Land use scenarios, seasonality, and stream identity determine the water physicochemistry of tropical cloud forest streams

Abstract

Background: Land use is a major factor determining stream water physicochemistry. However, most streams move from one land use type to another as they drain their watersheds. Here, we studied three land use scenarios in a tropical cloud forest zone in Mexico. We addressed three main goals, to: (1) assess how land use scenarios generate different patterns in stream physicochemical characteristics; (2) explore how seasonality (i.e., dry, dry-to-wet transition, and wet seasons) might result in changes to those patterns over the year; and (3) explore whether physicochemical patterns in different scenarios resulted in effects on biotic components (e.g., algal biomass).

Methods: We studied Tropical Mountain Cloud Forest streams in La Antigua watershed, Mexico. Streams drained different three scenarios, streams with (1) an upstream section draining forest followed by a pasture section (F-P), (2) an upstream section in pasture followed by a forest section (P-F), and (3) an upstream forest section followed by coffee plantation (F-C). Physicochemistry was determined at the upstream and downstream sections, and at the boundary between land uses. Measurements were seasonal, including temperature, dissolved oxygen, conductivity, and pH. Water was analyzed for suspended solids, alkalinity, silica, chloride, sulfate, magnesium, sodium, and potassium. Nutrients included ammonium, nitrate, and phosphorus. We measured benthic and suspended organic matter and chlorophyll.

Results: Streams presented strong seasonality, with the highest discharge and suspended solids during the wet season. Scenarios and streams within each scenario had distinct physicochemical signatures. All three streams within each scenario clustered together in ordination space and remained close to each other during all seasons. There were significant scenario-season interactions on conductivity (F = 9.5, P < 0.001), discharge (F = 56.7, P < 0.001), pH (F = 4.5, P = 0.011), Cl^- (F = 12.2, P < 0.001), SO₄^2- (F = 8.8, P < 0.001) and NH₄⁺ (F = 5.4, P = 0.005). Patterns within individual scenarios were associated with stream identity instead of land use. Both P-F and F-C scenarios had significantly different physicochemical patterns from those in F-P in all seasons (Procrustes analysis, m₁₂ = 0.05-0.25; R = 0.86-0.97; P < 0.05). Chlorophyll was significantly different among scenarios and seasons (F = 5.36, P = 0.015, F = 3.81, P = 0.42, respectively). Concentrations were related to physicochemical variables more strongly during the transition season.

Conclusion: Overall, land use scenarios resulted in distinctive water physicochemical signatures highlighting the complex effects that anthropogenic activities have on tropical cloud forest streams. Studies assessing the effect of land use on tropical streams will benefit from assessing scenarios, rather than focusing on individual land use types. We also found evidence of the importance that forest fragments play in maintaining or restoring stream water physicochemistry.

Keywords: Cloud forest; Land use; Land use scenarios; Seasonality; Stream physicochemistry; Tropical streams.

Figure 1. Study streams draining different scenarios in the upper La Antigua watershed, Veracruz, Mexico.

The nine study streams were first or second order draining Forest-Pasture (F-P, green stars), Pasture-Forest (P-F, yellow circles), and Forest-Coffee plantation (F-C, red pentagons). Since we selected first to second order streams, not all symbols fall on a visible stream channel.

Figure 2. Principal Component Analysis of physicochemical variables at each scenario and season.

Scenarios are represented by symbols: Forest-Pasture (circles), Pasture-Forest (squares), and Forest-Coffee plantation (starts). Seasons are represented in colors and letters; dry (D, yellow), transition (T, red), and wet (W, blue). Two letters together represent the middle sampling point between land uses (e.g., PF: pasture to forest boundary).

Figure 3. (A–D) Comparison of major physicochemical variables among scenarios.

Only variables that were found significantly different among scenarios, without a significant scenario x season interaction, in 2-way ANOVA. Different lowercase letters within each panel indicate significant differences at P < 0.05.

Figure 4. (A–D) Comparison of major physicochemical variables among scenarios and seasons.

Only variables that were found significantly different in 2-way ANOVA are included. Different letters indicate significant differences at P < 0.05.

Figure 5. (A–I) Water temperature (°C) at the three sampling points per scenario during the three sampling seasons.

Same color symbols represent each of the three studied streams per scenario. The 0 m point is uppermost section, 100 m middle point represents the boundary between the two land uses, and 200 m point is the lowermost section. Land uses are forest (F), pasture (P), and coffee plantation (C).

Figure 6. (A–I) N-NO₃⁻ concentrations (µM) at the three sampling points per scenario during the three sampling seasons.

Same color symbols represent each of the three studied streams per scenario. The 0 m point is uppermost section, 100 m middle point represents the boundary between the two land uses, and 200 m point is the lowermost section. Land uses are forest (F), pasture (P), and coffee plantation (C).

Figure 7. (A–I) TP concentrations (µM) at the three sampling points per scenario during the three sampling seasons.

Same color symbols represent each of the three studied streams per scenario. The 0 m point is uppermost section, 100 m middle point represents the boundary between the two land uses, and 200 m point is the lowermost section. Land uses are forest (F), pasture (P), and coffee plantation (C).

Figure 8. Principal Component Analysis of physicochemical variables per each scenario and season.

Each PCA includes three sampling points at three streams within a particular scenario. (A–C) F-P, P-F, and F-C during the dry season, (D and E) the same scenarios during the transition season, and (G–I) the scenarios during the wet season.

Figure 9. Comparison of chlorophyll a concentrations among scenarios and seasons.

Different lowercase letters indicate significant differences in 2-way ANOVA at P < 0.05.