Empirical analysis and modeling of Argos Doppler location errors in Romania

Background Advances in wildlife tracking technology have allowed researchers to understand the spatial ecology of many terrestrial and aquatic animal species. Argos Doppler is a technology that is widely used for wildlife tracking owing to the small size and low weight of the Argos transmitters. This allows them to be fitted to small-bodied species. The longer lifespan of the Argos units in comparison to units outfitted with miniaturized global positioning system (GPS) technology has also recommended their use. In practice, large Argos location errors often occur due to communication conditions such as transmitter settings, local environment, and the behavior of the tracked individual. Methods Considering the geographic specificity of errors and the lack of benchmark studies in Eastern Europe, the research objectives were: (1) to evaluate the accuracy of Argos Doppler technology under various environmental conditions in Romania, (2) to investigate the effectiveness of straightforward destructive filters for improving Argos Doppler data quality, and (3) to provide guidelines for processing Argos Doppler wildlife monitoring data. The errors associated with Argos locations in four geographic locations in Romania were assessed during static, low-speed and high-speed tests. The effectiveness of the Douglas Argos distance angle filter algorithm was then evaluated to ascertain its effect on the minimization of localization errors. Results Argos locations received in the tests had larger associated horizontal errors than those indicated by the operator of the Argos system, including under ideal reception conditions. Positional errors were similar to those obtained in other studies outside of Europe. The errors were anisotropic, with larger longitudinal errors for the vast majority of the data. Errors were mostly related to speed of the Argos transmitter at the time of reception, but other factors such as topographical conditions and orientation of antenna at the time of the transmission also contributed to receiving low-quality data. The Douglas Argos filter successfully excluded the largest errors while retaining a large amount of data when the threshold was set to the local scale (two km). Discussion Filter selection requires knowledge about the movement patterns and behavior of the species of interest, and the parametrization of the selected filter typically requires a trial and error approach. Selecting the proper filter reduces the errors while retaining a large amount of data. However, the post-processed data typically includes large positional errors; thus, we recommend incorporating Argos error metrics (e.g., error ellipse) or use complex modeling approaches when working with filtered data

Identification of areas of very high biodiversity value to achieve the EU Biodiversity Strategy for 2030 key commitments

Background The European Union strives to increase protected areas of the EU terrestrial surface to 30% by year 2030, of which one third should be strictly protected. Designation of the Natura 2000 network, the backbone of nature protection in the EU, was mostly an expert-opinion process with little systematic conservation planning. The designation of the Natura 2000 network in Romania followed the same non-systematic approach, resulting in a suboptimal representation of invertebrates and plants. To help identify areas with very high biodiversity without repeating past planning missteps, we present a reproducible example of spatial prioritization using Romania’s current terrestrial Natura 2000 network and coarse-scale terrestrial species occurrence. Methods We used 371 terrestrial Natura 2000 Sites of Community Importance (Natura 2000 SCI), designated to protect 164 terrestrial species listed under Annex II of Habitats Directive in Romania in our spatial prioritization analyses (marine Natura 2000 sites and species were excluded). Species occurrences in terrestrial Natura 2000 sites were aggregated at a Universal Traverse Mercator spatial resolution of 1 km2. To identify priority terrestrial Natura 2000 sites for species conservation, and to explore if the Romanian Natura 2000 network sufficiently represents species included in Annex II of Habitats Directive, we used Zonation v4, a decision support software tool for spatial conservation planning. We carried out the analyses nationwide (all Natura 2000 sites) as well as separately for each biogeographic region (i.e., Alpine, Continental, Pannonian, Steppic and Black Sea). Results The results of spatial prioritization of terrestrial Natura 2000 vary greatly by planning scenario. The performance of national-level planning of top priorities is minimal. On average, when 33% of the landscape of Natura 2000 sites is protected, only 20% of the distribution of species listed in Annex II of Habitats Directive are protected. As a consequence, the representation of species by priority terrestrial Natura 2000 sites is lessened when compared to the initial set of species. When planning by taxonomic group, the top-priority areas include only 10% of invertebrate distribution in Natura 2000. When selecting top-priority areas by biogeographical region, there are significantly fewer gap species than in the national level and by taxa scenarios; thusly, the scenario outperforms the national-level prioritization. The designation of strictly protected areas as required by the EU Biodiversity Strategy for 2030 should be followed by setting clear objectives, including a good representation of species and habitats at the biogeographical region level

Space use data and systematic conservation planning inform habitat conservation priorities for brown bears in Romania

