English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Shade-grown coffee plantations are part of the regional landscape and may contribute to the diversity of woody plants. Tree species richness was evaluated in eight active and abandoned coffee plantations. We used non-parametric (ACE, ICE, Chao 1, Chao 2, Jackknife 1, Jackknife 2, Bootstrap) and asymptotic models (Clench, Linear) to compare observed or sampled richness with estimated richness. The precision of the estimators was evaluated as bias and accuracy through the comparison of estimated richness and true (or total) richness values. Observed richness was 55 tree species in active coffee plantations and 61 species in abandoned plantations. Most species showed a clumped distribution. In no case did species-accumulation curves reach an asymptote. ICE and Chao 2 displayed the best performance. Parametric models were the least precise and Jackknife 2 was the most precise. Non-parametric estimators have disadvantages, but they appear to be appropriate to estimate richness in managed systems such as coffee plantations.

Evaluación de métodos no paramétricos para la estimación de riqueza de especies de plantas leñosas en cafetales