica), orange (Citrus sinensis), Mexican hawthorn (Crataegus pubescens), and wheat (Triticum spp). We built niche models for some species and determinated the overlap areas (agroecosystems) with special emphasis on maize races. Our results showed an important persistence of different agroecosystems (73% of the territory in Puebla). These systems are likely to increase their surface area under scenario A1B and B1, while in the A2A and B2 scenarios the impact of climate change is greater in agroecosystems. In the first case, agroecosystems lose in average up to 13% of surface area, and 12% for the second scenario. Finally the growth margin is 8% compared to the A1B and B1 models. We determinate vulnerability areas to global change in the southwestern of Puebla (maize origin center) and the north (rainforest protect area). [ABSTRACT FROM AUTHOR]

Mosquito-borne diseases account for human morbidity and mortality worldwide, caused by the parasites (e.g., malaria) or viruses (e.g., dengue, Zika) transmitted through bites of infected female mosquitoes. Globally, billions of people are at risk of infection, imposing significant economic and public health burdens. As such, efficient methods to monitor mosquito populations and prevent the spread of these diseases are at a premium. One proposed technique is to apply acoustic monitoring to the challenge of identifying wingbeats of individual mosquitoes. Although researchers have successfully used wingbeats to survey mosquito populations, implementation of these techniques in areas most affected by mosquito-borne diseases remains challenging. Here, methods utilizing easily accessible equipment and encouraging community-scientist participation are more likely to provide sufficient monitoring. We present a practical, community-science-based method of monitoring mosquito populations using smartphones. We applied deep-learning algorithms (TensorFlow Inception v3) to spectrogram images generated from smartphone recordings associated with six mosquito species to develop a multiclass mosquito identification system, and flag potential invasive vectors not present in our sound reference library. Though TensorFlow did not flag potential invasive species with high accuracy, it was able to identify species present in the reference library at an 85% correct identification rate, an identification rate markedly higher than similar studies employing expensive recording devices. Given that we used smartphone recordings with limited sample sizes, these results are promising. With further optimization, we propose this novel technique as a way to accurately and efficiently monitor mosquito populations in areas where doing so is most critical., (© The Author(s) 2021. Published by Oxford University Press on behalf of Entomological Society of America.All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Around 27% of South Americans live in central and southern Brazil. Of 19,400 human malaria cases in Brazil in 2018, some were from the southern and southeastern states. High abundance of malaria vectors is generally positively associated with malaria incidence. Expanding geographic distributions of Anopheles vector mosquito species (e.g. A. cruzii) in the face of climate change processes would increase risk of such malaria transmission; such risk is of particular concern in regions that hold human population concentrations near present limits of vector species' geographic distributions. We modeled effects of likely climate changes on the distribution of A. cruzii, evaluating two scenarios of future greenhouse gas emissions for 2050, as simulated in 21 general circulation models and two greenhouse gas scenarios (RCP 4.5 and RCP 8.5) for 2050. We tested 1305 candidate models, and chose among them based on statistical significance, predictive performance, and complexity. The models closely approximated the known geographic distribution of the species under current conditions. Under scenarios of future climate change, we noted increases in suitable area for the mosquito vector species in São Paulo and Rio de Janeiro states, including areas close to 30 densely populated cities. Under RCP 8.5, our models anticipate areal increases of >75% for this important malaria vector in the vicinity of 20 large Brazilian cities. We developed models that anticipate increased suitability for the mosquito species; around 50% of Brazilians reside in these areas, and ∼89% of foreign tourists visit coastal areas in this region. Under climate change thereefore, the risk and vulnerability of human populations to malaria transmission appears bound to increase., (Copyright © 2021. Published by Elsevier B.V.)

Lycoriella species (Sciaridae) are responsible for significant economic losses in greenhouse production (e.g., mushrooms, strawberries, and nurseries). The current distributions of species in the genus are restricted to cold-climate countries. Three species of Lycoriella are of particular economic concern in view of their ability to invade areas in countries across the Northern Hemisphere. We used ecological niche models to determine the potential for range expansion under future climate change scenarios (RCP 4.5 and RCP 8.5) in the distribution of these three species of Lycoriella . Stable environmental suitability under climate change was a dominant theme in these species; however, potential range increases were noted in key countries (e.g., USA, Brazil, and China). Our results illustrate the potential for range expansion in these species in the Southern Hemisphere, including some of the highest greenhouse production areas in the world.

Climate change ranks among the most important issues globally, affecting geographic distributions of vectors and pathogens, and inducing losses in livestock production among many other damaging effects. We characterized the potential geographic distribution of the ticks Rhipicephalus (Boophilus) microplus, an important vector of babesiosis and anaplasmosis globally. We evaluated potential geographic shifts in suitability patterns for this species in two periods (2050 and 2070) and under two emissions scenarios (RCPs 4.5 and 8.5). Our results anticipate increases in suitability worldwide, particularly in the highest production areas for cattle. The Indo-Malayan region resulted in the highest cattle exposure under both climate change projections (2050), with increases in suitability of > 30%. This study illustrates how ecological niche modeling can be used to explore probable effects of climate change on disease vectors, and the possible consequences on economic dimensions.

We point out complications inherent in biodiversity inventory metrics when applied to large-scale datasets. The number of units of inventory effort (e.g., days of inventory effort) in which a species is detected saturates, such that crucial numbers of detections of rare species approach zero. Any rare errors can then come to dominate species richness estimates, creating upward biases in estimates of species numbers. We document the problem via simulations of sampling from virtual biotas, illustrate its potential using a large empirical dataset (bird records from Cape May, NJ, USA), and outline the circumstances under which these problems may be expected to emerge., Competing Interests: The authors declare that they have no competing interests., (© 2020 Khalighifar et al.)

Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions., (© 2018 New York Academy of Sciences.)

The Media Luna lake-spring was selected as representative of all thermal or no thermal springs in the zone of Valley of Rioverde, a semi-arid vegetation in the North-eastern of Mexico. This system is inhabited by 11 fish species, of which six are native. Four of the native species are endemic to the region and threatened due to touristic pressure and to the introduction of exotic species. The objectives were to determine the characteristics that influence the spatial distribution of the fish species, to analyze their spatial distribution patterns, and to describe the relationships between the different species. The general aim was to establish some basis for the conservation of these fish communities and their habitat. Several sessions were initiated in 1992 through direct observation. Later, between 1998 and 1999 five systematically seasonal sampling sessions were conducted (54 subaquatic transects/session). Finally, the data was updated by sampling in summer 2002 and winter 2006. Through the analysis was performed only for endemics of the region, like Ataeniobius toweri Meek, Cualac tessellatus Miller, Cichlasoma bartoni Bean and C. labridens Pellegrin, in at least one life stage, showed correlation with habitat variables or with other species. For these species, patterns of spatial aggregation and association with other species were observed. These results show a certain degree of specialization of endemic species to some microhabitat characteristics, as well as a significant interaction with other native species which they coexist. In addition, some significant relations between endemic and alien species suggest an antagonist relation. Management actions focused in the touristic use of the spring represent the main threat for these species, followed by an adequate management of exotic species. This study provides basis for future responsible management of these wetlands, where tourism and conservation can be combined.