Elevation map of Morocco showing (a) the main geographical features and cities treated in the text, and (b) the Moroccan CAN composed of present and future (SIBES) National Parks and different SIBES priority levels  

Elevation map of Morocco showing (a) the main geographical features and cities treated in the text, and (b) the Moroccan CAN composed of present and future (SIBES) National Parks and different SIBES priority levels  

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The integration of spatial area prioritization algorithms and species distribution modelling has shown great promise in conservation planning in recent years. However, despite the fact that reptiles and amphibians have the highest threat status of all terrestrial vertebrates, these species are often under-represented in conservation planning. The K...

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... More heterogenous environments are presumed to support a greater number of species and, consequently, increased species diversity [18][19][20][21]. Identifying environmental characteristics that structure amphibian assemblages and determining suitable habitats are a prerequisite for understanding the ecological underpinnings of amphibians' lifestyle, and for proposing pertinent conservation plans [1,[22][23][24][25][26][27]. ...
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Simple Summary Amphibian biodiversity is declining around the globe and habitat destruction and fragmentation impact two-thirds of all amphibians. The distinct characteristics of amphibians, such as low mobility and permeable skin, make them more susceptible to environmental influences than other taxa. We have shown that within the small area of the Kirindy Forest in Madagascar, environmental differences influenced the selection of breeding sites by frogs to such an extent that the composition of the anuran larvae assemblage differed vastly between individual ponds. The diversity of breeding sites increases species richness by serving the needs of multiple species. Characteristics such as pond size, vegetation, and time until desiccation of ponds should be considered when designing conservation action plans to protect a wide variety of species. If breeding sites become unavailable because of a shift in environmental gradients, not only amphibian diversity but the whole ecosystem could be harmed. Abstract Environmental filtering shapes animal communities by preventing the colonization and persistence of certain species in a given habitat. More heterogenous environments are presumed to support a greater number of species and, consequently, increased species diversity, as environmental filters are also likely more heterogenous. Amphibians are especially sensitive to environmental influences due to distinct characteristics like permeable skin and low mobility. By analyzing the species richness and assemblage composition of tadpoles in 132 breeding ponds, we examined how the interplay of environmental variables shapes anuran species assemblages in breeding habitats of the dry forest of Western Madagascar. We found that environmental filtering is prevalent and habitat heterogeneity not only increases larval species richness but also alters species composition between these assemblages. Our study highlights the need for conserving heterogenous habitats to maintain local diversity. Furthermore, we recommend including multivariate modelling approaches to conservation efforts to acknowledge differences between specific habitats and beta diversity.
... Generally, there was a large agreement between the richness patterns obtained from SDM using both approaches (MaxEnt and Random Forest), as also shown in a previous study (Megna et al., 2021). MaxEnt and Random Forest models have been shown to attain high prediction accuracy with few occurrence records and small sample sizes in comparison to other algorithms (Wisz et al., 2008;Costa et al., 2010;de Pous et al., 2010). Despite the potential of SDMs, there is criticism about their accuracy in predicting actual species distributions since biotic interactions, genetic variability and species dispersal abilities are not taken into account, and these factors limit species survival in a priory suitable climatic environments (Dawson et al., 2011;Garzón et al., 2011;Kissling et al., 2012). ...
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Freshwater biodiversity loss is of concern in the Mediterranean Basin, as one of the global hotspots of biodiversity. Despite a number of faunistic and taxonomic studies that have been conducted in the last years in the African part of the Mediterranean Basin, our knowledge on freshwater biodiversity patterns in this area is still very limited. In this study, we aim to i) identify the areas with the highest potential species richness of water beetles, estimated from species distribution models using two different approaches (MaxEnt and Random Forest) and ii) conduct a gap analysis to assess the effectiveness of protected areas in the conservation of these areas. Results showed that the highest potential species richness of water beetles in Morocco occurs in the mountain areas of the Rif and Prerif, Middle Atlas and northern Central Plateau of Morocco. Among the identified priority areas (those in the top 5% of potential richness values), 21.6% are totally unprotected and ca. 65% are poorly protected (i.e., protected area extent < 25%). These results call for urgent and direct policies to protect North African freshwater biodiversity.
... Therefore, understanding the geographical distribution of herpetofauna species is essential for their conservation, and various modeling techniques have been applied and evaluated to determine their distribution characteristics [4,18,19] . These studies have mainly focused on establishing strategies for species conservation and protection by predicting habitat changes as a consequence of climate change or identifying hotspot or core areas [2,4,6,20] . ...
