• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    Carbon stocks in a highly fragmented landscape with seasonally dry tropical forest in the Neotropics

    2022-06-10 07:34:48MesaSierraLabordeChaplinKramerEsobar
    Forest Ecosystems 2022年2期

    N. Mesa-Sierra, J. Laborde, R. Chaplin-Kramer, F. Esobar

    a Instituto Tecnol′ogico y de Estudios Superiores de Occidente,Centro Interdisciplinario para la Formaci′on y Vinculaci′on Social,Perif′erico Sur Manuel G′omez Morín 8585,45604, Tlaquepaque, Jalisco, Mexico

    b Gnosis - Naturaleza con ciencia, A.C., Lorenzo Barcelata 5101, 45239, Guadalajara, Jalisco, Mexico

    c Instituto de Ecología, A. C., Ecología Funcional, Carretera Antigua a Coatepec 351, El Haya, 91073, Xalapa, Veracruz, Mexico

    d Natural Capital Project, Woods Institute for the Environment, Stanford University, 327 Campus Drive, Stanford, CA, 94305, USA

    e Institute on the Environment, University of Minnesota, 1954 Buford Ave, St. Paul, Minnesota, 55108, USA

    f Instituto de Ecología, A.C., Ecoetología, Carretera Antigua a Coatepec 351, El Haya, 91073, Xalapa, Veracruz, Mexico

    Keywords:Seasonally dry tropical region Ecosystem services Carbon sequestration Human modified landscapes Climate change mitigation

    ABSTRACT Background:Global modeling of carbon storage and sequestration often mischaracterizes unique ecosystems such as the seasonally dry tropical forest of the central region of the Gulf of Mexico,because species diversity is usually underestimated, as is their carbon content. In this study, aboveground and soil carbon stocks were estimated to determine the climate mitigation potential of this highly degraded landscape (<25% of forest cover).Results: Tree species in the study area had carbon content values that were 30%–40% higher than the standard value proposed by the IPCC(i.e.,50%).Tropical oak forest in the region,despite its restricted distribution and low species richness, accounted for the highest mean carbon stocks per unit area. The main factors driving spatial variability in carbon stocks were: maximum precipitation, soil organic matter, clay and silt content. No strong relationship was found between aboveground carbon stocks and soil organic carbon in the study area. Quantification of carbon stocks is an important consideration in the assessment of the conservation value of remnants of native vegetation in human-modified landscapes.Conclusions: This study demonstrates the importance of the highly fragmented tropical dry regions of the Neotropics in maintaining landscape functionality and providing key ecosystem services such as carbon sequestration.Our results also highlight how crucial field-based studies are for strengthening the accuracy of global models.Furthermore,this approach reveals the real contribution of ecosystems that are not commonly taken into account in the mitigation of climate change effects.

    1. Background

    Global trends in biodiversity conservation and ecosystem services in terrestrial ecosystems continue to be negative, caused in part by drastic climatic and environmental changes(e.g.,greater frequency and impact of hurricanes,presence of novel viruses) that also threaten human wellbeing(Soto-Navarro et al.,2020).Recent commitments to avert climate change, made by governments and businesses at the local and international levels, have generated policy mechanisms and funding for nature-based climate solutions such as carbon sequestration payments.As the uptake of such strategies increases, information regarding the carbon sequestration potential of different landscapes is urgently needed,so their contribution can be accurately assessed and appropriate incentives set.There is a growing consensus regarding the need to generate national policies aimed at the local implementation of actions to achieve the global goals set forth in intergovernmental agendas. Given the current rates of emission and the fact that some of the greenhouse gases remain in the atmosphere for hundreds of years,it is necessary to design and implement corrective actions on suitable time scales to ensure successful mitigation (Anderegg et al., 2020). Terrestrial ecosystems,particularly forest,are among the most important contributors needed to meet the goals set in the global agreements(e.g.,Paris Agreement,Bonn Challenge)recognized by several countries(Chazdon et al.,2016;Bastin et al., 2019; Soto-Navarro et al., 2020; Anderegg et al., 2020; Heilmayr et al.,2020).It has been estimated that strategies based on the protection of forests can help to sequester approximately 7 Pg CO2e per year by 2030(Anderegg et al.,2020),however these estimates are usually based on temperate forest assessments or on satellite information at very coarse scales and are therefore limited. Information obtained at the local level from actual landscapes is essential to design plans tailored to each landscape's context and local anthropic pressures.This information could ultimately be incorporated into local and national policies and help build more accurate global models.

    Today, most landscapes worldwide have been modified by anthropogenic activities such as urbanization, agriculture, tourism, infrastructure development, mining, and others that seriously threaten their dynamics and long-term function (Melo et al., 2013; Chazdon, 2014;IPBES et al., 2019; WWF, 2020). Understanding and quantifying the resulting changes in biogeochemical processes(e.g.,nutrient flow in soil)are critical for the reliable assessment of all the consequences of land-use and land cover change to landscape functionality(i.e.,the capacity of the landscape to provide services by maintaining ecosystem functions). It is known that environmental variables that are susceptible to climate change,such as temperature,precipitation,soil moisture,and pH,among others, may have a strong influence on the process of carbon sequestration and thus,should be incorporated into climate mitigation assessments(Jaramillo et al.,2003;Ibrahim et al.,2006;Corona-Nú~nez et al.,2018).Assessing and monitoring carbon stocks over time is critical to designing effective landscape management plans and conservation strategies to enhance carbon sequestration in human-modified landscapes.

