scholarly journals Exploring Surface Biophysical-Climate Sensitivity to Tropical Deforestation Rates Using a GCM: A Feasibility Study*

2012 ◽  
Vol 16 (4) ◽  
pp. 1-23 ◽  
Author(s):  
C. Kendra Gotangco Castillo ◽  
Kevin Robert Gurney
Keyword(s):  
Climate Sensitivity ◽  
Amazon Basin ◽  
Forest Cover ◽  
Tropical Deforestation ◽  
Tree Cover ◽  
Dynamic Global Vegetation Model ◽  
Climate System Model ◽  
Deforestation Rates ◽  
Global Vegetation

Abstract Deforestation perturbs both biophysical and carbon feedbacks on climate. However, biophysical feedbacks operate at temporally immediate and spatially focused scales and thus may be sensitive to the rate of deforestation rather than just to total forest-cover loss. Explored here is a method for simulating annual tropical deforestation in the fully coupled Community Climate System Model, version 3.0 (CCSM3) with the Dynamic Global Vegetation Model (DGVM) for testing biosphere climate sensitivity to “preservation pathways.” Two deforestation curves were simulated—a 10% deforestation curve with a 10% preservation target (DFC10-PT10) versus a 1% deforestation curve with a 10% preservation target (DFC1-PT10). During active deforestation, albedo, net radiation, latent heat flux, and climate variables were compared for time dependence and sensitivity to tropical tree cover across the tropical band and the Amazon basin, central African, and Southeast Asian regions. The results demonstrated the feasibility of modeling incremental deforestation and detecting both transient and long-term impacts, although a warm/dry bias in CCSM3–DGVM and the absence of carbon feedbacks preclude definitive conclusions on the magnitude of sensitivities. The deforestation rates produced characteristic trends in biophysical variables with DFC10-PT10 resulting in rapid increase/decrease during the initial 10–30 years before leveling off, whereas DFC1-PT10 exhibits gradual changes. The rate had little effect on biophysical and climate sensitivities when averaged over tropical land but produced significant differences at a regional level. Over the long term, the rates produced dissimilar vegetation distributions, despite having the same preservation target in both cases. Overall, these results indicate that the question of rates is one worth further analysis.

scholarly journals A Sensitivity Analysis of Surface Biophysical, Carbon, and Climate Impacts of Tropical Deforestation Rates in CCSM4-CNDV*

2013 ◽  
Vol 26 (3) ◽  
pp. 805-821 ◽  
Author(s):  
C. Kendra Gotangco Castillo ◽  
Kevin Robert Gurney
Keyword(s):  
Southeast Asia ◽  
Amazon Basin ◽  
Central Africa ◽  
Tropical Deforestation ◽  
Climate Impacts ◽  
Sensitivity Analyses ◽  
Tree Cover ◽  
Climate System Model ◽  
Deforestation Rates ◽  
Precipitation Decrease

Abstract The biophysical–climate and combined biophysical and carbon–climate feedbacks of tropical deforestation rates are explored through sensitivity analyses using the Community Climate System Model 4 with prognostic carbon–nitrogen and dynamic vegetation. Simulations test 5%, 2%, 1%, and 0.5% annual deforestation rates, each paired with preservation targets of 10% per tropical tree type. Perturbations are applied over pan-tropical land but analyses also investigate responses over the subcontinental areas of the Amazon basin, central Africa, and Southeast Asia. Sensitivities [expressed as the change in a variable per million square kilometers (Mkm2) of change in tree cover] and means of selected biophysical, carbon, and climate variables during and after deforestation are compared across rates. The most apparent effect of the rates is in hastening/postponing climate change, but otherwise results show no consistent differences across rates and vary more across subcontinents (with the Amazon basin reflecting highest sensitivities in albedo and ground temperatures, and Southeast Asia for total ecosystem carbon). Additionally, biophysical feedbacks alone were found to have significant impact on climate over subcontinental scales. In the Amazon, ground temperature increase due to biophysical feedbacks is as much as 55%, and precipitation decrease up to 61%, of combined biophysical and carbon impacts. Replication with other models is required. Although it is still unclear whether a slow but prolonged deforestation differs in impacts from one that is rapid but short, the rate can still be relevant to planning with regards to the timing of impacts.

scholarly journals Species distribution modeling and conservation assessment of the black-headed night monkey (Aotus nigriceps) – A species of Least Concern that faces widespread anthropogenic threats

2020 ◽  
Author(s):  
William D. Helenbrook ◽  
Jose W. Valdez
Keyword(s):  
Protected Areas ◽  
Species Distribution ◽  
Amazon Basin ◽  
Forest Cover ◽  
Indigenous Communities ◽  
Sympatric Species ◽  
Tree Cover ◽  
Conservation Assessment ◽  
Buffer Zones ◽  
Deforestation Rates