... In South Korea, recent studies have indicated the need for using habitat prediction models for the establishment of protected areas for wild animals and plants [5,33,70,71] . Habitat prediction model studies can be used to provide objective and scienti c methods and procedures for the establishment of protected areas [4,6,20] . Previous studies carried out with the aim of establishing habitat conservation areas for herpetofauna species in other regions have used habitat prediction models, for example to establish protected areas for 16 endangered species belonging to the family Hylidae in South America, and to determine which areas are in need of conservation for the protection of seven species belonging to the family Viperidae inhabiting northeast Africa [4,72] . ...
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Understanding the geographic distribution of species is crucial for establishing protected areas. This study aimed to identify the preferred habitat environment of South Korean herpetofauna using distribution point information, providing the information necessary to protect their habitat by establishing a species distribution model. We found that climate variables in the region where 19 amphibians and 20 reptiles were distributed showed a correlation with altitude, suggesting altitude had a major influence on their distribution. The species distribution modeling indicated that 10–12 amphibian species and 13–16 reptile species inhabit the Gangwon-do region, forming hotspot areas in the eastern and western regions around the Taebaek Mountains. Some of these hotspot areas occurred in the Demilitarized Zone (DMZ) and national parks, which are government managed ecological conservation areas. However, some hotspot areas are vulnerable to habitat destruction due to development and deforestation as they are not designated conservation areas. Therefore, it is necessary to establish new conservation areas with a focus on herpetofauna, after confirming the actual inhabitation of species through precise monitoring in predicted hotspot areas, and designate them as protected areas. These results can serve as important basic data for establishing protection measures and designating protected areas for herpetofauna species.
... One common current practice is first to model the distributions of each individual species within some taxon of interest (Early et al. 2008, de Pous et al. 2011, Villero et al. 2017. Typically, these are modelled independently (but see Pollock et al. 2014, Rougier et al. 2015. ...
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... Information layers, including presence points and environmental variables, were prepared and entered into MaxEnt. Finally the habitat suitability layers have been overlapped in order to determine the species richness hotspots in GNP and by comparing these hotspots and current zoning of the park the conservation gaps can be detected (areas with the highest number of suitability resulting from the accumulation of overlapping considered as hotspots) (Rodrigues et al. 2004, Catulloa et al. 2008, Brito et al. 2009, Wilting et al. 2010, Pous et al. 2011, Kalle et al. 2013, Almasieh et al. 2016, Naderi et al. 2018. ...
... In the future, and in the absence of conflicts, these patches should be added to current conservation zones. Pous et al. (2011) used MaxEnt to prioritize and assess the efficiency of Morocco's network of protected areas to support and conserve reptiles and amphibians. After preparing species richness maps for reptiles and amphibians in Morocco and distribution patterns for each species, they concluded that a significant expansion of protected areas is needed to meet the global goal of at least 10percent representation in order to guarantee the sustainability and survival of each individual reptilian and amphibian species. ...
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... These reserves, however, span over huge areas, encompassing within their boundaries of not only conservation areas but also vast agricultural lands and even densely populated urban centres (such as the city Agadir within the Arganeraie Biosphere reserve). Previous studies evaluating the effectiveness of the current protected areas of Morocco have already suggested low coverage of the country's amphibians and reptiles, despite the high conservation value of these groups (Pleguezuelos et al., 2010;Carvalho et al., 2011;de Pous et al., 2011). Such studies on the Algerian and Tunisian protected areas are lacking. ...
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... Thus, our dataset could serve as an important basis for conservation interventions in Albania and this knowledge can also be applied to other countries or regions (Ribeiro et al., 2016). Further, it might also be feasible to create gap-analysis with existing protected areas either with or without the involvement of species distribution modelling (Carvalho et al., 2010;de Pous et al., 2011;de Novaes e Silva et al., 2014). The database could be also integrated into larger areas such as the European continent and thus will fill an important gap for macroecological studies (Sillero et al., 2014a(Sillero et al., , 2014bEstrada et al., 2015). ...