    Most research and policy development efforts in the tropics have focused on humid ecosystems such as tropical rain forests and mangroves, with less attention to other tropical vegetation types, such as tropical dry forest(Stoner and S′anchez-Azofeifa,2009;Portillo-Quintero et al., 2015; Corona-Nú~nez et al., 2018). The latter, also known as seasonally dry tropical forest(SDTF,sensu Pennington et al.,2009),is the most widely distributed type of forest cover in the tropics,accounting for approximately 42%of tropical forest worldwide(Pennington et al.,2009;Dirzo, 2011; Banda et al., 2016). It is found in areas where the mean annual temperature is 17 to 26°C and annual precipitation 250 to 2,000 mm.As its name implies,this type of tropical forest is highly seasonal.Its growing season only lasts five to seven months of the year (Jaramillo et al.,2003).Some traits(e.g.,leaf area)of the dominant species in these forests allow the trees to have efficient systems for nutrient fixation, to exploit limited resources and to ensure the growth of their foliage and wood (Powers and Tiffin, 2010). In the Americas, this forest type is distributed from Mexico to northern Argentina,including the Caribbean islands, and it is regarded as one of the most threatened terrestrial ecosystems in the world due to the expansion of human activities (Dirzo,2011). A greater proportion of SDTF has been degraded or transformed than that of tropical rain forest,with less than 10%of the original cover of Neotropical SDTF remaining (Jaramillo et al., 2003; Banda et al.,2016).The available information on current and potential carbon storage of SDTF is scarce when compared to that of humid tropical forests(Corona-Nú~nez et al.,2018).

    Currently,Mexico retains 25%to 36%of its original SDTF—the vast majority of which is relatively young secondary vegetation—and this is a larger proportion of the original SDTF cover than remains in the rest of the Neotropics (Jaramillo et al., 2003; L′opez-Barrera et al., 2014).Seasonally dry tropical regions in Mexico are located on the Pacific Slope,in the northwestern region of the Yucatan Peninsula and the central part of the Gulf of Mexico coast in the state of Veracruz. Assessments of the carbon stocks in Mexican SDTF have focused on the first two regions,while the carbon storage potential of the Gulf of Mexico remains largely unknown, though there is some information in government reports. In this region, less than 25% of the original cover of SDTF remains today(Mesa-Sierra, 2020), making its conservation and the assessment of its carbon stocks a crucial and urgent task.The latter is especially critical if climate mitigation policy and funding are to be used as leverage for securing the protection of the remaining SDTF in this region.

    Here,we characterize the potential climate-mitigation value of SDTF in Veracruz, by: i) estimating the basal area of different types of oldgrowth and secondary forest present within the region, ii) estimating the carbon stored in each forest type, both aboveground (in the vegetation)and in the soils, and iii) evaluating which environmental variables are related to the spatial variation of the aboveground and soil organic carbon stocks.The aim is to provide solid quantitative information that is urgently needed for the reliable assessment of the carbon storage potential of the different types of SDTF still present in this highly transformed and populated region.This is crucial for designing management programs and policies aimed at maximizing carbon stocks,and therefore climate change mitigation in human-modified landscapes in the tropics,by incorporating spatial heterogeneity into the priorities for protecting the remaining well-preserved forest and the restoration or natural regeneration of secondary forest.

    The seasonally dry tropical region of the Gulf of Mexico is located in the central part of the state of Veracruz. It is distributed from the lowlands of the Manuel Díaz mountain range that extends down to and is perpendicular to the Atlantic coast and extends southwards along the coastalplain endingbetweenthecityofCardeland thePuente Nacional zone,from 19°16′55′′to19°48′16′′Nandfrom96°19′13′′to 96°48′48′′W (Fig. 1). The region's weather is classified as AW2, characterized by marked seasonality in its rainfall regime.During five to eight months of the year, precipitation is very low compared to that of other regions in the tropics that are more humid and less seasonal(García,2004). Mean annual temperature is 22–26°C,and mean annual rainfall is 1,200 to 1,15,05000 m mmm(Travieso-Bello and Campos,2006).Ten different types of soils have been found in the region (Travieso-Bello and Campos, 2006),including: obrist histosols, cambid aridisols and mollic gleysols(FAO/UNESCO classification).

    2. Materials and methods

    2.1. Study area

    2.2. Vegetation types and aboveground carbon

    Based on a previous analysis of land cover using SPOT5 images from 2014 and intense field verification(Mesa-Sierra et al.,2020a,2020b),ten sampling sites with forest cover that were at least 1 km apart were selected for sampling across the study area (approximately 1,100 km2).In each of these 10 sites an area of 600 by 600 m (36 ha) with forest patches inside was delimited. All forest patches >1 ha present within these ten sites, were sampled, totaling 29 forested patches (Fig. 1). All forest patches sampled had a stand-age equal to or greater than five years.

    Three 50 m×20 m parallel belt-transects were set up(at least 20 m apart) within each of the 29 patches (87 transects in total). All woody plants with a DBH ≥5 cm and rooted within the transects were identified to the species or genus level and their DBH was measured during January and September 2016.Along the central line of each transect,the height of the canopy was measured every 5 m in order to generate a vertical profile of the canopy.Following Mesa-Sierra et al.(2020a),six types of forested vegetation were distinguished based on species composition and physiognomy: three old-growth forest types, tropical oak forest (TOF),low-statured deciduous forest (LWF), semi-deciduous forest (SDF), and three secondary forest types (with SDF cover before disturbance), late secondary forest (LSF; > 20 years old), intermediate secondary forest(ISF;10–20 years old)and early secondary forest(ESF;5–10 years old).

    Fig.1. Study area location in the seasonally dry tropical region of the Gulf of Mexico,Veracruz,Mexico.The distribution of tropical dry forest ecosystems in Mexico is shown(gray),in the upper left inset.The locations of the ten sampling sites(A–J)are shown and for each site all of the forest patches sampled are drawn,numbered from 1 to 29 (bottom right). Vegetation types (defined in Mesa-Sierra et al., 2020a) include: three old-growth forest types: Tropical Oak Forest (TOF); Low-statured Deciduous Forest (LWF) and Semi-Deciduous Forest (SDF); and three secondary forest (SF) types: Late SF (LSF); Intermediate SF (ISF) and Early SF (ESF).

