Estimating home-range size: when to include a third dimension?

Most studies dealing with home ranges consider the study areas as if they were totally flat, working only in two dimensions, when in reality they are irregular surfaces displayed in three dimensions. By disregarding the third dimension (i.e., topography), the size of home ranges underestimates the surface actually occupied by the animal, potentially leading to misinterpretations of the animals' ecological needs. We explored the influence of considering the third dimension in the estimation of home-range size by modeling the variation between the planimetric and topographic estimates at several spatial scales. Our results revealed that planimetric approaches underestimate home-range size estimations, which range from nearly zero up to 22%. The difference between planimetric and topographic estimates of home-ranges sizes produced highly robust models using the average slope as the sole independent factor. Moreover, our models suggest that planimetric estimates in areas with an average slope of 16.3° (±0.4) or more will incur in errors ≥5%. Alternatively, the altitudinal range can be used as an indicator of the need to include topography in home-range estimates. Our results confirmed that home-range estimates could be significantly biased when topography is disregarded. We suggest that study areas where home-range studies will be performed should firstly be scoped for its altitudinal range, which can serve as an indicator for the need for posterior use of average slope values to model the surface area used and/or available for the studied animals.This work was partially supported by a research project from the Spanish National Plan (project ref: CGL2009-10741) funded by the Spanish Ministry of Science and Innovation and EU-FEDER funds. P. M. was supported by a Ph.D. grant from the Fundaçao para a Ciència e a Tecnologia (FCT) (SFRH/BD/37795/2007). N. S. was partially supported by a postdoctoral grant from FCT (SFRH/BPD/26666/2006). L. M. R. was funded by a Postdoctoral fellowship from the FCT and Fundo Social Europeu (III Quadro Comunitario de Apoio) (SFRH/BPD/35842/2007) and FAPESP (Proc. Ref.: 2011/00408-4).Peer Reviewe

Three decades of research on Iberian wild Carnivora: trends, highlights, and future directions

1. Mammalian carnivores (Carnivora) are crucial components of landscapes, because of both their top-down effects on lower trophic level species and their sensitivity to bottom-up processes, such as limited food resources (e.g. due to climate instability). To understand their functional role in Iberian ecosystems more clearly, and to define effective plans for their management and conservation, it is crucial to sum up the available regional knowledge that can inform decision-making processes.2. We review bio-ecological research on wild Iberian carnivores over 30 years (1990–2020) and identify key knowledge gaps and priority avenues for future research. Based on a systematic review of the scientific literature, we aimed to: 1) summarise current knowledge; 2) assess species and ecoregion representativeness; 3) identify key research topics addressed and those lacking investment and 4) suggest key future research priorities.3. We examined 920 peer-reviewed articles involving wild Iberian mammalian carnivores, focusing on different bio-ecological issues. We found considerable heterogeneity in the topics and species investigated, as well as in the study areas (ecoregions) explored, with a mismatch between the research priorities identified by researchers and the knowledge gaps.4. We suggest that future research should prioritise: 1) rear-edge populations that are at the southwestern limits of the species' Eurasian range, thus being particularly sensitive to the increasing fragmentation and aridity of Iberian ecosystems, and that were less studied (e.g. brown bear Ursus arctos, stoat Mustela erminea, European mink Mustela lutreola and pine marten Martes martes); 2) less-studied topics, such as morphometry and body condition, ecophysiology, and reproductive biology, all of which provide essential information for species' management and conservation and 3) specific ecoregions for which studies on species' adaptations to environmental and anthropic contexts are lacking (e.g. northern ecoregions of Iberia, Iberian conifer forests and Northwest Iberian montane forests). Our review provides the necessary background to support future research on carnivore populations in Iberia.João Carvalho was supported by a research contract (CEECIND/01428/2018) from the Fundação para a Ciência e a Tecnologia (FCT). Nuno Santos was also supported by Fundação para a Ciência e Tecnologia (SFRH/BPD/116596/2016). Carlos Fernandes appreciates the support of cE3c through an Assistant Researcher contract (FCiência.ID contract #366) and FCT (Fundação para a Ciência e a Tecnologia) for Portuguese National Funds attributed to cE3c within the strategic project UID/BIA/00329/2020. Carlos Fernandes also thanks FPUL for a contract of Invited Assistant Professor. Pedro Monterroso was supported by UID/BIA/50027/2021 with funding from FCT/MCTES through national funds. Thanks are due to FCT/MCTES for the financial support to cE3c (UIDB/00329/2020), CHANGE (LA/P/0121/2020) and CESAM (UIDP/50017/2020 + UIDB/50017/2020+ LA/P/0094/2020), through national funds, and FEDER co-funding within the PT2020 Partnership Agreement and Compete 2020. This work was also financially supported by: i) project POCI-01-0145-FEDER-028204 (WildForests) funded by FEDER, through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI), and by national funds (OE) through FCT/MCTES; Project ref. 2022.03253.PTDC (ForCe), funded by national funds (OE) through FCT; iii) project NORTE-01-0246-FEDER-000063, supported by the Norte Portugal Regional Operational Programme (NORTE2020) under the PORTUGAL 2020 Partnership Agreement and through the European Regional Development Fund (ERDF).Peer reviewe