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Although Albania has a rich reptile fauna, efforts to reveal its diversity have so far been limited. To fill this gap, we collected available published and unpublished (museum collections, online sources) records of reptile occurrences and conducted several expeditions to search for reptiles in areas with few or no previous records. Our georeferenced database contains 3731 records of 40 species from between 1918 and 2015. Based on this comprehensive dataset, we prepared distribution maps for each reptile species of the country. Applying spatial statistics, we revealed that overall sampling effort was clustered, with hotspots associated with easily accessible areas and natural heritage sites. The maximum number of species per cell was 26 with an average of seven. Cells harbouring large reptile diversity were located along the Adriatic and Ionian coasts, on the western slopes of south Albanian mountains, i.e. in areas generally considered as Balkans biodiversity hotspots or potential historical refugia. We found that species presence and diversity is strongly influenced by landscape features. Diversity of land cover, altitudinal variation, temperature and precipitation variation explained the observed pattern in our models. Our study presents the largest database of reptile occurrences to date and is the first to analyse reptile diversity patterns in Albania. The database and the diversity patterns can provide a basis for future macroecological studies and conservation planning.
... From the initial list of birds, 15 species were removed, as the predictions of their distributions were not robust (Fig. 2; AUC <0.75; Pearce and Ferrier, 2000, Elith, 2002, Pous et al., 2011). These species were Common Swift, Alpine Swift, Tawny Pipit, Tree Pipit, Eurasian Golden Oriole, Winchat, House Martin, Lesser Spotted Woodpecker, Alpine Chough, Eurasian Magpie, Eurasian Reed Warbler, Ortolan Bunting, Olivaceous Warbler, Eurasian Hobby, and Spotted Flycatcher. ...
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Understanding distributions of wildlife species is a key step towards identifying biodiversity hotspots and designing effective conservation strategies. In this paper, the spatial pattern of diversity of birds in Golestan Province, Iran, was estimated. Ecological niche modeling was used to determine distributions of 144 bird species across the province using a maximum entropy algorithm. Richness maps across all birds, and separately for rare and threatened species, were prepared as approximations to hotspots. Results showed close similarity between hotspots for all birds and those for rare birds; hotspots were concentrated in the southern and especially the southwestern parts of the province. Hotspots for threatened birds tended more to the central and especially the western parts of the province, which include coastal habitats. Based on three criteria, it is clear that the western part is the most important area of the province in terms of bird faunas. Despite some shortcomings, hotspot analysis could be applied to guide conservation efforts and provide useful tool towards efficient conservation action.
... between both validation methods, then we can assume good model performance (Beauregard and de Blois, 2014). In our data there was no significant correlation between the mean AUC values and the number of records, and hence we believe that sample size did not affect model performance (Elith et al., 2006;de Pous et al., 2011). Some other studies have achieved good model performance with large sample sizes (Kadmon et al., 2003;Hernandez et al., 2006), as we did. ...
... Such analyses can include elements of both lower suitability and uncertainty in model predictions, depicted as lighter shades of red in Figure 1 (model uncertainty can be illustrated explicitly as well, see, e.g., Peterson et al. 2013), and applications for real-world use would include considerable experimentation with parameter settings (Warren & Seifert 2011), beyond default settings. Such data-driven approaches have seen massive-scale application to many questions in conservation biology, biogeography, and macroecology (e.g., Costa et al. 2010;de Pous et al. 2011;Moreno et al. 2011). ...
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Species' geographic distributions are mapped using various approaches for use in conservation decision-making. Some such mapping efforts have relied on modifications of coarse-resolution extent-of-occurrence maps to downscale them to fine resolutions for conservation planning. This contribution examines (1) the quality of the extent-of-occurrence maps as range summaries, and (2) the utility of refining those maps into fine-resolution distributional hypotheses. In both cases, we found significant problems: the extent-of-occurrence maps are overly simple, omit many known and well-documented populations, and likely frequently include many areas not holding populations. Refinement steps involve typological assumptions about habitat preferences and elevational ranges of species, which can introduce significant error in anticipating species' true distributional areas; however, as no model evaluation steps are taken to assess predictive ability of models, "bad" models are not noticed. Whereas range summaries derived by these methods may be useful in coarse-grained, global-extent studies, their continued use in on-the-ground conservation challenges at fine resolutions is not advisable. On the other hand, data-driven techniques that integrate primary biodiversity occurrence data with remotely sensed data summarizing environmental dimensions, termed ecological niche modeling or species distribution modeling, with rigorous and quantitative testing of model predictions prior to any use. These data-driven approaches constitute a well-founded, widely accepted alternative with a minimum of assumptions. This article is protected by copyright. All rights reserved.