Species Distribution Modeling for Conservation Purposes

Species distribution models (SDMs) can be useful for different conservation purposes. We discuss the importance of fitting spatial scale and using current records and relevant predictors aiming conservation. We choose jaguar (Panthera onca) as a target species and Brazil and Atlantic Forest biome as study areas. We tested two different extents (continent and biome) and resolutions (similar to 4 Km and similar to 1 Km) in Maxent with 186 records and 11 predictors (bioclimatic, elevation, land-use and landscape structure). All models presented satisfactory AUC values (>0.70) and low omission errors (<23%). SDMs were scale-sensitive as the use of reduced extent implied in significant gains to model performance generating more constrained and real predictive distribution maps. Continental-scale models performed poorly in predicting potential current jaguar distribution, but they reached the historic distribution. Specificity increased significantly from coarse to finer-scale models due to the reduction of overprediction. The variability of environmental space (E-space) differed for most of climatic variables between continental and biome-scale and the representation of the E-space by predictors differed significantly (t = 2.42, g.I. = 9, P < 0.05). Refining spatial scale, incorporating landscape variables and improving the quality of biological data are essential for improving model prediction for conservation purposes.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP

APRENDIZAGEM BASEADA EM PROBLEMAS SOCIOAMBIENTAIS DE PIRACICABA

A interação entre os municípios e universidades pode fornecer poderosas ferramentas na resolução de problemas socioambientais locais. Apresentamos aqui os processos de construção e os resultados de uma dessas formas de interação. A disciplina Ecologia Aplicada é destinada aos ingressantes do curso de Ciências Biológicas da Escola Superior de Agricultura “Luiz de Queiroz” (ESALQ/USP), em Piracicaba, São Paulo. Nela, grupos de alunos, com a ajuda de um tutor e sempre monitorados pelos docentes responsáveis, trabalham na resolução de problemas socioambientais, contando com a Aprendizagem Baseada em Problemas. No primeiro semestre de 2020, excepcionalmente, em contexto da pandemia da COVID-19, a disciplina foi oferecida a distância e sem as excursões nas quais os problemas socioambientais a serem trabalhados seriam identificados. Para sua realização, o ambiente virtual da universidade foi fundamental em todas as etapas. A cada aluno foi pedido que identificasse questões ambientais no município de Piracicaba. Os docentes formaram grupos de alunos por afinidade de assunto. Cada grupo escolheu um problema ambiental a ser trabalhado durante o semestre. Após trabalharem com os tutores ao longo do semestre, os alunos propuseram resoluções a seus problemas ambientais. Os trabalhos foram considerados pelos docentes de alta qualidade, tendo muitos grupos chegado a resultados que podem futuramente se transformar em políticas públicas. Alguns grupos produziram material informativo à sociedade, outros criaram perfis em redes sociais para comunicação. A Aprendizagem Baseada em Problemas se mostrou válida para promover reflexões e buscar soluções para problemas do município

Land-use changes lead to functional loss of terrestrial mammals in a Neotropical rainforest

Land-use changes are a main driver of modifications in tropical ecosystems, leading to the loss of species and ecological traits and affecting key ecological functions. Although much attention has been given to predict the effects of species loss on ecological processes, information on the large-scale effects of land-use changes over ecological functions is scarce. Here, we detected erosion in the prevalence of ecological functions performed by mammals in response to land-use changes in the Atlantic Forest of Brazil. By analyzing the loss of different ecological functions (vertebrate and invertebrate predation, seed dispersal, seed depredation, herbivory) performed by mammal assemblages in a deforestation gradient, we observed that vulnerable functions (performed by sensitive species, such as browsing, seed depredation, medium and large vertebrate predation) were positively related to patch size and forest cover and negatively related to anthropogenic cover. These relationships were reversed for persistent functions (performed by resilient species, such as grazing, small seed dispersal, small vertebrate and invertebrate predation). Vulnerable functions were virtually restricted to large forest remnants, while persistent functions were prevalent in human-modified landscapes. Disturbed forests are not necessarily empty of mammal species, but there is a substantial loss of ecological functions across most of the Atlantic Forest. Five out of ten ecological functions lose prevalence in small forest remnants. Nonetheless, these small remnants serve as refuges for the remaining biodiversity and are on the verge of the functional extinction of important processes. The erosion of ecological functions provided by mammals compromise the persistence of Atlantic Forest's biodiversity. (C) 2021 Associacao Brasileira de Ciencia Ecologica e Conservacao. Published by Elsevier B.V.Peer reviewe

