A GIS model for identifying eastern spadefoot toad (Scaphiopus holbrookii) habitat in eastern Connecticut

Assortative mixing in eastern spadefoot (Scaphiopus holbrookii) spatial networks is driven by landscape features

“…We note that none of the soil or habitat descriptors had any predictive power of an eastern spadefoot's stage or size, even though burrow site for this species is strongly dependent on soil characteristics (Moran & Button, 2011). Combined with our results, we suggest that soil and habitat characteristics predict occupancy (presence/absence) but not assortative mixing.…”

“…For the rest of the year on nonbreeding nights, adults emerge regularly from their burrows to forage in forests (Devan‐Song et al, 2021), traveling short distances between several burrows (Pearson, 1957; Timm et al, 2014). Although soil types determine where spadefoots are able to dig burrows (Baughman & Todd, 2007; Moran & Button, 2011), their life history is tightly linked to the extreme unpredictability and ephemerality of breeding pools. The forests and wetlands used by S. holbrookii provide a useful study system for understanding how habitat features shape assortative mixing in amphibians, especially highly terrestrial species.…”

Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs

“…They are important data sets for geomorphological research because surficial features can be visualized, processes operating on landforms modeled, and rates of surface change predicted (Cavalli et al, 2008;Frankl et al, 2010). They are also frequently used in hydrological modeling to delineate watersheds, natural streams, and sinks (Hopkinson et al, 2009;Murphy et al, 2008) and have also been used extensively for land use planning and site selection and suitability analyses, including the prediction of fish densities using stream channel gradients (Wissmar et al, 2010) and for the identification of critical habitat for endangered species according to prescribed surface characteristics (Moran & Button, 2011). In addition, they are often used to perform line of sight and viewshed analyses to determine optimum locations for structures and facilities such as communication towers and wind turbines (Akella et al, 2010;Möller, 2006) and are frequently used for erosion modeling, calculating the loss of glacial ice, or performing cut-and-fill analyses to determine the volume of earth, rock, or water located within a defined area of interest (Chen et al, 2006;Keutterling & Thomas, 2006;Thoma et al, 2005).…”

Μοντέλα Πρόβλεψης Της Χωρικής Κατανομής Της Βιοποικιλότητας Σε Δασικό Περιβάλλον, Για Το Σχεδιασμό Πρακτικών Διατήρησης Και Προστασίας Με Τη Βοήθεια Εξειδικευμένων Γεωγραφικών Συστημάτων Πληροφοριών

“…Στη βιβλιογραφία συναντάμε πολυάριθμες εφαρμογές των ΓΣΠ στην οικολογική έρευνα, οι οποίες συνοπτικά επικεντρώνονται στον προσδιορισμό των σχέσεων των παραγόντων του περιβάλλοντος και της κατανομής των ειδών, ενώ προβλέπουν τη χρήση του χώρου από τα είδη και την καταλληλότητα των ενδιαιτημάτων ως προς αυτά (Ποϊραζίδης, 2003), (Engler, Guisan, & Rechsteiner, 2004;Guisan & Thuiller, 2005;Guisan & Zimmermann, 2000;Hirzel & Le Lay, 2008;Lenton, Fa, Perez, & Val, 2000;Store, 2003;Moran & Button, 2011;Zohmann, Pennerstorfer, & Nopp-Mayr, 2013). Παράλληλα, πολλοί ερευνητές αξιοποίησαν τις αναλυτικές δυνατότητες των ΓΣΠ για να προβλέψουν την κατανομή των ειδών και των κινδύνων που αυτά αντιμετωπίζουν (Boyd & Foody, 2011), με την εφαρμογή σεναρίων (Pennington, 2007;Shinneman, Cornett, & Palik, 2010) αλλά και τη χαρτογράφηση απειλών όπως την απώλεια ενδιαιτημάτων (Vogiatzakis et al, 2006), την αλλαγή χρήσεων γης, την απώλεια συνεκτικότητας του τοπίου ή ακόμη και την επίδραση της κλιματικής αλλαγής (Akçakaya, Butchart, Watson, & Pearson, 2014;Schivo, Bauni, Krug, & Quintana, 2019;Subba, Sen, Ravikanth, & Nobis, 2018).…”