AbstractDeforestation rates in the Brazilian Amazon have been steadily increasing since 2007. Recent government policy, projected growth of agriculture, and expansion of the cattle industry is expected to further pressure primates within the Amazon basin. In this study, we examined the anthropogenic impact on the widely distributed black-headed night monkey, Aotus nigriceps, whose distribution and population status have yet to be assessed. We 1) modeled species distribution in A. nigriceps; 2) estimated impact of habitat loss on population trends; and 3) highlight landscape-based conservation actions which maximize potential for their long-term sustainability. We found the black-headed night monkey to be restricted by several biotic and environmental factors including forest cover, elevation, isothermality, and precipitation. Over the last two decades, over 132,908 km2 of tree cover (18%) has been lost within their documented range. We found this species occupies only 49% of habitat within in their range, a loss of 19% from their estimated 2000 distribution, and just over 34% of occupied areas were in protected areas. Projected deforestation rates of A. nigriceps equates to an additional loss of 23,084 km2 of occupied habitat over the next decade. This study suggests that although classified as a species of Least Concern, A. nigriceps may have a much smaller range and is likely more at risk than previously described. The future impact of continued expansion of mono-cultured crops, cattle ranching, and wildfires is still unknown. However, expanded use of participatory REDD+, sustainable agroforestry in buffer zones, secured land tenor for indigenous communities, wildlife corridors, and the expansion of protected areas can help ensure viability for this nocturnal primate and other sympatric species throughout the Amazon Basin.

scholarly journals Climate change will cause non-analog vegetation states in Africa and commit vegetation to long-term change

2020 ◽  
Vol 17 (22) ◽  
pp. 5829-5847
Author(s):  
Mirjam Pfeiffer ◽  
Dushyant Kumar ◽  
Carola Martens ◽  
Simon Scheiter
Keyword(s):  
Vegetation Change ◽  
Structural Changes ◽  
Equilibrium States ◽  
Tree Cover ◽  
Environmental Drivers ◽  
Vegetation Model ◽  
Dynamic Global Vegetation Model ◽  
Lag Times ◽  
Over Time

Abstract. Vegetation responses to changes in environmental drivers can be subject to temporal lags. This implies that vegetation is committed to future changes once environmental drivers stabilize; e.g., changes in physiological processes, structural changes, and changes in vegetation composition and disturbance regimes may happen with substantial delay after a change in forcing has occurred. Understanding the trajectories of such committed changes is important as they affect future carbon storage, vegetation structure, and community composition and therefore need consideration in conservation management. In this study, we investigate whether transient vegetation states can be represented by a time-shifted trajectory of equilibrium vegetation states or whether they are vegetation states without analog in conceivable equilibrium states. We use a dynamic vegetation model, the aDGVM (adaptive Dynamic Global Vegetation Model), to assess deviations between simulated transient and equilibrium vegetation states in Africa between 1970 and 2099 for the RCP4.5 and 8.5 scenarios using regionally downscaled climatology based on the MPI-ESM output for CMIP5. We determined lag times and dissimilarity between simulated equilibrium and transient vegetation states based on the combined difference of nine selected state variables using Euclidean distance as a measure for that difference. We found that transient vegetation states over time increasingly deviated from equilibrium states in both RCP scenarios but that the deviation was more pronounced in RCP8.5 during the second half of the 21st century. Trajectories of transient vegetation change did not follow a “virtual trajectory” of equilibrium states but represented non-analog composite states resulting from multiple lags with respect to vegetation processes and composition. Lag times between transient and most similar equilibrium vegetation states increased over time and were most pronounced in savanna and woodland areas, where disequilibrium in savanna tree cover frequently acted as the main driver of dissimilarities. Fire additionally enhanced lag times and dissimilarity between transient and equilibrium vegetation states due to its restraining effect on vegetation succession. Long lag times can be indicative of high rates of change in environmental drivers, of meta-stability and non-analog vegetation states, and of augmented risk for future tipping points. For long-term planning, conservation managers should therefore strongly focus on areas where such long lag times and high residual dissimilarity between most similar transient and equilibrium vegetation states have been simulated. Particularly in such areas, conservation efforts need to consider that observed vegetation may continue to change substantially after stabilization of external environmental drivers.

scholarly journals Evidence that a national REDD+ program reduces tree cover loss and carbon emissions in a high forest cover, low deforestation country

