Terrestrial hydrological controls on land surface phenology of African savannas and woodlands

This paper presents a continental-scale phenological analysis of African savannas and woodlands. We apply an array of synergistic vegetation and hydrological data records from satellite remote sensing and model simulations to explore the influence of rainy season timing and duration on regional land surface phenology and ecosystem structure. We find that (i) the rainy season onset precedes and is an effective predictor of the growing season onset in African grasslands. (ii) African woodlands generally have early green-up before rainy season onset and have a variable delayed senescence period after the rainy season, with this delay correlated nonlinearly with tree fraction. These woodland responses suggest their complex water use mechanisms (either from potential groundwater use by relatively deep roots or stem-water reserve) to maintain dry season activity. (iii) We empirically find that the rainy season length has strong nonlinear impacts on tree fractional cover in the annual rainfall range from 600 to 1800 mm/yr, which may lend some support to the previous modeling study that given the same amount of total rainfall to the tree fraction may first increase with the lengthening of rainy season until reaching an “optimal rainy season length,” after which tree fraction decreases with the further lengthening of rainy season. This nonlinear response is resulted from compound mechanisms of hydrological cycle, fire, and other factors. We conclude that African savannas and deciduous woodlands have distinctive responses in their phenology and ecosystem functioning to rainy season. Further research is needed to address interaction between groundwater and tropical woodland as well as to explicitly consider the ecological significance of rainy season length under climate change

Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics –i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (−20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—'chronic water stress', 'acute water stress' and 'minimum water stress' - which are respectively associated with three broad spatial patterns of African ecosystem physiognomy, i.e. savannas, woodlands, and tropical forests

Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are already limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales

Soil biogeochemistry across Central and South American tropical dry forests

The availability of nitrogen (N) and phosphorus (P) controls the flow of carbon (C) among plants, soils, and the atmosphere, thereby shaping terrestrial ecosystem responses to global change. Soil C, N, and P cycles are linked by drivers operating at multiple spatial and temporal scales: landscape-level variation in macroclimate and soil geochemistry, stand-scale heterogeneity in forest composition, and microbial community dynamics at the soil pore scale. Yet in many biomes, we do not know at which scales most of the biogeochemical variation emerges, nor which processes drive cross-scale feedbacks. Here, we examined the drivers and spatial/temporal scales of variation in soil biogeochemistry across four tropical dry forests spanning steep environmental gradients. To do so, we quantified soil C, N, and P pools, extracellular enzyme activities, and microbial community structure across wet and dry seasons in 16 plots located in Colombia, Costa Rica, Mexico, and Puerto Rico. Soil biogeochemistry exhibited marked heterogeneity across the 16 plots, with total organic C, N, and P pools varying fourfold, and inorganic nutrient pools by an order of magnitude. Most soil characteristics changed more across space (i.e., among sites and plots) than over time (between dry and wet season samplings). We observed stoichiometric decoupling among C, N, and P cycles, which may reflect their divergent biogeochemical drivers. Organic C and N pool sizes were positively correlated with the relative abundance of ectomycorrhizal trees and legumes. By contrast, the distribution of soil P pools was driven by soil geochemistry, with larger inorganic P pools in soils with P-rich parent material. Most earth system models assume that soils within a texture class operate similarly, and ignore subgrid cell variation in soil properties. Here we reveal that soil nutrient pools and fluxes exhibit as much variation among four Neotropical dry forests as is observed across terrestrial ecosystems at the global scale. Soil biogeochemical patterns are driven not only by regional differences in soil parent material and climate, but also by local-scale variation in plant and microbial communities. Thus, the biogeochemical patterns we observed across the Neotropical dry forest biome challenge representation of soil processes in ecosystem models

Synergistic ecoclimate teleconnections from forest loss in different regions structure global ecological responses

ABSTRACT: Forest loss in hotspots around the world impacts not only local climate where loss occurs, but also influences climate and vegetation in remote parts of the globe through ecoclimate teleconnections. The magnitude and mechanism of remote impacts likely depends on the location and distribution of forest loss hotspots, but the nature of these dependencies has not been investigated. We use global climate model simulations to estimate the distribution of ecologically-relevant climate changes resulting from forest loss in two hotspot regions: western North America (wNA), which is experiencing accelerated dieoff, and the Amazon basin, which is subject to high rates of deforestation. The remote climatic and ecological net effects of simultaneous forest loss in both regions differed from the combined effects of loss from the two regions simulated separately, as evident in three impacted areas. Eastern South American Gross Primary Productivity (GPP) increased due to changes in seasonal rainfall associated with Amazon forest loss and changes in temperature related to wNA forest loss. Eurasia’s GPP declined with wNA forest loss due to cooling temperatures increasing soil ice volume. Southeastern North American productivity increased with simultaneous forest loss, but declined with only wNA forest loss due to changes in VPD. Our results illustrate the need for a new generation of local-to-global scale analyses to identify potential ecoclimate teleconnections, their underlying mechanisms, and most importantly, their synergistic interactions, to predict the responses to increasing forest loss under future land use change and climate change