Predicting the current distribution of the chacoan peccary (catagonus wagneri) in the gran Chaco

The Chacoan peccary (Catagonus wagneri), or Tagua, an endemic species living in the Chaco eco¬region, is endangered by highly increasing deforestation rates across the region, particularly in the last decade. This situation highlights the need to better understand the current distribution of the species, as well as how environmental conditions affect habitat suitability. This study predicts the distribution of the Chacoan peccary and evaluates the current environmental conditions in the Chaco for this species. Using six environmental variables and 177 confirmed occurrence records (from 2000 to 2015) provided by researchers, we developed a Species Distribution Model (SDM) applying the Maxent algorithm. The final model was highly accurate and significant (p < 0.001; AUC 0.860 ± 0.0268; omission error 1.82 %; post¬hoc validation of omission error using independent presence¬only records 1.33 %), predicting that 46.24 % of the Chaco is suitable habitat for the Chacoan peccary, with the most important areas concentrated in the middle of Paraguay and northern Argentina. Land cover, isothermality and elevation were the variables that better explained the habitat suitability for the Chacoan peccary. Despite some portions of suitable areas occurring inside protected areas, the borders and the central portions of suitable areas have recently suffered from intensive deforestation and development, and most of the highly suitable areas for the species are not under protection. The results provide fundamental insights for the establishment of priority Chacoan peccary conservation areas within its rangeFil: Paschoaletto Micchi, Katia Maria. Universidade Do Sao Paulo. Escola Superior de Agricultura Luiz de Queiroz Esalq; Brasil. Conservation Breeding Specialist Group Brazilian network; BrasilFil: Silva Angelieri, Cintia Camila. Universidade Do Sao Paulo. Escola Superior de Agricultura Luiz de Queiroz Esalq; BrasilFil: Altrichter, Mariana. Prescott College; Estados UnidosFil: Desbiez, Arnaud. Royal Zoological Society of Scotland. Edimburgo; Reino Unido. Conservation Breeding Specialist Group Brazilian network; BrasilFil: Yanosky, Alberto. Asociación Guyra Paraguay. Asunción; ParaguayFil: Campos Krauer, Juan Manuel. Centro Chaqueño para la Conservación y la Investigación; ParaguayFil: Torres, Ricardo Jose. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; ArgentinaFil: Camino, Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; ArgentinaFil: Cabral, Hugo. Asociación Guyra Paraguay. Asunción; ParaguayFil: Cartés, José. Asociación Guyra Paraguay. Asunción; ParaguayFil: Cuellar, Rosa Leny. Fundación Kaa Iya; BoliviaFil: Gallegos, Marcelo. Secretaría de Ambiente de la Provincia de Salta. Programa Guardaparques; ArgentinaFil: Giordano, Anthony J.. No especifica;Fil: Decarre, Julieta. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; ArgentinaFil: Maffei, Leonardo. Wildlife Conservation Society. Lima; PerúFil: Neris, Nora. Universidad Nacional de Asunción; ParaguayFil: Saldivar Bellassai, Silvia. Itaipu Binacional; ParaguayFil: Wallace, Robert. Wildlife Conservation Society. New York; Estados UnidosFil: Lizarraga, Leónidas. Delegación Regional Noroeste. Sistema de Información de Biodiversidad de la Administración de Parques Nacionales. Salta; ArgentinaFil: Thompson, Jeffrey. Universidad Nacional de Asunción; ParaguayFil: Velilla, Mariela. Universidad Nacional de Asunción; Paragua

Bird sensitivity to disturbance as an indicator of forest patchconditions: An issue in environmental assessments