    For this study 29 tree species were selected to extract woody samples and assess their carbon content(Table S1).The species selected included those with the highest importance value index (IVI) in each vegetation type (i.e., dominant species per type), and were a subset of the 157 species recorded in vegetation sampling(Mesa-Sierra et al.,2020a).This index allowed us to select species based on their relative frequency,relative density, and relative dominance and ensure that they were a representative sample of the trees recorded. Wood samples of the dominant species were extracted from the trunk of three individuals with DBH >10 cm in each sampled patch, using a Hagl¨of borer with a 10”penetration depth. Samples were only taken from stem wood; the other parts of the trees were not sampled (e.g., branches). The samples were dried at a constant temperature of 37°C for at least 24 h and then a standardized sub-sample of one cubic centimeter was obtained from each field sample. Next, these 1 cm3samples were burned for 4 h in a high-temperature oven at 550°C.After the temperature had decreased to below 100°C,the samples were weighed again to determine the weight loss in grams after drying, which represents the organic carbon content(%) in the sample (sensu SARE, 2012). For wood density, different databases (Brown, 1997; Zanne et al., 2009; Harja et al., 2010; Ord′o~nez Díaz et al.,2015)were reviewed to obtain information for each of the 29 species. For those species that did not have specific information, the densities reported specifically in tropical areas for the genus were averaged. This information was used to estimate the aboveground biomass(AGB)for each of the species by forest patch,which was calculated using the model proposed by Chave et al.(2005)for dry forest:

    where ρ is wood density(t?m-3),D is the diameter at breast height(cm)and H is mean canopy height (m). Finally, to assess the aboveground carbon content per species(AGCs)of the dominant species in each forest patch, biomass was multiplied by percent carbon for each one (FAO,2011; Petrokofsky et al., 2012). Therefore, the aboveground carbon content per sampled patch (AGCp) was assessed by adding the AGCs values of the selected species that were present within the patch,and this was extrapolated to express the value per hectare.These values were,in turn, summed to obtain a value for the aboveground carbon content by vegetation type(AGCvt).

    2.3. Soil organic carbon

    Along each of the vegetation transects, soil samples were collected every 15 m.Each sample consisted of 300 g of soil extracted from an area of 100 cm2from the top 10 cm of mineral soil(excluding the litter layer),and were subsequently mixed to obtain a single combined soil sample per transect(3 samples per forest patch).These samples were dried at room temperature for approximately 24 h, ground and processed in the Soil Laboratory at the Instituto de Ecología, A.C. to determine: bulk density(t?m-3), organic carbon (OC), organic matter (OM), pH, and sand, clay and silt content,following standard procedures(Dane et al.,2002;Sparks et al.,2020).To estimate the soil organic carbon(SOC)stock(t C?ha-1)for each vegetation type and sampled patch, we multiplied organic carbon(%),by the bulk density(g?cm-3)and the depth at which the samples were taken(i.e.,10 cm),multiplied by the area sampled and extrapolated to get an estimate per hectare(Griffin et al.,2013).

    2.4. Data analyses

    Carbon content values were compared among the patches of the vegetation types with Generalized Linear Models (GLMs), using a negative-binomial error type due to the overly dispersed nature of the data.When significant differences were found,a post hoc test(Tukey)was used to determine which vegetation types were different. We also assessed the variation in carbon content among the three secondary vegetation forest types defined in this study(LSF,ISF and ESF)to analyze the temporal turnover of carbon accumulation during these successional stages.

    We performed Ordinary Least Squares (OLS) regressions to explore the relationship between each of the carbon values(AGC and SOC),and different variables per forest patch that summarized the heterogeneity of the 29 patches, including environmental variables and vegetation attributes (i.e., basal area, plant richness and abundance). Environmental variables per forest patch (Table S2) included maximum annual temperature(°C),mean annual precipitation(mm?year-1),maximum annual precipitation (mm), elevation (m a.s.l.), slope (°), soil pH, soil organic carbon(%),soil organic matter(%),and soil content of sand,clay and silt(%). To meet the assumptions for OLS regressions, we tested for normality. Climate variables (maximum annual temperature, mean annual and maximum annual precipitation) were extracted from the high-resolution(30-arc sec;approx.90 m per pixel)climate surfaces for Mexico(Cuervo-Robayo et al., 2014), and topographic variables(elevation, slope, and aspect)were obtained from a national Digital Elevation Model(DEM)of the study area with a resolution of 25 m per pixel(INEGI,2009).OLS regression analysis was also used to determine if the AGC and SOC stocks per patch were related.All statistical analyses were run in R(R Development Core Team,2019).

    3. Results

    3.1. Basal area

    The basal area was 106.4 m2in a total sampling area of 87,000 m2(12.2 m2?ha-1),represented by 6,007 plants belonging to 157 species of woody species and 113 genera. Of all the species recorded, 29 were dominant in at least one of the six forest types in the study area,based on their IVI values in each forest type (see Table S1). These species represented 18.5% of total plant richness in the vegetation sampling, but together accounted for 60%of the total abundance and 64%of total basal area(see Supplemental section 1 and Mesa-Sierra et al.,2020a).

    3.2. Carbon stocks

    3.2.1. Aboveground

    In a sample area of 8.7 ha within the study area,the remaining forest vegetation,both old-growth and secondary forest,stores>272 t C,with an average value of 9.4±6.5 t C?ha-1(±s.d.)per patch(N =29 patches).Tropical oak forest (TOF) had the highest AGC, with one of its patches>23 t C?ha-1. There were significant differences among the mean AGC values per forest type (χ2=44.97; d.f. =5; P < 0.05), mainly between TOF and the other forest types(Fig.2).The lowest value was recorded for early secondary forest (ESF). TOF had the lowest variation among the patches in terms of AGC values(Fig.2).

    Overall,wood density varied between 0.30 and 0.97 t?m-3(Table 1)among the species analyzed. Carbon content values in the wood were 73.5%–99.5%.The five species with the highest percent carbon(≥98%)were Cestrum racemosum, Mirandaceltis monoica, Quercus sapotifolia,Caesalpinia cacalaco and Senna atomaria, while those with the lowest carbon values (<85%) were Gliricidia sepium, Guazuma ulmifolia, Nectandra salicifolia and Erythrina americana (Table 1). Some species had a remarkably high intra-specific variation in percent carbon,as revealed by extremely high coefficient of variation values (CV), particularly for Gliricidia sepium (CV =49%), Erythrina americana (31%), Nectandra salicifolia(38%)and Guazuma ulmifolia(26%),while the CV of all the other species analyzed was lower than 5% (with the exception of Cedrela odorata;10%).

