Satellite surface reflectance improves habitat distribution mapping: a case study on heath and shrub formations in the Cantabrian Mountains (NW Spain)

Livestock Management for the Delivery of Ecosystem Services in Fire-Prone Shrublands of Atlantic Iberia

In the northwest of the Iberian Peninsula, characterized by its humid climate, large rural areas are being abandoned, mostly in less-favoured areas covered by heathlands, which present a low nutritive quality for livestock production. The high combustibility of these shrublands is driving a high wildfire incidence with negative environmental and economic effects. In this review, some aspects on wildfire occurrence and the potential of grazing livestock to reduce woody phytomass and fire risk in heathland-dominated areas whilst maintaining quality production and preserving biodiversity are summarized. Heathlands may be partially improved—converted to grassland—to better meet animals’ nutritional requirements while acting as ‘natural’ firebreaks. The specific grazing behaviour offers the opportunity to combine different domestic herbivores (mixed grazing) to achieve sustainable systems utilizing heterogeneous resources. Cattle, sheep, goats, and horses may have a role in the provision of different ecosystem services such as food production and biodiversity conservation. Genotype x environment interactions shape the ability of animals to cope with poor vegetation conditions, with smaller species and breeds performing better than larger animals. Goats and horses are indicated to arrest woody encroachment. Sustainable grazing systems are affordable in heathland–grassland mosaics by selecting appropriate livestock species and breeds for quality production, thus favouring rural economies and lowering fire risk.

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam's lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species.