Recovery of large carnivores in the European human-dominated landscapes has sparked a debate regarding the optimal landscape conditions in which carnivores can thrive and coexist with humans (López-Bao et al. 2015). Here, we use brown bears (Ursus arctos) in the Romanian Carpathians to test and develop a framework for identifying habitat conservation priorities based on a novel integration of resource selection functions, home range data, and systematic conservation planning (Pop et al. 2018). We used a comprehensive GPS telemetry dataset from 18 individuals to (1) calculate sex-specific seasonal home ranges, and (2) characterize population-level habitat selection. We then used systematic conservation planning software Zonation to identify contiguous areas of high conservation value for males and females by using Manly’s habitat selection ratios as weights for habitat layers, and home range information as a smoothing parameter for habitat connectivity. Home ranges were smallest during winter (median [IQR] for November-February: 28.2 km2 [9.8-42.4]), and largest during the intense-feeding season (September-November: 127.3 km2 [62.2-288.5]), with males having larger home ranges across all seasons. Females consistently selected for mixed forest habitat during all seasons. Males selected mixed forest during winter; then switched to a rather generalist approach, selecting regenerating forest, and mixed and coniferous forests during low-feeding/reproduction and wild berries seasons. We identified large tracts of forest habitat (~14% of the landscape) that was selected across all seasons as key habitats for brown bear conservation in the Eastern Carpathians. Spatially, high-value winter habitat was the most dissimilar for both males and females, suggesting that conservation actions should focus on protecting contiguous denning habitat. These key findings can inform the management and conservation of the brown bear population in the Romanian Carpathians, currently plagued by high uncertainity in management outcomes (Popescu et al. 2016) by identifying critical intervention areas for maintaining landscape connectivity, enable transboundary management, and contribute to maintaining Favourable Conservation Status, an important target of European Union Strategy for Biodiversity. 1. López-Bao, J.V., Kaczensky, P., Linnell, J.D.C., Boitani, L. & Chapron, G. (2015). Carnivore coexistence: Wilderness not required. Science 348, 871–872. 2. Pop, M. I., R. Iosif, I. V. Miu, S. Chiriac, L. Rozylowicz, and V. D. Popescu. 2018. Combining resource selection functions and home range data to identify habitat conservation priorities for brown bears. Animal Conservation. in press 3. Popescu, V. D., K. A. Artelle, M. I. Pop, S. Manolache, and L. Rozylowicz. 2016. Assessing biological realism of wildlife population estimates in data-poor systems. Journal of Applied Ecology 53, 1248-1259peerReviewe

Understanding how the scientific community influences grasslands’ management decisions – a social network approach

Farming landscapes of Europe are vital arenas for social-ecological sustainability because their significant coverage and potential to integrate food production with biodiversity conservation. While the term 'governance' is popular but imprecise, network governance is well defined, and allows the analysis of informal and formal arrangements where independent people or organization work together towards a common goal (Scarlett and McKinney 2016). Even though real progress has been made in conceptualizing and analyzing network governance in landscape conservation, the use of social network analysis remains at an exploratory stage. This is mostly because methodological and epistemological differences between social science and ecology tools, which make the interdisciplinary approaches a challenging task (Popescu et al. 2014). The number of studies focused on management of grasslands in Romania is limited, and the grasslands management is still deficient despite the late legal motions, which most often do not consider the contribution of science to the process. Therefore, one important issue affecting grasslands management is the gap between practice and research, and no current approach captures the level of cooperation among the researchers in the field. As a result, it is necessary to demonstrate that interactions between researchers, policy makers and stakeholders can have a crucial impact on the management quality. This is why, this paper aims at using Social Network Analysis (SNA), a well-developed scientific domain that envisages network theory to analyze relationships between authors and current situation of the overall scientific network (available online on Scopus) compared with the Romanian network. The results illustrate co-authorship networks, invisible authors, academic stars, research groups dealing with grasslands, research topics in clusters, collaboration between domains, most central researchers, bridge researchers, and also interinstitutional cooperation. Thus, understanding the roles of researchers in the field, and also the connections established within a grassland management network may provide information for designing a better management (Plieninger et al. 2015) and will help Romanian scientists to reframe the debate surrounding the conservation of biodiversity in human-dominated landscapes. Our SNA findings will lead to improved collaboration and knowledge exchange between practitioners, scientists, policy makers and stakeholders and therefore will help overcome the main issues caused by Common Agricultural Policies. Because of the biodiversity impacts of contradictory EU policies, it is fundamental for Romanian scientists and authorities to re-evaluate the traditional approaches based exclusively on protection and conservation, and rethink the landscape policy, leading it towards planning and managing by considering the past experiences, research, traditions, and public attitudes.peerReviewe

Who is researching biodiversity hotspots in Eastern Europe? A case study on the grasslands in Romania.