    When the aboveground carbon content was analyzed within the different types of secondary forest whose successional age(from Early to Late)could be regarded as a chronosequence,turnover in the species that stored the most carbon was observed.The species that made the greatest contribution to carbon stocks were Acacia pennatula in the Early Secondary Forest,Gliricidia sepium in Intermediate Secondary Forest and Mirandaceltis monoica in Late Secondary Forest (Fig. 3). Likewise, individual species exhibited their highest values of carbon storage at different successional stages.For example,the highest AGC values were found for Leucaena leucocephala in Late Secondary Forest (LSF), for Guazuma ulmifolia in Intermediate Secondary Forest(ISF),and for Bursera simaruba in Early Secondary Forest(ESF;Fig.3).

    3.2.2. Soil

    For soil organic carbon stocks in the study area, the mean value of carbon stored in the forest patches sampled was 11.12 ± 7.92 t C?ha-1(±s.d.) per patch (N =29 patches). There were five patches whose soil organic carbon(SOC)content surpassed 20,000 t C?ha-1:the tropical oak forest(TOF)patches and two of the late secondary forest(LSF)patches.TOF had the highest mean SOC value,and LSF had the highest variation in SOC content per patch (CV =89%). SOC stock differed among forest types(χ2=38.3;d.f.=5;P<0.001),especially between TOF compared to SDF,ISF and ESF(Fig.4).

    3.3. Environmental variables related with carbon stocks

    3.3.1. Aboveground

    The variables that best explained the variation in carbon content per patch were soil attributes. None of the topographic or climate variables had a significant influence (Table S3) on the AGC values. The strongest positive relationships with the AGC values were with organic matter and organic carbon in the soil (Fig. 5a and b). Weaker relationships were found with the clay content of the soil,which was negative,and the sand content of the soil,positive(Fig.5c and d).

    3.3.2. Soil

    Of all the environmental variables analyzed (Table S2), three were significantly related to the SOC stock per patch. Forest patches with a high proportion of organic matter in the soil (Fig. 6a) or with a higher number of individuals(Fig.6c),had a higher SOC stock,though this last relationship was weak. In contrast, for forest patches with the highest values of maximum annual precipitation, the SOC values were below 10,000 t C?ha-1(Fig.6b).

    Fig. 2. Mean aboveground carbon stock (t C?ha-1 ± s.d.) per forest type, estimated from the dominant species of each forest type(see Methods).Forest types are: Tropical Oak Forest (TOF), Low-statured Deciduous Forest (LWF), Semideciduous Forest (SDF), Late Secondary Forest (LSF), Intermediate Secondary Forest (ISF) and Early Secondary Forest (ESF). Different letters indicate significant differences between forest types (Tukey test; P < 0.05).

    Table 1 Summary of percent carbon(%)and wood density(t?m-3)for each of the 29 species sampled(n =3 individuals per species),as well as their stem volume(m3?ha-1)in each forest type where they were found.Forest types:Tropical Oak Forest(TOF),Low-statured Deciduous Forest(LWF),Semi-deciduous Forest(SDF),Late Secondary Forest (LSF), Intermediate Secondary Forest (ISF) and Early Secondary Forest (ESF).

    Finally, contrary to expectation, there was not a strong relationship between aboveground(AGC)and soil(SOC)carbon stocks per patch(R2=0.311; P =0.002). Extremely high and contrasting spatial variability were found for these two variables; some of the sampled patches with high values of AGC had a very low SOC content,while others with a very high SOC content had an extremely low AGC content (see Table S2;patches #13 for the first case,and#1,27 for the second).

    4. Discussion

    4.1. Aboveground carbon storage

    The plant species associated with seasonally dry tropical forest are characterized by different growth forms that have great physiological plasticity, which allows them to adapt to different conditions and overcome the prolonged periods of drought that are typical of this ecosystem(Williams-Linera and Lorea,2009;Alvarez-Aquino and Williams-Linera,2012; Chaturvedi et al., 2018). Some of the traits (e.g., leaf area) of dominant species in these forests allow the trees to have efficient systems for nutrient fixation,to exploit limited resources and ensure the growth of their foliage and wood (Powers and Tiffin, 2010). In this study, we found that the dominant tree species (i.e., greater IVI) of the seasonally dry tropical region of the Gulf of Mexico are highly capable of fixing carbon in their trunks, with carbon content values (up to 99%) that are higher than those recorded in other dry Neotropical regions(47%–50%;Chave et al., 2009; Schmitt-Harsh et al., 2012; Gonz′alez C′asares et al.,2017;Corona-Nú~nez et al.,2018).Twenty-five of the twenty-nine species studied had carbon content values higher than 90%, while only two species had values lower than 85%.

    Fig. 3. Total carbon stock (t C?ha-1) for the 15 dominant species in the three types of secondary forest (i.e., different successional stages): Late Secondary Forest (LSF), Intermediate Secondary Forest (ISF) and Early Secondary Forest (ESF).

    Fig. 4. Soil organic carbon stock (t C?ha-1) in each forest type. Mean and standard deviation (vertical lines) are shown. Old-growth forest types: Tropical Oak Forest(TOF),Low-statured Deciduous Forest(LWF),Semi-deciduous Forest(SDF). And secondary forest types: Late Secondary Forest (LSF), Intermediate Secondary Forest (ISF) and Early Secondary Forest (ESF). Different letters indicate significant differences between forest types (Tukey test; P < 0.05).