2019 ◽  
Vol 116 (49) ◽  
pp. 24492-24499 ◽  
Author(s):  
Anand Roopsind ◽  
Brent Sohngen ◽  
Jodi Brandt
Keyword(s):  
Forest Cover ◽  
Forest Degradation ◽  
Tree Cover ◽  
Forest Protection ◽  
Forest Policies ◽  
Deforestation Rates ◽  
Climate Change Mitigation Policy ◽  
Implementation Period ◽  
Rich Countries ◽  
The Impact

Reducing emissions from deforestation and forest degradation (REDD+) is a climate change mitigation policy in which rich countries provide payments to developing countries for protecting their forests. In 2009, the countries of Norway and Guyana entered into one of the first bilateral REDD+ programs, with Norway offering to pay US$250 million to Guyana if annual deforestation rates remained below 0.056% from 2010 to 2015. To quantify the impact of this national REDD+ program, we construct a counterfactual times-series trajectory of annual tree cover loss using synthetic matching. This analytical approach allows us to quantify tree cover loss that would have occurred in the absence of the Norway-Guyana REDD+ program. We found that the Norway-Guyana REDD+ program reduced tree cover loss by 35% during the implementation period (2010 to 2015), equivalent to 12.8 million tons of avoided CO2 emissions. Our analysis indicates that national REDD+ payments attenuated the effect of increases in gold prices, an internationally traded commodity that is the primary deforestation driver in Guyana. Overall, we found strong evidence that the program met the additionality criteria of REDD+. However, we found that tree cover loss increased after the payments ended, and therefore, our results suggest that without continued payments, forest protection is not guaranteed. On the issue of leakage, which is complex and difficult to quantify, a multinational REDD+ program for a region could address leakage that results from differences in forest policies between neighboring countries.

Investigating the impact of different drought-heat signatures on carbon dynamics using a dynamic global vegetation model

2020 ◽  
Author(s):  
Elisabeth Tschumi ◽  
Sebastian Lienert ◽  
Karin van der Wiel ◽  
Fortunat Joos ◽  
Jakob Zscheischler
Keyword(s):  
Carbon Cycle ◽  
Heat Waves ◽  
Carbon Dynamics ◽  
Climate Forcing ◽  
Carbon Uptake ◽  
Climate Variables ◽  
Vegetation Model ◽  
Dynamic Global Vegetation Model ◽  
Global Vegetation

<p><span>Droughts and heat waves have large impacts on the terrestrial carbon cycle. They lead to reductions in gross and net carbon uptake or anomalous increases in carbon emissions to the atmosphere because of responses such as stomatal closure, hydraulic failure and vegetation mortality. The impacts are particularly strong when drought and heat occur at the same time. Climate model simulations diverge in their occurrence frequency of compound hot and dry events, and it is unclear how these differences affect carbon dynamics. Furthermore, it is unknown whether an increase in frequency of droughts and heat waves leads to long-term changes in carbon dynamics, and how such an increase might affect vegetation composition.</span></p><p><span>To study the immediate and long-term effects of varying signatures of droughts and heat waves on carbon dynamics such as inter-annual variability of carbon fluxes and cumulative carbon uptake, we employ the state-of-the-art dynamic global vegetation model LPX-Bern (v1.4) under different drought-heat scenarios.</span></p><p><span>We have constructed five 100-yr long scenarios with different drought-heat signatures, representing a “control”, “close to mean seasonal cycle”, “drought only”, “heat only”, and “compound drought and heat” climate forcing to LPX-Bern. This is done by sampling daily climate variables from a 2000-year stationary simulation of a General Circulation Model (EC-Earth) for present-day climate conditions. Such a sampling ensures physically-consistent co-variability between climate variables in the climate forcing.</span></p><p><span>We investigate the carbon-cycle response and changes in vegetation structure to different drought-heat signatures on a global grid, representing different land cover types and climate zones. Our results provide a better understanding of the links between hot and dry conditions and carbon dynamics. This may help to reduce uncertainties in carbon cycle projections, which is important for constraining carbon cycle-climate feedbacks.</span></p>

scholarly journals A long-term perspective on deforestation rates in the Brazilian Amazon

2015 ◽  
Vol XL-7/W3 ◽  
pp. 539-544 ◽  
Author(s):  
M. D. Velasco Gomez ◽  
R. Beuchle ◽  
Y. Shimabukuro ◽  
R. Grecchi ◽  
D. Simonetti ◽  
...  
Keyword(s):  
Land Cover ◽  
Forest Cover ◽  
Brazilian Amazon ◽  
Thematic Mapper ◽  
Tree Cover ◽  
Amazon Forest ◽  
Forest Cover Change ◽  
Visual Interpretation ◽  
Deforestation Rates ◽  
Arc Of Deforestation