European farmlands are vital arenas for socio-ecological sustainability because of their significant land coverage and potential for integrating food production with biodiversity conservation. The knowledge produced by scientific research is a critical ingredient in developing and implementing socio-economically and ecologically sustainable management strategies for farming landscapes. The grasslands of Europe have been managed for millennia. They have exceptional socio-cultural and economic value and are among the most biodiverse ecosystems in the world. The quality of scientific knowledge on them and its potential to address grasslands as complex socio-ecological systems is strongly dependent not only on the creativity and scientific ambition of the researcher, but also on the network around the researcher (including both academic and non-academic sectors). The goal of this study is to map the research network around Romania's grasslands using bibliometrics analysis, a well-developed scientific domain that utilizes network theory to analyze relationships between affiliations networks, co-authorship networks, and co-word analysis. The number of studies targeting grasslands in Romania is increasing, owing mostly to international involvement. However, management of the grasslands is still deficient and the contribution of science to the process is virtually absent. The current research is mainly related to the biological and ecological characteristics of grasslands, with topics related to their management notably absent from internationally visible research, especially in the context of EU Common Agricultural Policies. To increase scientific inquiry and better inform the EU and local policies on grasslands management, Romanian researchers should capitalize on international collaborations and local academic leaders. Our findings can be used to identify research gaps and to improve collaboration and knowledge exchange between practitioners, researchers, policy makers, and stakeholders

A social network approach for assessing sustainability of traditionally managed grasslands in a policy-driven management context

A substantial coverage of native vegetation with high diversity of structural elements, protected species and functional groups can be an important source of resilience for the farming landscapes. Nevertheless, the new Common Agricultural Policies (CAP) measures contradict the EU Biodiversity Strategy to 2020 objective of halting the loss of grasslands, by making agricultural intensification or afforestation an attractive option for farmers (Pe'er et al. 2014). This situation can be interpreted as a "rigidity trap" case, where the landowners recognize the unsuitability of CAP measures but are encouraged to continue by EU subsidies. Furthermore, acquisition of agricultural lands by large landowners (land concentration) allows a small number of owners to control large swaths of land. Such threats simplify the management of grasslands, change the connections among farmers and ultimately disrupt the traditional land use (Hartel and Plieninger 2014). Governance structures involved in agricultural landscape management are highly fragmented mostly because policy and operational responsibilities are divided between an array of organizations and persons which makes the analysis of governance structures difficult with conventional tools. However, network governance allows the analysis of informal and formal arrangements where independent people or organisations work together for a common goal, such as management of grasslands (Alexander et al. 2016). To analyze the changes in grasslands governance induced by EU CAP policies, we use social network analysis to contrast two areas over time (before and after influence of CAP) in two regions from Romania - Iron Gates Natural Park and Dobrogea. We selected two Romanian regions (Iron Gates Natural Park (IGNP) - SW Romania and Dobrogea - SE Romania), representative for grassland management in mountain and lowland settings, respectively. The IGNP pasture management was traditionally performed in a decentralized, community-level system and this type of management continues to this day. In contrast, Dobrogea was characterized by a centralized, state-run management regime during the communist time, and by large landowners after transition period ended. We first identified actors of grasslands' governance (i.e., organisations, local people) and analyse management networks using social network metrics (e.g., network-level metrics), we then, identified actors or groups of actors with leadership roles, mainly those promoting sustainability of traditionally managed grasslands in a EU policy-driven management context (e.g., pioneer, sponsor, steward, facilitator of a network), and finally, reported the difference between management regimes in two areas. The results allowed us to explore barriers and opportunities for successful governance by considering influences of typical practices regarding landscape governance and performance, and to understand how formal policy networks influence informal social networks.peerReviewe

