Abstract Climate change (CC) and human footprint (HF) shape species spatial patterns and may affect the effectiveness of Protected Areas (PAs) network. Spatial patterns of threatened bird species of Subtropical–temperate hotspots in Southeastern South American grasslands are relevant biodiversity features to guide conservation policies. However, the PAs network covers less than 1% of grassland areas and does not overlap areas with the most suitable environmental conditions for threatened birds. Our aim was to find the most environmentally suitable areas for both current and future threatened birds (2050 and 2070) in Entre Ríos. We applied Systematic Conservation Planning protocols with Ecological Niche Models (ENMs) and ZONATION using distribution interaction function and HF as a cost. Then we overlapped binary maps to find priority areas among time periods. HF showed a more fragmented spatial configuration. The PAs network may include environmentally suitable conditions for threatened birds in CC scenarios and HF. We found areas that showed more connectivity in landscape prioritization over time and ensure high-quality environmental conditions for birds. We concluded that the effectiveness of the PAs network could be improved by overlapping priority areas. Our approach provides a knowledge base as a contribution to conservation-related decisions by considering HF and CC.

Abstract The Neotropical region is characterized by the high species richness of birds, whose protection and inventories show biases due to lack of geographic representation and species diversity. In Entre Ríos province its protected areas have not been well established, generating biases in biodiversity representativeness. We updated the birds’ inventory of Entre Ríos with 80,000 records. The province was divided into 39 cells of 0.5° lat-long to analyze birds’ richness and priority areas through a complementary analysis. The Protected Areas (PAs) system was overlapped with the complementary areas to detect gap conservation areas. Entre Ríos presents 396 bird species and needs 10 cells to protect them all. The priority areas included cells on the Paraná and Uruguay rivers. These priority areas overlap poorly with the current PAs system. We recommend the creation of new PAs or change the protection categories of PAs that overlap with priority areas selected. This work revaluates the importance of updated inventories to perform spatial prioritization and contrast the current PAs system to generate representative and efficient systems.

Resumen La región neotropical se caracteriza por su gran riqueza de aves, cuya protección e inventarios presentan sesgos de representación geográfica y composición de especies. En la provincia de Entre Ríos, las áreas protegidas han sido establecidas con escasa planificación, lo que generó profundos sesgos en la representatividad de la biodiversidad provincial. Se actualizó el inventario de las aves de Entre Ríos con 80,000 registros. Se dividió la provincia en 39 celdas de 0.5° lat-long para analizar la riqueza de aves y priorizarlas mediante un análisis de complementariedad. Se comparó el sistema de áreas protegidas (AP) con las áreas complementarias para detectar vacíos de conservación. Entre Ríos posee 396 especies requiriendo 10 celdas para incluirlas a todas. Las áreas prioritarias mayormente incluyeron celdas sobre los ríos Paraná y Uruguay. Estas áreas prioritarias se superponen deficientemente con las AP existentes. Se recomienda la creación de nuevas AP o cambiar las categorías de protección de AP ubicadas en las áreas prioritarias. El presente trabajo revaloriza la importancia de contar con inventarios actualizados para poder realizar priorizaciones espaciales y contrastar el sistema actual de AP para generar sistemas representativos y eficientes.

The Exotic plant species invasion in the Argentine Espinal region causes a change in the appearance of the landscape, altering the environment and producing a significant loss of biodiversity. We studied the composition of ground spiders in Parque General San Martín, Entre Ríos, during the summer and winter seasons of 2012. Three areas were selected: pajonal (P), native forest (BN) and exotic forest (BE), pitfalls were used for sampling. A total of 1398 spiders (26 families and 120 species/morphospecies) were collected. The most abundant families in the different areas were Lycosidae (n=574; 41.06%), Tetragnathiidae (n=223; 15.95%) and Linyphiidae (n=137; 9.80%). The guild category "ground hunters" (n=632) "sheet web weavers" (n=262) and "orb webs weavers" (n=244) were highly represented in all sampling areas. Diversity indices showed that BN was more diverse than P and BE. Complementarity values obtained between P and BE and BN were higher than 71%, while BE and BN showed values of 63%. This study constitutes the first record of the spider´s community of Parque General San Martín.

La invasión de especies leñosas exóticas en la región argentina del Espinal provoca un cambio en la fisonomía del paisaje ya que altera el ambiente y produce la pérdida de biodiversidad. Se estudió la composición de arañas asociada al suelo del Parque General San Martín, Entre Ríos, durante el verano e invierno de 2012. Se seleccionaron tres ambientes: pajonal (P), bosque nativo (BN) y bosque exótico (BE), y se utilizaron trampas de caídas para el muestreo. Se recolectaron en total 1398 arañas (26 familias y 120 especies/morfoespecies). Las familias más abundantes en los tres ambientes fueron Lycosidae (n=574; 41.06%), Tetragnathiidae (n=223; 15.95%) y Linyphiidae (n=137; 9.80%), respectivamente. Los gremios que presentaron la mayor abundancia fueron "cazadoras corredoras sobre suelo" (n=632), "tejedoras de telas en sábanas" (n=262) y "tejedoras de telas orbiculares" (n=244), representados en todos los ambientes estudiados. Los perfiles de diversidad indicaron que el BN fue más diverso que el P y el BE. Los valores de complementariedad mostraron una diferencia de 71% entre P-BE y P-BN, y de 63% entre BE-BN. Este trabajo constituye el primer registro sobre la comunidad de arañas de suelo del Parque General San Martín.