    Our carbon values are far higher than those used by the Intergovernmental Panel on Climate Change(IPCC;50%)to assess carbon stocks in vegetation(AGC) worldwide, suggesting that the current potential of seasonally dry tropical regions to provide the ecosystem service of carbon fixation in aboveground biomass is greatly undervalued. Recent assessments of AGC based on remote sensing estimates of vegetation biomass(Avitabile et al.,2016;Baccini et al., 2017) do not directly measure the carbon content of the different plant species, but rather indirectly estimate biomass(based on tree height,not basal area)and apply the factor recommended by the IPCC to estimate carbon content per unit of biomass.This vastly undervalues the true carbon content of the tropical dry forests of Veracruz, and possibly that of other ecosystems not revealed by coarse scale maps.While the rapid assessment of ecosystem services in tropical landscapes that takes into account the high rate of deforestation is an urgent task, it is also necessary to develop feasible methods to incorporate: i) remote sensing estimates of basal area (e.g.,LiDAR), ii) existing baseline information (e.g., national forest inventories),and iii)datasets of carbon density for the dominant species of different ecosystems. As our results show, it is also critical to include more tree species in the carbon density datasets,since there is such high variability across species, particularly for highly diverse tropical forests and their secondary vegetation. It has been proposed that species richness could be used to predict certain ecosystem services such as carbon sequestration(Midgley,2012;Arasa-Gisbert et al.,2018),but for tropical forests there is evidence that the predictive power of this variable is too low to obtain reliable data(Arasa-Gisbert et al.,2018).Our study provides a clear example of the disconnect between species richness and carbon storage potential;specifically,the results of the tropical oak forest where almost 90% of its basal area comes from only three tree species,which all have a relatively high capacity to fix carbon in their wood.This refutes the findings of Arasa-Gisbert et al.(2018)in a similar ecosystem in Mexico.

    While the relationship between aboveground carbon stocks and soil variables was found to be weak in other seasonally dry tropical regions of Mexico(Jaramillo et al.,2003;Corona-Nú~nez et al.,2018;Gavito et al.,2018), our results show that the carbon stored in the aboveground biomass is strongly related to edaphological variables, mainly soil organic carbon and organic matter,as well as with the proportion of sand and clay, for which weaker relationships were detected. Some authors have reported a relationship between edaphological variables and the functional attributes of plants in dry forests,such as the carbon content of the leaves, stomatal conductivity, photosynthetic rates and biomass increase(Chaturvedi et al.,2011,2018),which are related to the capacity of trees to fix carbon in their tissues.Additionally,and specifically in the case of clay and sand content, these variables directly influence the soil water retention capacity, since a higher sand content increases soil permeability and quick water loss,while a higher clay content increases water retention, retaining moisture for longer periods of time (Powers and Per′ez-Aviles,2013).Variation in soil water retention is particularly important in seasonally dry tropical regions where water availability is extremely low or completely absent during the months-long dry season,and access to water by the roots is a key determinant in nutrient acquisition (e.g., carbon fixation) and wood growth (Becknell and Powers,2014;Corona-Nú~nez et al.,2018).The evidence for the mechanisms that explain the influence of edaphic attributes on the capacity of carbon storage in the aboveground biomass is scarce, indicating the need to carry out more in-depth studies.

    Fig.5. Significant relationships (i.e.,R2>15%)between aboveground carbon stock per forest patch(t C?ha-1)and environmental variables:(a)soil organic carbon(%), (b) soil organic matter (%), (c) soil clay (%) and (d) soil sand (%) content for the patches (N =29) sampled in the seasonally dry tropical region of the Gulf of Mexico.

    Fig. 6. Significant relationships between soil organic carbon stock (t C?ha-1)and environmental variables: (a) soil organic matter (%), (b) maximum annual precipitation (mm) and (c) plant abundance (number of stems) for the forested patches sampled in the seasonally dry tropical region of the Gulf of Mexico.Precipitation data is from Cuervo-Robayo et al. (2014).

    4.2. Soil organic carbon storage

    It has been reported that the conversion of natural vegetation cover into different types of land use does not have particularly strong consequences for soil organic carbon stocks, and even that while the conversion of a forest into a pasture reduces the amount of nitrogen in the soil,it does not reduce its carbon content (Cairns et al., 2000; Jaramillo et al.,2003; Ibrahim et al., 2006). However, on average the old-growth forest types in the region we studied have a higher soil organic carbon stock than secondary forest patches of different successional stages do,providing evidence that past changes in land use result in degraded soils by diminishing nutrients stocks,including those of carbon(Becknell and Powers,2014;Gavito et al.,2018). Still,despite the high rates of deforestation in the study area,the soils of this landscape have a high capacity for recovery after the agricultural disturbance stops and secondary succession progresses,as shown by some of the patches of secondary forest whose soil carbon content was as high as that of old-growth forest patches.

    Tropical oak forest (TOF)had the highest soil carbon content,likely due to the fact that these patches have remained relatively undisturbed in their forest structure and species composition over the past few centuries(Mesa-Sierra et al.,2020a).The rough,extremely poor soils of this forest type are not suitable for agricultural activities,and thus soil degradation has been prevented. This forest type is regarded as a Pleistocene relic(Arriaga et al., 2000), where it is possible to find species that are not distributed in any other zone of the tropical dry region of the Gulf of Mexico(e.g.,Quercus sapotifolia).Today,tropical oak forest is one of the most threatened vegetation types in the region due to open-pit mining projects focused on precious metals located directly underneath the remaining patches of this forest type (Laborde, 2018). However, this study demonstrates that in addition to its relevance as a biodiversity refuge(e.g.,millennial-old cycads),TOF also has a great deal of potential to provide ecosystem services, including the highest carbon stocks per unit area within the region studied.

    Soil organic matter is directly related to vegetation structure (especially the number of woody plants) and species composition, whose spatial variation has explicit effects on leaf litter production,and rates of organic matter decomposition and nutrient exchange (Jaramillo et al.,2003;Gavito et al.,2018).However,our results in this respect,as well as the weak relationship between aboveground and soil organic carbon stocks, demonstrate the need for further edaphological analyses in the seasonally dry tropical region of the Gulf of Mexico; particularly to increase our understanding of how the spatial variation in species composition and edaphic properties influence soil carbon stocks,regardless of the amount of organic matter in the soil.This would allow us to generate a database of the most desirable tree species for assisted restoration projects and to enrich vegetation patches during secondary succession,and to more quickly and completely recover forest attributes in terms of the edaphological processes (e.g., carbon cycle) and soil nutrients,not only at the local patch level,but also for the whole anthropic landscape.