An Environmental Assessment (EA) is one of the steps within the Environmental Impact Assessment process. Birds are often used in EA to help decision makers evaluate potential human impacts from proposed development activities. A “sensitivity to human disturbance” index, created by Parker III et al. (1996) for all Neotropical species, is commonly considered an ecological indicator. However, this parameter was created subjectively and, for most species, there have been no rigorous field test to validate its effectiveness as such. Therefore, in this study, we aim to: (1) evaluate if, at the local scale, birds from forest patches in a human-modified landscape (HML) may differ in sensitivity from Parker's sensitivity classification; (2) evaluate the effectiveness of the species richness value at each sensitivity level as an ecological indicator; (3) gather information on how often and in which manner Parker's classification has been used in EA. To do so, bird sampling was performed in eight forest patches in a HML over one year. Then, we created a local sensitivity to disturbance using information about threat, endemism, spatial distribution and relative abundance of all species in the study area. We found that 37% of the forest birds showed different local sensitivity levels when compared with Parker's classification. Our results show that only the richness of high-sensitivity species from our local classification fitted the ecological indicator assumptions helping the environmental conditions evaluation of the studied patches. We conclude that species richness of each Parker's bird sensitivity levels do not necessarily perform as an ecological indicator at the local scale, and particularly in HML. Nevertheless, Parker's Neotropical bird sensitivity classification was used in 50% of EA we reviewed. In these, 76% assumed that it was an accurate ecological indicator of the local forest conditions for birds. The lack of clear criteria used in Parker's classification allows diverse interpretations by ornithologists, and there is no agreement about the ecological meaning of each sensitivity level and what environmental conditions each level may indicate of. Therefore, the use of Parker's classification in EA may jeopardize accurate interpretations of proposed anthropogenic impacts. Furthermore, because a bird species’ sensitivity often varies between locations, we argue that Parker's generalized classification of bird sensitivity should not be used as an indicator of forest environmental conditions in EA throughout HMLs in Neotropics. Rather, local bird ecological indices should be explored, otherwise, erroneous predictions of the anthropogenic impacts will continue to be common

Social media data from two iconic Neotropical big cats: can this translate to action?

IntroductionThere has been a gradual increase in studies of social media data usage in biodiversity conservation. Social media data is an underused source of information with the potential to maximize the outcomes of established conservation measures. In this study, we assessed how structured social media data can provide insight into species conservation through a species conservation plan, based on predefined actions. MethodsWe established a framework centered on a set of steps that go from defining social media platforms and species of interest to applying general analysis of data based on data dimensions—three W’s framework (What, When, Who) and the public engagement that posts received. The final and most important step in our proposed framework is to assess the overlap between social media data outcomes and measures established in conservation plans. In our study, we used the Brazilian National Action Plan (BNAP) for big cats as our model. We extracted posts and metrics about jaguars (Panthera onca) and pumas (Puma concolor) from two social media platforms, Facebook and Twitter. ResultsWe obtained 159 posts for both jaguars and pumas on Facebook (manually) and 23,869 posts for the jaguar and 14,675 posts for the puma on Twitter (through an application user interface). Data were categorized for content and users (only Facebook data) based on analysis of the content obtained and similarities found between posts. We used descriptive statistics for analyzing the metrics extracted for each data dimension (what, when, who, and engagement). We also used algorithms to predict categories in the Twitter database. Our most important findings were based on the development of a matrix summarizing the overlapping actions and dimensions of the data. Our findings revealed that the most prominent category of information for jaguars on Facebook was the sighting of wildlife outside protected areas, while for pumas, it was the trespassing of property by wildlife. From the Twitter dataset, we observed that the most prominent category of information for jaguars was: the sighting of wildlife outside protected areas, while for pumas, it was wildlife depredation by direct or indirect means. We found temporal trends that highlight the importance of categories in understanding information peaks on Facebook and Twitter. DiscussionWhen we analyze online engagement, we see a predominance of positive reactions on Facebook, and on Twitter, we see a balanced reaction between positive and negative. We identified 10 of 41 actions in the BNAP that might benefit from social media data. Most of the actions that could benefit from our dataset were linked to human–wildlife conflicts and threats, such as wildlife–vehicle collisions. Communication and educational actions could benefit from all dimensions of the data. Our results highlight the variety of information on social media to inform conservation programs and their application to conservation actions. We believe that studies on the success of applying data to conservation measures are the next step in this process and could benefit from input from decision-makers

