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. 2025 Aug;39(4):e70067.
doi: 10.1111/cobi.70067. Epub 2025 May 21.

Habitat dynamics of flagship species for conservation prioritization in southern Europe

Antonio Velasco-Rodríguez  1 , Adrián Regos  2   3 , Isabel Castillejo González  4 , Neftalí Sillero  5 , Salvador Arenas-Castro  1
Affiliations

Habitat dynamics of flagship species for conservation prioritization in southern Europe

Antonio Velasco-Rodríguez et al. Conserv Biol. 2025 Aug.

Abstract
in English, Spanish

Biodiversity loss is accelerating due to human actions, and decision-making for conservation needs to be streamlined. Ex situ biodiversity modeling and monitoring based on satellite time-series data could be an affordable and cost-efficient tool for improving the prioritization of conservation areas. We developed a set of dynamic indicators for conservation prioritization based on a habitat suitability index (HSI) trend analysis of 6 flagship species (two vascular plants, bird, amphibian, reptile, and mammal) over 19 years (2001-2019) in Andalucía (southern Spain). The HSI models were derived from ecological niche models (MaxEnt) and satellite time-series data (MODIS) as predictors. Based on the annual HSI models of all species and using the spatial conservation prioritization tool Marxan, we derived interannual dynamic indicators of habitat quality for conservation prioritization. Overall, models showed a generalized habitat regression. The best predictors of habitat quality were related to vegetation composition and structure (land cover), climate (land surface temperature), and energy balance (evapotranspiration), matching with the ecology of climate (such as Abies pinsapo) or vegetation-dependent (such as Alytes dickhilleni) species. Marxan identified interannual dynamics for the priority areas outside and inside protected areas. Interannual variation in habitat quality led to shifting conservation priorities across Andalucia from 2001 to 2019. Only 10.5% of the region and 20% of protected areas showed high spatial stability. Stable zones appeared both inside and outside protected areas. The south and northeast consistently exhibited high-priority regions. The legacy indicator highlighted areas of historical importance that have since declined in importance. New high-value areas emerged in the south. Static and dynamic approaches to conservation planning differed significantly. Many areas prioritized in 2019 alone ranked lower when long-term trends were considered. Our multiscale method underscores the need to integrate temporal dynamics into effective conservation strategies to achieve long-term conservation objectives in an efficient way.

Dinámicas de hábitat de las especies emblemáticas para la priorización de la conservación en el sureste europeo Resumen La pérdida de biodiversidad se acelera debido a la acción humana y es necesario agilizar la toma de decisiones para su conservación. La modelización y el seguimiento ex situ de la biodiversidad con base en series temporales de datos obtenidos por satélite podrían ser una herramienta asequible y rentable para mejorar la priorización de las áreas de conservación. Desarrollamos un conjunto de indicadores dinámicos para la priorización de la conservación basados en un análisis de tendencias del índice de idoneidad del hábitat (IIH) de seis especies emblemáticas (plantas, aves, anfibios, reptiles y mamíferos) durante 19 años (2001 ‐ 2019) en Andalucía (sur de España). Los modelos IIH se derivaron de modelos de nicho ecológico (MaxEnt) y datos de series temporales de satélite (MODIS) como predictores. Con base en los modelos IIH anuales de todas las especies y con la herramienta de priorización espacial de la conservación Marxan, derivamos indicadores dinámicos interanuales de la calidad del hábitat para la priorización de la conservación. En general, los modelos mostraron una regresión generalizada del hábitat. Los mejores predictores de la calidad del hábitat estaban relacionados con la composición y estructura de la vegetación (cubierta terrestre), el clima (temperatura de la superficie terrestre) y el balance energético (evapotranspiración), coincidiendo con la ecología de especies dependientes del clima (como Abies pinsapo) o de la vegetación (como Alytes dickhilleni). Marxan identificó dinámicas interanuales para las áreas prioritarias fuera y dentro de las áreas protegidas. La variación interanual en la calidad del hábitat condujo a cambios en las prioridades de conservación en toda Andalucía entre 2001 y 2019. Sólo el 10.5% de la región y el 20% de las áreas protegidas mostraron una alta estabilidad espacial. Aparecieron zonas estables tanto dentro como fuera de las áreas protegidas. El sur y el noreste mostraron sistemáticamente regiones de alta prioridad. El indicador de legado puso de relieve zonas de importancia histórica que desde entonces han perdido importancia. En el sur aparecieron nuevas zonas de gran valor. Los enfoques estáticos y dinámicos de la planificación de la conservación difirieron significativamente. Muchas zonas prioritarias que sólo se clasificaron en 2019 quedaron peor clasificadas cuando se tuvieron en cuenta las tendencias a largo plazo. Nuestro método multiescala subraya la necesidad de integrar la dinámica temporal en estrategias de conservación eficaces para alcanzar objetivos de conservación a largo plazo de forma eficiente.

Keywords: Natura 2000 network; análisis de series temporales; biodiversity monitoring; ecological niche models; habitat suitability; idoneidad de hábitat; modelos de nicho ecológico; monitoreo de biodiversidad; red Natura 2000; remote sensing; telemetría; time‐series analysis.

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Figures

FIGURE 1
FIGURE 1
Workflow for the development of dynamic indicators of priority conservation areas in Andalucia (southern Spain): (I) data collection (occurrence data for the target species and generation of annual MODIS time series [predictors]); (II) multiapproach modeling workflow (MaxEnt) (predictors obtained in step I); and (III) spatial–temporal habitat suitability index (HSI) trends (includes mapping trends) and developing priority protected area indicators (Marxan).
FIGURE 2
FIGURE 2
Species occurrences in 5 × 5‐km pixels (left) and habitat suitability index (HSI) trends in each occurrence pixel (right) (blue, positive trends; red, negative trends; gray, no trend; VU, vulnerable; EN, endangered; NT, near threatened). Photo of Podarcis carbonelli is by Toño Garcia, and the rest are under Creative Commons licenses.
FIGURE 3
FIGURE 3
Dynamic indicators of areas of conservation priority derived from Marxan simulations in Andalucia (southern Spain) for 2001–2019: (a) stability of priority areas (temporal variation) as a representation of the standard deviation of irreplaceability values (SD‐Irr indicator) (Table 2), (b) areas of historical importance (legacy) represented by the time since last designation by Marxan as an area of priority for conservation (TSD indicator), (c) stability of areas of conservation priority (risk‐to‐reward ratio) as a representation of the coefficient of variation of irreplaceability (CV‐Irr indicator), and (d) mean values of irreplaceability across time (cost‐effectiveness) (Mean‐Irr indicator) (red lines, limit of the current network of national and natural parks in Andalucia).
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References

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