    4.3. Forest resilience

    Regardless of the structural similarities among the old-growth and secondary forest patches, particularly in terms of tree size distribution,the basal area of secondary forest types was lower than that of two of the old-growth forest types: the tropical oak forest (TOF) and the semideciduous forest (SDF), though it was similar to or even greater than that of the low-statured deciduous forest (LWF). These structural differences have usually been attributed to differences in stand age (Hern′andez-Stefanoni et al., 2011; Dupuy et al., 2012; Becknell and Powers,2014; Poorter et al., 2016), which can be the direct result of chronic human disturbance, natural disturbances (e.g., hurricanes) or both.However, large trees (DBH ≥60 cm) were recorded in patches of early secondary forest (ESF), whose presence during the early stages of secondary succession is explained by specific tree management practices along with agricultural uses of the plot. For example, leaving large canopy trees in the middle of pastures during forest clearing provides shade for cattle,or along rivers that cross properties protects the riverbanks,or by directly planting trees as living fence posts. These large trees that remain within farmers’ plots improve the heterogeneity and quality of the agricultural matrix,as well as landscape connectivity(Guevara et al.,1998; Arroyo-Rodríguez et al., 2020), and they also increase the basal area of regenerating secondary vegetation during the fallow period after plot abandonment. These forest patches have a profuse, dense advance regeneration,i.e.,plenty of juvenile trees,to maintain forest regeneration(Chazdon et al.,2007;Hern′andez-Stefanoni et al.,2011;Mesa-Sierra and Laborde,2017;Corona-Nú~nez et al.,2018).

    These attributes of secondary forest patches can be interpreted as indirect evidence of resilience (Mesa-Sierra et al., 2020b), at least in forest physiognomy, which is explained not only by the distribution of tree sizes but also by the spatial and temporal turnover of the species that dominate the biomass of the different successional stages. Vachellia pennatula,for example,is dominant in the early stages of succession(i.e.,ESF),but declines over time and is replaced by later stage species such as Gliricidia sepium or Guazuma ulmifolia, having facilitated more suitable microclimatic conditions for the arrival of those later species. Similar successional trends have been reported for other seasonally dry regions within the Neotropics,where resilience is also represented by changes in the species that dominate the biomass through succession (Kalacska et al.,2004;Powers et al.,2009;Griscom,2020).Such resilience confers ecological stability and the long-term maintenance of other ecosystem services in addition to carbon sequestration, particularly those that are directly related to forest biomass,such as the availability of high-quality habitat for forest fauna, efficient nutrient fixation and cycling, and the mitigation of natural disturbances (e.g., hurricanes), among others(Balderas Torres and Lovett, 2013; Becknell and Powers, 2014; Poorter et al., 2016; Prado-Junior et al., 2016). This resilience is of vital importance,considering the global crisis of forest ecosystems(i.e.,high rates of deforestation) and their capacity to regulate climate (Anderegg et al.,2020),making these tropical dry forests a high priority for carbon offset projects.

    4.4. Landscape management implications

    At first sight from a satellite image (e.g., Google Earth) our study region seems to be devastated and devoid of its original forest cover.However, on closer inspection as in our study, we can appreciate that numerous small forest patches are still present in this landscape,and that they also have a notable richness of forest plants and contribute substantially to carbon sequestration.

    We are aware that our methods underestimate carbon stocks because we were unable to take into account every stem in our transects.This was related to constraints in available funding and time for field sampling,but also because it was not possible to carry out the extraction and analysis of samples for all the species detected.While we only obtained carbon sequestration data for 29 of the 157 species present in the study area,the data obtained clearly indicates that this vegetation is making a substantial contribution. However, the procedure we followed allowed us to compare not only the six different vegetation types present in our study site,but also the spatial variability among the 29 patches sampled in a systematic way,based on the dominant species of the region.

    Quantifying both the aboveground and also the soil organic carbon stocks is essential to recognizing the full conservation value of the remnant patches of native vegetation that are still present in humanmodified landscapes but rarely taken into account in GIS analyses. In the seasonally dry tropical region of the Gulf of Mexico,despite the great impact of human activities,there is an important pool of tree species that seem to maintain landscape functionality,providing essential ecosystem services such as carbon sequestration, and that ensure the capacity of soils to perform critical processes such as nutrient and carbon cycling.In the secondary forests of different ages that we sampled (LSF, ISF, ESF),successional turnover results in successive floristic transitions that contribute to increasingly higher values of AGC stocks,if allowed to grow undisturbed. Thus, in order to enrich a plot of land after agricultural disturbance,our results suggest that the best trees to reintroduce would be secondary species of the Fabaceae family (formerly Leguminosae)such as Vachellia pennatula,Gliricidia sepium and Leucaena leucocephala,or other species with high growth rates and carbon storage potential such as

    Bursera simaruba and Cedrela odorata.

    These species would rapidly regenerate biomass and modify biotic and abiotic conditions, promoting the arrival and growth of the shadetolerant species typical of old-growth forest. Fabaceae species have a high carbon content and fast rates of wood growth,and are able to attain high densities in patches of secondary forest.They are also recognized for their ability to restore biogeochemical cycles in the soil,such as nitrogen fixation (Gavito et al., 2018; Bakhoum et al., 2018; Castellanos Barliza et al.,2019).Even though in this region there was no evidence of a direct relationship between aboveground and soil organic carbon stocks,it has been proposed that these tree species are able to promote an increase in soil carbon stocks (Castellanos Barliza et al., 2018; Gavito et al., 2018).More research is needed to determine the best management practices to enhance the carbon stocks of the region and similar landscapes, and to improve our understanding of how biogeochemical processes and nutrient distribution are related to the environmental variables that are vulnerable to climate change.