Wild dogs at stake: deforestation threatens the only Amazon endemic canid, the short-eared dog (Atelocynus microtis)

The persistent high deforestation rate and fragmentation of the Amazon forests are the main threats to their biodiversity. To anticipate and mitigate these threats, it is important to understand and predict how species respond to the rapidly changing landscape. The short-eared dog Atelocynus microtis is the only Amazon-endemic canid and one of the most understudied wild dogs worldwide. We investigated short-eared dog habitat associations on two spatial scales. First, we used the largest record database ever compiled for short-eared dogs in combination with species distribution models to map species habitat suitability, estimate its distribution range and predict shifts in species distribution in response to predicted deforestation across the entire Amazon (regional scale). Second, we used systematic camera trap surveys and occupancy models to investigate how forest cover and forest fragmentation affect the space use of this species in the Southern Brazilian Amazon (local scale). Species distribution models suggested that the short-eared dog potentially occurs over an extensive and continuous area, through most of the Amazon region south of the Amazon River. However, approximately 30% of the short-eared dog's current distribution is expected to be lost or suffer sharp declines in habitat suitability by 2027 (within three generations) due to forest loss. This proportion might reach 40% of the species distribution in unprotected areas and exceed 60% in some interfluves (i.e. portions of land separated by large rivers) of the Amazon basin. Our local-scale analysis indicated that the presence of forest positively affected short-eared dog space use, while the density of forest edges had a negative effect. Beyond shedding light on the ecology of the short-eared dog and refining its distribution range, our results stress that forest loss poses a serious threat to the conservation of the species in a short time frame. Hence, we propose a re-assessment of the short-eared dog's current IUCN Red List status (Near Threatened) based on findings presented here. Our study exemplifies how data can be integrated across sources and modelling procedures to improve our knowledge of relatively understudied species

Capybara spatial distribution (Hydrochoerus hydrochaeris) in relation to the landscape of Piracicaba river basin, SP

