2021
DOI: 10.1007/s13364-021-00556-9
|View full text |Cite
|
Sign up to set email alerts
|

Deforestation leads to prey shrinkage for an apex predator in a biodiversity hotspot

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
21
0
2

Year Published

2021
2021
2023
2023

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 21 publications
(24 citation statements)
references
References 46 publications
1
21
0
2
Order By: Relevance
“…The high frequency of use of small prey we found for this predator species may be related to changes in prey availability due to anthropic impacts, such as habitat loss and fragmentation. Indeed, according to the studies we analysed, Puma concolor consumes mainly large prey in regions with lower human influence such as Patagonia (Iriarte et al 1991), but feeds mainly on small rodents in study sites within altered landscapes, a pattern that has been found using both faecal content analysis and isotopic analysis (Magioli et al 2014, Magioli & Ferraz 2021. This trophic niche flexibility of Puma concolor may facilitate its ability to persist in human-modified landscapes (De Angelo et al 2011).…”
Section: Carnivorans' Diet Patternsmentioning
confidence: 69%
See 1 more Smart Citation
“…The high frequency of use of small prey we found for this predator species may be related to changes in prey availability due to anthropic impacts, such as habitat loss and fragmentation. Indeed, according to the studies we analysed, Puma concolor consumes mainly large prey in regions with lower human influence such as Patagonia (Iriarte et al 1991), but feeds mainly on small rodents in study sites within altered landscapes, a pattern that has been found using both faecal content analysis and isotopic analysis (Magioli et al 2014, Magioli & Ferraz 2021. This trophic niche flexibility of Puma concolor may facilitate its ability to persist in human-modified landscapes (De Angelo et al 2011).…”
Section: Carnivorans' Diet Patternsmentioning
confidence: 69%
“…Although we found a clear peak in body mass distributions of mammalian prey for all predators, we also found that many predators display bimodal body mass distributions of prey use, suggesting that these species often supplement their diets with alternative resources outside the optimum size range. The energetic balance resulting from consuming a given prey relates to other factors besides body mass that are intrinsic to the predators, such as other morphophysiological characteristics and behaviour, or to extrinsic factors, such as the determinants of prey availability – biogeography, prey activity patterns and land‐use patterns (Eriksen et al 2011, Beca et al 2017, Mendes et al 2020, Magioli & Ferraz 2021). Variation in prey availability may change the cost–benefit relationship of prey species (Svanbäck & Bolnick 2005) and favour the use of prey outside the expected body size range.…”
Section: Discussionmentioning
confidence: 99%
“…2019; Magioli, et al . 2019; Magioli & Ferraz, 2021); only hair from adult individuals were collected.…”
Section: Methodsmentioning
confidence: 99%
“…By consuming and trampling seedlings, preying upon or dispersing fruits and their seeds, returning these into the soil with nutrients and serving as prey for large predators, large mammalian herbivores are essential to maintaining diversity in tropical ecosystems (Villar et al . 2020, 2021; Magioli & Ferraz, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…Network approaches have been used for the prediction of risk and dynamics of dengue [18], Chagas disease [19], Rickettsiosis [20], Leishmaniasis [21] and a myriad of infectious diseases in livestock and wildlife [22]. Additionally, prediction of interaction networks is a growing imperative for next-generation biodiversity monitoring, requiring a conceptual framework and a flexible set of tools to predict interactions that is explicitly spatial and temporal in perspective [23][24][25]. Developing better models for prediction of these interactions will rely on integration of data from many sources, and the sources for this data may differ depending on the type of interaction we wish to predict [26].…”
Section: Introductionmentioning
confidence: 99%