    5. Conclusions

    Our results reveal that patches of remnant old-growth and secondary forest together and under appropriate conservation and management actions, can make a substantial contribution to meeting climate mitigation objectives through their carbon stocks. This may help set priorities for land-use planning and in the development of programs for landscape restoration at the national scale, with the aim of achieving the international goals of increasing forest cover and carbon stocks.Combining local information on biodiversity and organic carbon stocks to produce maps that are accurate at a finer resolution will enable governments and other stakeholders to geospatially identify where different management actions can help them to meet their conservation and restoration objectives,as well as understand how local and national actions contribute to global goals.

    Funding

    This study was funded by The Rufford Foundation (Rufford small grant #206761, to N.M.-S.); the Instituto de Ecología, A. C. (project INECOL, 20030–10281, to J.L.); and the Consejo Nacional de Ciencia y Tecnología(CONACYT,Scholarship#263474,to N.M.-S.).

    Availability of data and material

    All the data generated or analyzed during this study are included in this published article and its supplementary information files.

    Authors’ contributions

    N.M.-S.,J.L.,R.C-K.,and F.E.conceived the ideas and hypotheses,and designed the study.N.M.-S.collected data.N.M.-S.,J.L.,R.C.-K.,and F.E.ran the statistical analyses and interpreted the results. N.M.-S. coordinated the writing of the manuscript. All the authors substantially contributed to the manuscript and agreed with the final version for submission.

    Ethics approval and consent to participate

    Not applicable.

    Consent for publication

    Not applicable.

    Declaration of competing interest

    The authors declare that they have no competing interests.

    Acknowledgments

    We are grateful to Victor V′azquez, No′e Cardona, Miguel Ramirez,Evodio Martínez, Tom′as Higueredo, and Enrique Romero for their help during field work and to those in charge of the Amelco UMA. Ren′e Altamirano,No′e Cardona,and the Higueredo Family generously granted us permission to work on their properties, and Ariadna Martínez Viru′es provided expert advice on the methods for estimating carbon content of wood.We thank Bianca Delfosse her editorial work on the final English version of the manuscript.

    Appendix A. Supplementary data

    Supplementary data to this article can be found online at https://do i.org/10.1016/j.fecs.2022.100016.