Genetic integrity of European wildcats: Variation across biomes mandates geographically tailored conservation strategies

Hybridisation between domestic and wild taxa can pose severe threats to wildlife conservation, and human-induced hybridisation, often linked to species' introductions and habitat degradation, may promote reproductive opportunities between species for which natural interbreeding would be highly unlikely. Using a biome-specific approach, we examine the effects of a suite of ecological drivers on the European wildcat's genetic integrity, while assessing the role played by protected areas in this process. We used genotype data from 1217 putative European wildcat samples from 13 European countries to assess the effects of landcover, disturbance and legal landscape protection on the European wildcat's genetic integrity across European biomes, through generalised linear models within a Bayesian framework. Overall, we found European wildcats to have genetic integrity levels above the wildcat-hybrid threshold (ca. 83%; threshold = 80%). However, Mediterranean and Temperate Insular biomes (i.e., Scotland) revealed lower levels, with 74% and 46% expected genetic integrity, respectively. We found that different drivers shape the level of genetic introgression across biomes, although forest integrity seems to be a common factor promoting European wildcat genetic integrity. Wildcat genetic integrity remains high, regardless of landscape legal protection, in biomes where populations appear to be healthy and show recent local range expansions. However, in biomes more susceptible to hybridisation, even protected areas show limited effectiveness in mitigating this threat. In the face of the detected patterns, we recommend that species conservation and management plans should be biome- and landscape-context-specific to ensure effective wildcat conservation, especially in the Mediterranean and Temperate Insular biomes.Thanks are due to FCT/MCTES for the financial support to cE3c (UIDB/00329/2020), through national funds, and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. PM was supported by UID/BIA/50027/2021 with funding from FCT/MCTES through national funds. FDR was supported by a postdoctoral contract from the University of Málaga (I Plan Propio de Investigación y Transferencia, call 2020). This study was partly funded by research projects CGL2009-10741, funded by the Spanish Ministry of Science and Innovation and EU-FEDER, and OAPN 352/2011, funded by the Organismo Autónomo Parques Nacionales (Spain). Luxembourg sample collection has been co-funded by the Ministry of Environment, Climate and Sustainable Development of Luxembourg. We would like to thank the Bavarian Forest National Park Administration for the approval and support in collecting samples.Peer reviewe

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Livelihood vulnerability and human-wildlife interactions across protected areas

Protected Areas (PAs) are important wildlife refuges and act as climate change buffers, but they may impact human livelihoods, particularly engendering a high risk of negative human -wildlife interactions (HWI). Understanding synergies and tradeoffs among the drivers of overall human vulnerability within PAs is needed to ensure good outcomes for conservation and human wellbeing. We examined how climate variability, HWI, and socio-demographics affect livelihood vulnerability across three PAs in Mozambique, Southeast Africa. We used structured questionnaires to obtain information on livelihood vulnerability and socialecological context -specific variables. We applied principal component analysis to understand synergies and trade-offs between the dimensions of vulnerability and linear models to test the effect of social -ecological drivers on vulnerability. We show that households are mostly vulnerable within PAs due to exposure to climate variability and to HWI, and their low capacity to employ livelihood strategies or to have a strong social network. Furthermore, we show that vulnerability to HWI and climate variability increases with distance to strict protection areas within the PAs and distance to rivers, which implies that proximity to strict protection areas and rivers within PAs still promotes better livelihood conditions than elsewhere. On the other hand, we also found that lower access to infrastructure and other livelihood assets enhances vulnerability, which reflects a trade-off within PAs that potentially limits the benefits of socially inclusive conservation. Our results show that the impacts of PAs, HWI, and climate on community vulnerability should not be viewed in isolation, but instead, conservation and livelihood improvement strategies should reflect their interconnectedness. Although livelihood vulnerability appears to be shaped by these general effects of PAs, it is important also to consider the local PA context when addressing or mitigating livelihood vulnerability in and around them