Ghid pentru estimarea abundenței și ocupanței animalelor sălbatice

Estimarea abundenței şi ocupanţei speciilor constituie una din cele mai dificile și importante activităţi de management a speciilor sălbatice. Datele pentru aceste estimări se obțin în principal din studii de capturare-recapturare (abundenţă) și studii de tip ocupanță sau N-mixture (ocupanţă sau abundenţă). Dacă studiile de capturare-recapturare sunt mai greu de aplicat, uneori imposibil precum în cazul urşilor, studiile care nu necesită identificarea indivizilor (ocupanță, N-mixture sau alte variante) pot fi mai uşor de pus în practică din punct de vedere logistic, dar sunt dificil de analizat statistic. Scopul acestui ghid este accesibilizeze astfel de modele de analiză și să îmbunătățească estimările demografice sau de distribuţie ale populațiilor speciilor de animale sălbatice din România, prin dezvoltarea explicarea și exemplificarea modelelor statistice de ocupanță și abundență. Cel mai adesea, studierea animalelor sălbatice implică identificarea urmelor sau amplasarea camerelor foto, fiind astfel sunt relativ ușor de implementat pe teren, dar pentru a obține date robuste sunt necesare protocoale de prelevare corecte și o analiză statistică a datelor riguroasă. Analiza statistică poate fi realizată folosind modelele ierarhice, în special modelele de ocupanță sau N-mixture, care permit cercetătorilor să țină cont de detectare imperfectă faunei sălbatice. Acest lucru înseamnă că modelele pot estima probabilitatea ca o specie să fie prezentă într-o locație chiar dacă nu este observată. De asemenea, detectarea unei specii nu este întotdeauna garantată chiar dacă aceasta este prezentă. Aceste modele statistice sunt capabile să estimeze chiar şi în prezenţa dator lipsă sau incomplete, o problemă comună în studiile ecologice. Ghidul include un sumar al metodelor de detectare a speciilor (urme, peleţi, ADN, sunete, structuri specifice, observaţii directe, camere foto, observaţii aeriene, camere cu termoviziune, interviuri, baze de date preexistente, citizen science), prezentarea modelelor de ocupanță și N-mixture pentru un sezon și o specie, precum şi aplicaţii practice prin care se simulează un studiu folosind programul R unmarked. Acest ghid servește ca o resursă esențială pentru cercetătorii și managerii faunei sălbatice, oferind metodologii detaliate și instrumente practice pentru estimarea ocupanței și abundenței populațiilor de animale nemarcate, integrând exemple practice și cod R pentru a exemplifica metodele

Collaboration Networks in Applied Conservation Projects across Europe

<div><p>The main funding instrument for implementing EU policies on nature conservation and supporting environmental and climate action is the LIFE Nature programme, established by the European Commission in 1992. LIFE Nature projects (>1400 awarded) are applied conservation projects in which partnerships between institutions are critical for successful conservation outcomes, yet little is known about the structure of collaborative networks within and between EU countries. The aim of our study is to understand the nature of collaboration in LIFE Nature projects using a novel application of social network theory at two levels: (1) collaboration between countries, and (2) collaboration within countries using six case studies: Western Europe (United Kingdom and Netherlands), Eastern Europe (Romania and Latvia) and Southern Europe (Greece and Portugal). Using data on 1261 projects financed between 1996 and 2013, we found that Italy was the most successful country not only in terms of awarded number of projects, but also in terms of overall influence being by far the most influent country in the European LIFE Nature network, having the highest eigenvector (0.989) and degree centrality (0.177). Another key player in the network is Netherlands, which ensures a fast communication flow with other network members (closeness—0.318) by staying connected with the most active countries. Although Western European countries have higher centrality scores than most of the Eastern European countries, our results showed that overall there is a lower tendency to create partnerships between different organization categories. Also, the comparisons of the six case studies indicates significant differences in regards to the pattern of creating partnerships, providing valuable information on collaboration on EU nature conservation. This study represents a starting point in predicting the formation of future partnerships within LIFE Nature programme, suggesting ways to improve transnational cooperation and communication.</p></div

Conservation Priorities for Terrestrial Mammals in Dobrogea Region, Romania

© Iulia V. Miu et al. Based on species occurrence records of museum collections, published literature, and unpublished records shared by mammalian experts, we compiled a distribution database for 59 terrestrial mammals populating the extensively protected Dobrogea Region of Romania. The spatial patterns of mammal distribution and diversity was evaluated and systematic conservation planning applied to identify priority areas for their conservation. The spatial analyses revealed that intensive sampling was not directly correlated to mammal diversity but rather to accessibility for inventory. The spatial prioritisation analysis indicated a relatively aggregated pattern of areas with a high or low conservation value with virtually no connecting corridors between them. The significant overlap between Natura 2000 sites and national protected areas induced an over-optimistic vision of the effectiveness and representativeness of existing Natura 2000 network for species found in Annexes II and IV of the Habitats Directive. These results represent a key step in identifying core areas for the protection of mammal diversity and dispersal corridors for improved connectivity, and to guide future conservation efforts in increasing the effectiveness of the existing protected areas in the context of environmental changes