1
|
Abernathy HN, Crawford DA, Chandler RB, Garrison EP, Conner LM, Miller KV, Cherry MJ. Rain, recreation and risk: Human activity and ecological disturbance create seasonal risk landscapes for the prey of an ambush predator. J Anim Ecol 2023; 92:1840-1855. [PMID: 37415521 DOI: 10.1111/1365-2656.13976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 05/15/2023] [Indexed: 07/08/2023]
Abstract
Predation risk and prey responses exhibit fluctuations in space and time. Seasonal ecological disturbances can alter landscape structure and permeability to influence predator activity and efficacy, creating predictable patterns of risk for prey (seasonal risk landscapes). This may create corresponding seasonal shifts in antipredator behaviour, mediated by species ecology and trade-offs between risk and resources. Yet, how human recreation interacts with seasonal risk landscapes and antipredator behaviour remains understudied. In South Florida, we investigated the impact of a seasonal ecological disturbance, specifically flooding, which is inversely related to human activity, on interactions between Florida panthers (Puma concolor coryi) and white-tailed deer (Odocoileus virginianus). We hypothesized that human activity and ecological disturbances would interact with panther-deer ecology, resulting in the emergence of two distinct seasonal landscapes of predation risk and the corresponding antipredator responses. We conducted camera trap surveys across southwestern Florida to collect detection data on humans, panthers and deer. We analysed the influence of human site use and flooding on deer and panther detection probability, co-occurrence and diel activity during the flooded and dry seasons. Flooding led to decreased panther detections and increased deer detections, resulting in reduced deer-panther co-occurrence during the flooded season. Panthers exhibited increased nocturnality and reduced diel activity overlap with deer in areas with higher human activity. Supporting our hypothesis, panthers' avoidance of human recreation and flooding created distinct risk schedules for deer, driving their antipredator behaviour. Deer utilized flooded areas to spatially offset predation risk during the flooded season while increasing diurnal activity in response to human recreation during the dry season. We highlight the importance of understanding how competing risks and ecological disturbances influence predator and prey behaviour, leading to the generation of seasonal risk landscapes and antipredator responses. We emphasize the role of cyclical ecological disturbances in shaping dynamic predator-prey interactions. Furthermore, we highlight how human recreation may function as a 'temporal human shield,' altering seasonal risk landscapes and antipredator responses to reduce encounter rates between predators and prey.
Collapse
Affiliation(s)
- H N Abernathy
- Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
- Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, Texas, USA
- Haub School of Environment and Natural Resources, University of Wyoming, Laramie, Wyoming, USA
| | - D A Crawford
- Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, Texas, USA
- Jones Center at Ichauway, Newton, Georgia, USA
| | - R B Chandler
- Warnell School of Forestry and Natural Resources, Athens, Georgia, USA
| | - E P Garrison
- Florida Fish and Wildlife Conservation Commission, Tallahassee, Florida, USA
| | - L M Conner
- Jones Center at Ichauway, Newton, Georgia, USA
| | - K V Miller
- Warnell School of Forestry and Natural Resources, Athens, Georgia, USA
| | - M J Cherry
- Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, Texas, USA
| |
Collapse
|
2
|
Arrais RC, Widmer CE, Murray DL, Thornton D, Azevedo FCCD. Estimating density of ocelots in the Atlantic Forest using spatial and closed capture–recapture models. J Mammal 2022. [DOI: 10.1093/jmammal/gyac074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Monitoring variation in population features such as abundance and density is essential for evaluating and implementing conservation actions. Camera trapping can be important for assessing population status and trends and is increasingly used to generate density estimates through capture–recapture models. Moreover, success in using this technique can vary seasonally given shifting animal distributions and camera encounter rates. Notwithstanding these potential advantages, a gap still exists in our understanding of the performance of such models for estimating density of cryptic Neotropical terrestrial carnivores with low encounter rate probability with cameras. In addition, scanty information is available on how sampling design can affect the accuracy and precision of density estimates for Neotropical carnivores. We evaluate the performance of spatially explicit versus nonspatial capture–mark–recapture models for estimating densities and population size of ocelots (Leopardus pardalis) within an Atlantic Forest fragment in Brazil. We conducted two spatially concurrent surveys, a random camera-trap deployment covering the entire study area and a systematic camera-trap deployment in a small portion of the study area, where trails and unpaved roads were located. We obtained 244 photographs of ocelots in the Rio Doce State Park from April 2016 to November 2017, using 54-double camera stations spaced approximately 1.5 km apart (random placement) totaling 4,320 trap-nights and 15-double camera stations spaced from 0.3–10 km apart (systematic placement) totaling 1,200 trap-nights. Using the random placement design, ocelot density estimates were similar during the dry season, 14.0 individuals/km2 (± 5.6 SE, 6.6–30.0, 95% CI) and 13.78 individuals/km2 (± 4.25 SE, 5.4–22.1, 95% CI) from spatially explicit capture–recapture and nonspatial models, respectively. Using the systematic placement design spatially explicit models had smaller and less precise ocelot density estimates than nonspatial models during the dry season. Ocelot density was 12.4 individuals/100 km2 (± 5.0 SE, 5.8–26.7, 95% CI) and 19.9 individuals/km2 (± 5.2 SE, 9.7–30.1, 95% CI) from spatially explicit and nonspatial models, respectively. During the rainy season, we found the opposite pattern. Using the systematic placement design, spatial-explicit models had higher and less precise estimates than nonspatial models. Ocelot density was 24.6 individuals/100 km2 (± 13.9 SE, 8.7–69.4, 95% CI) and 11.89 individuals/km2 (± 3.93 SE, 4.19–19.59, 95% CI) from spatially explicit and nonspatial models, respectively. During the rainy season, we could not compare models using the random placement design due to limited number of recaptures to run nonspatial models. In addition, a single recapture yielded an imprecise population density estimate using spatial models (high SE and large 95% CIs), thus precluding any comparison between nonspatial and spatially explicit models. We demonstrate relative differences and similarities between the performance of spatially explicit and nonspatial capture–mark–recapture models for estimating density and population size of ocelots and highlight that both types of capture–recapture models differ in their estimation depending on the sampling design. We highlight that performance of camera surveys is contingent on placement design and that researchers need to be strategic in camera distribution according to study objectives and logistics. This point is especially relevant for cryptic or endangered species occurring at low densities and having low detection probability using traditional sampling methods.
Collapse
Affiliation(s)
- Ricardo Corassa Arrais
- Departamento de Ecologia, Conservação e Manejo de Vida Silvestre, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais , Belo Horizonte, Minas Gerais , Brazil
| | - Cynthia Elisa Widmer
- Projeto Carnívoros do Rio Doce – PCRD, Parque Estadual do Rio Doce , Marliéria, Minas Gerais , Brazil
| | - Dennis L Murray
- Department of Biology, Trent University , Peterborough, Ontario , Canada
| | - Daniel Thornton
- School of the Environment, Washington State University , Pullman, Washington , USA
| | - Fernando Cesar Cascelli de Azevedo
- Departamento de Ciências Naturais, Universidade Federal de São João del Rei , São João del Rei, Minas Gerais , Brazil
- Instituto Pró-Carnívoros , Atibaia, São Paulo , Brazil
| |
Collapse
|
3
|
Density, habitat use and activity patterns of the last giant armadillo population in the Brazilian Atlantic Forest. Mamm Biol 2022. [DOI: 10.1007/s42991-022-00277-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|