Anthropogenic and climate change-driven coastline dynamics will erode future nesting habitats of the kentish plover on the central adriatic coast

Abstract

Shorebirds play a crucial role in assessing the health of coastal ecosystems due to their life history, behaviour, migratory patterns, and feeding preferences. Many shorebird species are experiencing population declines worldwide, driven by habitat loss and climate change. Understanding these challenges requires extensive data on their distribution and breeding ecology. The Kentish Plover (Anarhynchus alexandrinus) is a small shorebird that constructs its nests on sandy beaches. However, there is a scarcity of data regarding the reproductive ecology of this species in many areas, including the Molise region of Southern Italy. This study aimed at assessing the potential role of environmental variables derived from remote sensing to model current and future Kentish Plover nesting habitat suitability accounting for future scenarios of coastal dynamics in 2040. Data on Kentish Plover nests were collected along the Molise coast over several years and used to calibrate ecological niche models (ENMs) relying on environmental variables derived from coastal images. Kentish Plover nesting habitat suitability was mostly affected by distance from open sand, artificial surfaces, shoreline, and herbaceous vegetation and forested areas. The study predicts an average decline of more than 22% in suitable nesting environments for the Kentish Plover within the next two decades. Results indicated that our modelling approach can offer valuable insights for the conservation strategy of Kentish Plover in the region. In conclusion, we assert that preserving the nesting habitat of the Kentish Plover will not only safeguard this species, but also other species that inhabit similar environments, along with providing protection for coastal landscapes and associated ecosystem services.

Fig. 1

Flow chart showing the methodological framework used in this research. Maps Data: Google, ©2024 Airbus.

Fig. 2

Adult male (a) and adult female (b) of Kentish Plover; typical Kentish Plover nest with three eggs (c). Pictures by Rosario Balestrieri.

Fig. 3

Zoomed section of the study area over the extent of the projection area. The main map depicts an example of the sampling transects surveyed to detect Kentish Plover’s nests, superimposed to the land cover categories used in the modelling phase (labels reported in the legend with an asterisk refer to land cover categories occurring in the study area but not within the extent of the zoomed section). Due to scale limitations, we represented parallel transects as single orange belts (a zoomed detail of the parallel transects is provided in the circular inset). The inset in the upper right corner shows the spatial reference of the study area (i.e., the red line), along with the location of the detail reported in the main map (i.e., the yellow dot). The numbered polygons in green refer to the three Natura 2000 sites insisting over the study area (i.e., 1: Foce Trigno – Marina di Petacciato [IT7228221]; 2: Foce Biferno – Litorale di Campomarino [IT7222216]; 3: Foce Saccione – Bonifica Ramitelli [IT7222217]). Maps Data: Google, ©2024 Airbus.

Fig. 4

Barplot in the upper left corner depicts the percentage of relative importance of the environmental variables. All variables are Euclidean distances except Shannon Index. Curves in partial dependence plots report the relation between Kentish Plover nesting habitat and environmental variables. The horizontal axes of all the panels but Shannon index indicate Euclidean distances and are expressed in meters.

Fig. 5

Model projection (EPSG:32633) showing the predicted range modifications under 2040 based on the coastline shift along a stretch of Molise coast. The presented binary map was created considering the ‘maximize TSS” binarization threshold. Maps Data: Google, ©2024 Airbus.

Fig. 6

Mean percentage of the projection area covered by each type of landscape and Kentish Plover nesting habitat modification generated by overlaying current and future ENM projections according to the coastline changes predicted for 2040. Bar height refers to the mean percentage cover values calculated from the three binary maps (i.e., ‘equalize sensitivity and specificity’, ‘maximize TSS’ and ‘10th percentile’), while error whiskers indicate standard deviation values.