SppTrend-package: SppTrend: Analyzing Linear Trends in Species Occurrence Data

In SppTrend: Analyzing Linear Trends in Species Occurrence Data

SppTrend: Analyzing Linear Trends in Species Occurrence Data

Description

Provides a methodology to analyze how species occurrences change over time, particularly in relation to spatial and thermal factors. It facilitates the development of explanatory hypotheses about the impact of environmental shifts on species by analyzing historical presence data that includes temporal and geographic information. Approach described in Lobo et al., 2023 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/ece3.10674")}.

Details

Methodology

SppTrend assumes that observed species occurrences reflect a temporal sequence of changes in response to environmental drivers.

The analysis uses:

• Predictors: Sampling date (e.g., year or year-month decimals).

• Responses: Geographic location (latitude, longitude or elevation) and environmental factors (temperature).

Workflow

SppTrend provides a structured workflow for analyzing these trends:

1. Rapid diagnostic and visual summary: Perform a quick visual diagnostic of the input data using get_fast_info.

2. Environmental data integration (optional): Enhance occurrence records with environmental context using functions like get_era5_tme (temperature) or get_elevation (elevation).

3. Overall trend estimation: Calculate the overall temporal trend (OT) of selected response variables across the entire dataset using overall_trend. This serves as a neutral reference against which species-specific temporal trends are evaluated

4. Individual trend analysis: Estimate the species-specific temporal trends for each selected response variable using spp_trend. This compares individual species' responses to the overall trend via interaction models.

5. Ecological strategy classification: Classify species into distinct Spatial or Thermal response strategies based on the direction and statistical significance of their species-specific trends relative to the overall trend using spp_strategy.

More details

Source code: https://github.com/MarioMingarro/SppTrend

Author(s)

Maintainer: Mario Mingarro [e-mail] (ORCID)

Authors:

• Emilio García-Roselló (ORCID)

• Jorge M. Lobo (ORCID)

SppTrend documentation built on Feb. 7, 2026, 5:07 p.m.