Monitoring tropical forest cover is central to biodiversity preservation, terrestrial carbon stocks, essential ecosystem and climate functions, and ultimately, sustainable economic development. The Amazon forest is the Earth’s largest rainforest, and despite intensive studies on current deforestation rates, relatively little is known as to how these compare to historic (pre 1985) deforestation rates. We quantified land cover change between 1975 and 2014 in the so-called Arc of Deforestation of the Brazilian Amazon, covering the southern stretch of the Amazon forest and part of the Cerrado biome. We applied a consistent method that made use of data from Landsat sensors: Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI). We acquired suitable images from the US Geological Survey (USGS) for five epochs: 1975, 1990, 2000, 2010, and 2014. We then performed land cover analysis for each epoch using a systematic sample of 156 sites, each one covering 10 km × 10 km, located at the confluence point of integer degree latitudes and longitudes. An object-based classification of the images was performed with five land cover classes: tree cover, tree cover mosaic, other wooded land, other land cover, and water. The automatic classification results were corrected by visual interpretation, and, when available, by comparison with higher resolution imagery. Our results show a decrease of forest cover of 24.2% in the last 40 years in the Brazilian Arc of Deforestation, with an average yearly net forest cover change rate of -0.71% for the 39 years considered.

scholarly journals The role of tectonic uplift, climate and vegetation in the long-term terrestrial phosphorous cycle

2010 ◽  
Vol 7 (1) ◽  
pp. 301-333 ◽  
Author(s):  
C. Buendía ◽  
A. Kleidon ◽  
A. Porporato
Keyword(s):  
Steady State ◽  
Amazon Basin ◽  
Atmospheric Transport ◽  
Tectonic Uplift ◽  
P Availability ◽  
Ecosystem Productivity ◽  
Terrestrial Biosphere ◽  
Global Vegetation ◽  
P Cycle

Abstract. Phosphorus (P) is a crucial element for life and therefore for maintaining ecosystem productivity. Its local availability to the terrestrial biosphere results from the interaction between climate, tectonic uplift, atmospheric transport and biotic cycling. Here we present a mathematical model that describes the terrestrial P-cycle in a simple but comprehensive way. The resulting dynamical system can be solved analytically for steady-state conditions, allowing us to test the sensitivity of the P-availability to the key parameters and processes. Given constant inputs, we find that humid ecosystems exhibit lower P availability due to higher runoff and losses, and that tectonic uplift is a fundamental constraint. In particular, we find that in humid ecosystems the biotic cycling seem essential to maintain long-term P-availability. The time-dependent P dynamics for the Franz Josef and Hawaii chronosequences show how tectonic uplift is an important constraint on ecosystem productivity, while hydroclimatic conditions control the P-losses and speed towards steady-state. The model also helps describe how with limited uplift and atmospheric input, as in the case of the Amazon Basin, ecosystems must rely on mechanisms that enhance P-availability and retention. Our analysis underlines the need to include the P cycle in global vegetation-atmosphere models for a reliable representation of the response of the terrestrial biosphere to global change.

scholarly journals Variable tree rooting strategies improve tropical productivity and evapotranspiration in a dynamic global vegetation model

2020 ◽  
Author(s):  
Boris Sakschewski ◽  
Werner von Bloh ◽  
Markus Drüke ◽  
Anna A. Sörensson ◽  
Romina Ruscica ◽  
...  
Keyword(s):  
Forest Cover ◽  
Soil Depth ◽  
Belowground Biomass ◽  
Rooting Depth ◽  
Dynamic Global Vegetation Model ◽  
Study Region ◽  
Climate Conditions ◽  
Annual Productivity ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Tree water access via roots is crucial for forest functioning and therefore forests have developed a vast variety of rooting strategies across the globe. However, Dynamic Global Vegetation Models (DGVMs), which are increasingly used to simulate forest functioning, often condense this variety of tree rooting strategies into biome-scale averages, potentially under- or overestimating forest response to intra- and inter-annual variability in precipitation. Here we present a new approach of implementing variable rooting strategies and dynamic root growth into the LPJmL4.0 DGVM and apply it to tropical and sub-tropical South-America under contemporary climate conditions. We show how competing rooting strategies which underlie the trade-off between above- and below-ground carbon investment lead to more realistic simulated intra-annual productivity and evapotranspiration, and consequently forest cover and spatial biomass distribution. We find that climate and soil depth determine a spatially heterogeneous pattern of mean rooting depth and belowground biomass across the study region.

scholarly journals Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

2020 ◽  
Vol 12 (19) ◽  
pp. 3226
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Area ◽  
Tree Cover ◽  
Agricultural Crop ◽  
Forest Change ◽  
Alos Palsar ◽  
Tropical Regions ◽  
The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

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