A bacia do rio Piracicaba, como toda a região sudeste do Brasil, tem sofrido alterações drásticas da paisagem original que certamente influenciam a distribuição e abundância das espécies animais. Aparentemente, a capivara é uma das espécies que tem sido afetada por este processo, uma vez que grandes agregações populacionais podem ser observadas em ambientes completamente alterados, possivelmente em função da maior oferta de áreas abertas e alimento e do desaparecimento de predadores naturais. O objetivo deste estudo foi o de obter um modelo preditivo da distribuição espacial da capivara em função da paisagem, na bacia do rio Piracicaba, Estado de São Paulo. As etapas deste estudo compreenderam: 1) modelagem da distribuição: Modelo SPIP (Modelo de Sobreposição dos Planos de Informação Ponderados pelo Usuário) e Modelo GARP (Algoritmo Genético para Regras de Predição), ambos elaborados com o auxílio do Sistema de Informações Geográficas (SIG); 2) levantamento aéreo: caracterização do ambiente físico e localização de sítios de coleta potenciais à ocorrência da espécie através da videografia aérea; e, 3) levantamento terrestre: estimativa da distribuição da capivara através do uso do índice presença/ausência de indivíduos e/ou vestígios nos sítios de coleta. 89 pontos de presença e 66 pontos de ausência foram usados para calibrar e validar os modelos. As variáveis utilizadas para gerar os modelos foram: imagem de satélite não classificada, imagem de satélite classificada pelo processo não supervisionado, uso da terra, modelo digital, aspecto, declividade, curvatura e distância da rede de drenagem. A freqüência relativa de presença de capivaras foi de 57,42%, sendo que os animais puderam ser observados em apenas 8,38% dos sítios visitados. As capivaras estavam associadas preferencialmente aos habitats agrícolas, em terrenos de baixa declividade, localizados nas proximidades de cursos d'água e com forte presença humana. O modelo SPIP obteve 100% de acerto sendo 79,77% em áreas previstas com alta probabilidade. A área prevista para a ocorrência da capivara compreende 99% da área total, sendo que 79,96% da área apresentou probabilidade média-alta de ocorrência com 67,53% em áreas agrícolas. As variáveis preditoras indicadas pelo modelo GARP para explicar a distribuição espacial da capivara na bacia foram imagem de satélite não classificada, modelo digital de elevação, curvatura, uso do solo e tipos de solos. 44,04% da área da bacia apresentou probabilidade média-alta de ocorrência de capivaras, sendo que 23,93% da área com alta probabilidade de ocorrência estava localizada em áreas com cana-de-açúcar e 12,25% com pastagens. Estimativas de presença foram altamente significativas (p < 0,001), entretanto, as predições de ausência foram pouco acuradas. A inclusão dos pontos de presença da espécie na calibração do modelo GARP melhorou seu desempenho, explicando a baixa taxa de erro do tipo II e, conseqüentemente, a alta taxa de acerto em termos de presença (97%). O índice presença/ausência foi eficiente na elaboração do modelo preditivo de distribuição espacial da capivara. O GARP foi o modelo mais eficiente na predição da distribuição espacial da capivara. No entanto, este modelo deverá ser validado para outras áreas com diferentes atributos da paisagem e/ou onde a espécie é menos abundante ou apresenta uma distribuição menos ampla. Modelos preditivos de distribuição de espécies devem servir como base no processo de tomada de decisões em ações de manejo.The Piracicaba river basin, like the whole southeastern Brazil, has been suffered landscape alterations that certainly influence distribution and abundance of vertebrates. Apparently, the capybara is one of the species that has been influenced by this process, since large groups can be observed in anthropogenic habitats, possibly due to the great availability of food, open areas, and the local extinction of large predators. The main goal of this study was to develop a predictive model of capybara spatial distribution in relation to the landscape of Piracicaba river basin in the Sao Paulo, Brazil. The present study had three steps: 1) Distribution modeling: SPIP model (weighted-Iayers overlay) and GARP model (genetic algorithm for rule-set prediction), both assessed by Geographic Information System (GIS); 2) Aerial videography: Characterization of physical environment and study sites location assumed as adequate to the species; and, 3) Terrestrial surveys: capybara distribution estimated by presence/absence Index of individuais and/or tracks in the study sites. 89 presence points and 66 absence points were used to calibrate and validate the models. The unclassified Landsat TM image, classified Landsat TM image, land uselland cover, digital elevation model, aspect, slope, curvature of terrain and water distance gradient were the environmental variables used to generate the models. The relative frequency of capybara presence was 57.42%, and the animais were observed at only 8.38% of the sites. Capybaras were associated mainly to the agricultural habitats, with lower slopes, nearby the stream network, and with strong human presence. 100% of presence was accurately predicted by the SPIP model, with 79.77% in areas with higher probability of occurrence. The area predicted by the SPIP model represented the 99% of the total basin area. The 79.96% of the predicted area had medium-high probability of occurrence with 67.53% in the agricultural areas. The predictive variables indicated by the GARP model to explain the capybaras spatial distribution were the unclassified Landsat TM image, digital elevation model, curvature of terrain, land uselland cover, and soil type. 44.04% of the total area had medium-high probability of capybaras occurrence, but 23.93% of the higher probability was sugar cane and 12.25% was pasture. Predictions of presence were highly significant (p < 0.001); however, predictions of absence were only marginally accurate. The inclusion of presence points in the GARP model calibration improved its performance, explaining the low type II error probability, and, consequently, the high accuracy (97%). The presence/absence Index was efficient for the modeling processo GARP was the most accurate model. However, it should be validated for other areas with different landscape attributes where the species is not as abundant or widespread. Predictive models of wildlife spatial distribution can be helpful for the decision-making process in management actions