Enhancing biodiversity conservation and monitoring in protected areas through efficient data management.

A scientifically informed approach to decision-making is key to ensuring the sustainable management of ecosystems, especially in the light of increasing human pressure on habitats and species. Protected areas, with their long-term institutional mandate for biodiversity conservation, play an important role as data providers, for example, through the long-term monitoring of natural resources. However, poor data management often limits the use and reuse of this wealth of information. In this paper, we share lessons learned in managing long-term data from the Italian Alpine national parks. Our analysis and examples focus on specific issues faced by managers of protected areas, which partially differ from those faced by academic researchers, predominantly owing to different mission, governance, and temporal perspectives. Rigorous data quality control, the use of appropriate data management tools, and acquisition of the necessary skills remain the main obstacles. Common protocols for data collection offer great opportunities for the future, and complete recovery and documentation of time series is an urgent priority. Notably, before data can be shared, protected areas should improve their data management systems, a task that can be achieved only with adequate resources and a long-term vision. We suggest strategies that protected areas, funding agencies, and the scientific community can embrace to address these problems. The added value of our work lies in promoting engagement with managers of protected areas and in reporting and analysing their concrete requirements and problems, thereby contributing to the ongoing discussion on data management and sharing through a bottom-up approach.

ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis.

Monitoring crop and rangeland conditions is highly relevant for early warning and response planning in food insecure areas of the world. Satellite remote sensing can obtain relevant and timely information in such areas where ground data are scattered, non-homogenous, or frequently unavailable. Rainfall estimates provide an outlook of the drivers of vegetation growth, whereas time series of satellite-based biophysical indicators at high temporal resolution provide key information about vegetation status in near real-time and over large areas. The new early warning decision support system ASAP (Anomaly hot Spots of Agricultural Production) builds on the experience of the MARS crop monitoring activities for food insecure areas, that have started in the early 2000's and aims at providing timely information about possible crop production anomalies. The information made available on the website (https://mars.jrc.ec.europa.eu/asap/) directly supports multi-agency early warning initiatives such as for example the GEOGLAM Crop Monitor for Early Warning and provides inputs to more detailed food security assessments that are the basis for the annual Global Report on Food Crises. ASAP is a two-step analysis framework, with a first fully automated step classifying the first sub-national level administrative units into four agricultural production deficit warning categories. Warnings are based on rainfall and vegetation index anomalies computed over crop and rangeland areas and are updated every 10 days. They take into account the timing during the crop season at which they occur, using remote sensing derived phenology per-pixel. The second step involves the monthly analysis at country level by JRC crop monitoring experts of all the information available, including the automatic warnings, crop production and food security-tailored media analysis, high-resolution imagery (e.g. Landsat 8, Sentinel 1 and 2) processed in Google Earth Engine and ancillary maps, graphs and statistics derived from a set of indicators. Countries with potentially critical conditions are marked as minor or major hotspots and a global overview is provided together with short national level narratives.

Truly sedentary? The multi-range tactic as a response to resource heterogeneity and unpredictability in a large herbivore.

Much research on large herbivore movement has focused on the annual scale to distinguish between resident and migratory tactics, commonly assuming that individuals are sedentary at the within-season scale. However, apparently sedentary animals may occupy a number of sub-seasonal functional home ranges (sfHR), particularly when the environment is spatially heterogeneous and/or temporally unpredictable. The roe deer (Capreolus capreolus) experiences sharply contrasting environmental conditions due to its widespread distribution, but appears markedly sedentary over much of its range. Using GPS monitoring from 15 populations across Europe, we evaluated the propensity of this large herbivore to be truly sedentary at the seasonal scale in relation to variation in environmental conditions. We studied movement using net square displacement to identify the possible use of sfHR. We expected that roe deer should be less sedentary within seasons in heterogeneous and unpredictable environments, while migratory individuals should be seasonally more sedentary than residents. Our analyses revealed that, across the 15 populations, all individuals adopted a multi-range tactic, occupying between two and nine sfHR during a given season. In addition, we showed that (i) the number of sfHR was only marginally influenced by variation in resource distribution, but decreased with increasing sfHR size; and (ii) the distance between sfHR increased with increasing heterogeneity and predictability in resource distribution, as well as with increasing sfHR size. We suggest that the multi-range tactic is likely widespread among large herbivores, allowing animals to track spatio-temporal variation in resource distribution and, thereby, to cope with changes in their local environment.

A one night stand? Reproductive excursions of female roe deer as a breeding dispersal tactic.

Breeding dispersal, defined as the net movement between successive breeding sites, remains a poorly understood and seldom reported phenomenon in mammals, despite its importance for population dynamics and genetics. In large herbivores, females may be more mobile during the breeding season, undertaking short-term trips (excursions) outside their normal home range. If fertilisation occurs, leading to gene flow of the male genome, this behaviour could be considered a form of breeding dispersal from a genetic point of view. Here, we investigated ranging behaviour of 235 adult roe deer using intensive GPS monitoring in six populations across Europe within the EURODEER initiative. We show that excursions are common from June to August among females, with 41.8% (vs. 18.1% of males) making at least one excursion. Most individuals performed only one excursion per season and departure dates for females were concentrated in time, centred on the rutting period, suggesting a link with reproduction. The distance females travelled during excursions was significantly greater than the site-specific average diameter of a male home range, while travel speed decreased once they progressed beyond this diameter, indicating search behaviour or interaction with other male(s) outside the resident male's territory. Because adults are normally highly sedentary, the potential for mating with relatives is substantial; hence, we conclude that rut excursions could be an alternative tactic enabling females to avoid mating with a closely related male. To understand better the ultimate drivers at play, it will be crucial to explore the genetic causes and consequences of this behaviour.

Seasonality, weather and climate affect home range size in roe deer across a wide latitudinal gradient within Europe.

1. Because many large mammal species have wide geographical ranges, spatially distant populations may be confronted with different sets of environmental conditions. Investigating how home range (HR) size varies across environmental gradients should yield a better understanding of the factors affecting large mammal ecology. 2. We evaluated how HR size of a large herbivore, the roe deer (Capreolus capreolus), varies in relation to seasonality, latitude (climate), weather, plant productivity and landscape features across its geographical range in Western Europe. As roe deer are income breeders, expected to adjust HR size continuously to temporal variation in food resources and energetic requirements, our baseline prediction was for HR size to decrease with proxies of resource availability. 3. We used GPS locations of roe deer collected from seven study sites (EURODEER collaborative project) to estimate fixed-kernel HR size at weekly and monthly temporal scales. We performed an unusually comprehensive analysis of variation in HR size among and within populations over time across the geographical range of a single species using generalized additive mixed models and linear mixed models, respectively. 4. Among populations, HR size decreased with increasing values for proxies of forage abundance, but increased with increases in seasonality, stochastic variation of temperature, latitude and snow cover. Within populations, roe deer HR size varied over time in relation to seasonality and proxies of forage abundance in a consistent way across the seven populations. Thus, our findings were broadly consistent across the distributional range of this species, demonstrating a strong and ubiquitous link between the amplitude and timing of environmental seasonality and HR size at the continental scale. 5. Overall, the variability in average HR size of roe deer across Europe reflects the interaction among local weather, climate and seasonality, providing valuable insight into the limiting factors affecting this large herbivore under contrasting conditions. The complexity of the relationships suggests that predicting ranging behaviour of large herbivores in relation to current and future climate change will require detailed knowledge not only about predicted increases in temperature, but also how this interacts with factors such as day length and climate predictability.

Wildlife tracking data management: a new vision.

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.