    av福利片在线| 叶爱在线成人免费视频播放| 人人妻,人人澡人人爽秒播| 亚洲专区中文字幕在线| av天堂在线播放| 日韩精品免费视频一区二区三区| 国产欧美日韩精品亚洲av| 18禁国产床啪视频网站| 国产精品免费一区二区三区在线 | 黄色a级毛片大全视频| 久久久久国产一级毛片高清牌| 欧美另类亚洲清纯唯美| 国产精品久久视频播放| 满18在线观看网站| 欧美亚洲 丝袜 人妻 在线| 日本一区二区免费在线视频| 亚洲综合色网址| 精品欧美一区二区三区在线| 男女高潮啪啪啪动态图| 日日摸夜夜添夜夜添小说| 日日摸夜夜添夜夜添小说| 国产精品二区激情视频| 99re6热这里在线精品视频| 亚洲第一青青草原| 老熟妇乱子伦视频在线观看| 国产99白浆流出| 免费看a级黄色片| avwww免费| 亚洲成人国产一区在线观看| 一个人免费在线观看的高清视频| 免费看十八禁软件| 精品久久久久久电影网| 国产单亲对白刺激| www.熟女人妻精品国产| 人人澡人人妻人| 无限看片的www在线观看| av天堂在线播放| 色94色欧美一区二区| 欧美人与性动交α欧美精品济南到| 黑人欧美特级aaaaaa片| 亚洲精品中文字幕在线视频| 黄色视频不卡| 国产国语露脸激情在线看| 欧美最黄视频在线播放免费 | 午夜91福利影院| 成人国产一区最新在线观看| 老汉色av国产亚洲站长工具| 精品国产一区二区三区久久久樱花| 老汉色∧v一级毛片| 日韩中文字幕欧美一区二区| 婷婷精品国产亚洲av在线 | 又大又爽又粗| 午夜精品在线福利| 亚洲第一欧美日韩一区二区三区| 国产激情欧美一区二区| 老司机在亚洲福利影院| 免费在线观看影片大全网站| 天天躁狠狠躁夜夜躁狠狠躁| 久久国产乱子伦精品免费另类| 精品国产一区二区三区四区第35| a级片在线免费高清观看视频| 美女高潮到喷水免费观看| 露出奶头的视频| 久久天躁狠狠躁夜夜2o2o| 无人区码免费观看不卡| 欧美精品av麻豆av| xxxhd国产人妻xxx| 99久久99久久久精品蜜桃| 岛国在线观看网站| 身体一侧抽搐| 国产亚洲欧美在线一区二区| 十分钟在线观看高清视频www| 欧美乱码精品一区二区三区| 成年动漫av网址| 啪啪无遮挡十八禁网站| 国产精品一区二区在线不卡| 亚洲三区欧美一区| 精品乱码久久久久久99久播| 亚洲人成电影免费在线| 无限看片的www在线观看| 国产成人系列免费观看| 亚洲精品中文字幕一二三四区| 大码成人一级视频| 曰老女人黄片| 日韩欧美三级三区| 免费观看a级毛片全部| 啦啦啦视频在线资源免费观看| 天天躁夜夜躁狠狠躁躁| 91成年电影在线观看| e午夜精品久久久久久久| 成人永久免费在线观看视频| 一区二区日韩欧美中文字幕| tocl精华| 亚洲av片天天在线观看| 搡老岳熟女国产| 黄频高清免费视频| 电影成人av| 日韩精品免费视频一区二区三区| 美女高潮喷水抽搐中文字幕| 黄频高清免费视频| 香蕉国产在线看| 男女高潮啪啪啪动态图| 国产在视频线精品| 美女视频免费永久观看网站| 精品人妻1区二区| 他把我摸到了高潮在线观看| 一二三四社区在线视频社区8| 久久亚洲真实| 欧洲精品卡2卡3卡4卡5卡区| 女性被躁到高潮视频| 国产男靠女视频免费网站| 国产成人精品在线电影| 国产精品久久久久久人妻精品电影| 一进一出抽搐动态| 两个人看的免费小视频| 91精品国产国语对白视频| 嫁个100分男人电影在线观看| 久久久国产成人免费| 老司机午夜十八禁免费视频| 欧美另类亚洲清纯唯美| 成人精品一区二区免费| 在线十欧美十亚洲十日本专区| 12—13女人毛片做爰片一| 五月开心婷婷网| e午夜精品久久久久久久| 女人爽到高潮嗷嗷叫在线视频| 丁香欧美五月| 嫁个100分男人电影在线观看| 亚洲在线自拍视频| 国产男靠女视频免费网站| 高清黄色对白视频在线免费看| av一本久久久久| 精品一区二区三区视频在线观看免费 | 日本撒尿小便嘘嘘汇集6| 欧美乱色亚洲激情| 搡老岳熟女国产| 久久天躁狠狠躁夜夜2o2o| 人人妻人人添人人爽欧美一区卜| 新久久久久国产一级毛片| 久久精品国产亚洲av高清一级| 午夜成年电影在线免费观看| 纯流量卡能插随身wifi吗| 国产av精品麻豆| 成熟少妇高潮喷水视频| 亚洲国产欧美日韩在线播放| 精品国产乱码久久久久久男人| 亚洲国产中文字幕在线视频| 国产亚洲一区二区精品| 亚洲九九香蕉| 国产精品欧美亚洲77777| 激情视频va一区二区三区| 大香蕉久久网| 欧美国产精品一级二级三级| 国产99白浆流出| 国产一区二区三区在线臀色熟女 | 国产成+人综合+亚洲专区| 国产不卡一卡二| 桃红色精品国产亚洲av| 中文字幕精品免费在线观看视频| 国产免费av片在线观看野外av| 亚洲色图 男人天堂 中文字幕| 久久 成人 亚洲| 亚洲欧美色中文字幕在线| 又大又爽又粗| 无限看片的www在线观看| 黄色女人牲交| 性少妇av在线| 一边摸一边抽搐一进一出视频| 欧美激情 高清一区二区三区| 99热国产这里只有精品6| 国产精品乱码一区二三区的特点 | 国产男靠女视频免费网站| 免费人成视频x8x8入口观看| 99精品在免费线老司机午夜| 国产不卡一卡二| 91国产中文字幕| 亚洲国产欧美网| 日韩精品免费视频一区二区三区| 国产国语露脸激情在线看| 欧美精品啪啪一区二区三区| 在线天堂中文资源库| 久久精品国产99精品国产亚洲性色 | 亚洲av日韩在线播放| 久久影院123| 自线自在国产av| 欧美在线一区亚洲| 精品高清国产在线一区| 午夜福利乱码中文字幕| 免费观看a级毛片全部| 亚洲一区二区三区不卡视频| 午夜福利,免费看| 人人妻人人澡人人看| 亚洲国产欧美网| 女人高潮潮喷娇喘18禁视频| 黄色女人牲交| 亚洲欧美日韩另类电影网站| 天天影视国产精品| 天堂中文最新版在线下载| 国产精品亚洲av一区麻豆| 亚洲一区二区三区不卡视频| 精品一区二区三区视频在线观看免费 | 亚洲国产欧美一区二区综合| 久久精品国产99精品国产亚洲性色 | 一边摸一边做爽爽视频免费| 久久狼人影院| 免费观看a级毛片全部| 欧美 亚洲 国产 日韩一| 亚洲男人天堂网一区| 日本vs欧美在线观看视频| 美女国产高潮福利片在线看| 国产三级黄色录像| 国产日韩一区二区三区精品不卡| 国产一区在线观看成人免费| 99久久国产精品久久久| 妹子高潮喷水视频| 母亲3免费完整高清在线观看| 久久青草综合色| 99re在线观看精品视频| 极品人妻少妇av视频| 色婷婷久久久亚洲欧美| 欧美激情极品国产一区二区三区| 欧美精品av麻豆av| 亚洲国产毛片av蜜桃av| 日韩有码中文字幕| 建设人人有责人人尽责人人享有的| 俄罗斯特黄特色一大片| 欧美大码av| 精品亚洲成a人片在线观看| 最新的欧美精品一区二区| 9191精品国产免费久久| 天堂√8在线中文| 色综合欧美亚洲国产小说| 女人被躁到高潮嗷嗷叫费观| 亚洲一区二区三区欧美精品| 中文字幕精品免费在线观看视频| 视频区欧美日本亚洲| av一本久久久久| 免费看a级黄色片| 国产精品成人在线| 欧美精品啪啪一区二区三区| 国产av精品麻豆| 国产精品一区二区免费欧美| 日韩精品免费视频一区二区三区| 很黄的视频免费| 日韩中文字幕欧美一区二区| 电影成人av| 黑人操中国人逼视频| 久久中文看片网| 狂野欧美激情性xxxx| 亚洲国产欧美日韩在线播放| 国产精品久久视频播放| 色老头精品视频在线观看| 黄色怎么调成土黄色| 欧美在线黄色| 在线av久久热| 国产深夜福利视频在线观看| 久久香蕉激情| 国产99白浆流出| 高清黄色对白视频在线免费看| 日日爽夜夜爽网站| 99国产精品免费福利视频| 欧美日韩亚洲国产一区二区在线观看 | 久久亚洲精品不卡| 久久精品国产99精品国产亚洲性色 | 亚洲人成电影免费在线| 激情视频va一区二区三区| 久久99一区二区三区| 亚洲中文日韩欧美视频| 亚洲熟妇中文字幕五十中出 | 757午夜福利合集在线观看| 亚洲男人天堂网一区| 校园春色视频在线观看| 搡老岳熟女国产| 99久久国产精品久久久| 欧美 日韩 精品 国产| 色精品久久人妻99蜜桃| 手机成人av网站| 国产av精品麻豆| 精品国内亚洲2022精品成人 | 国产97色在线日韩免费| 久久精品国产a三级三级三级| 大香蕉久久成人网| 亚洲欧美日韩另类电影网站| 老鸭窝网址在线观看| 丝袜美足系列| 国产午夜精品久久久久久| 伦理电影免费视频| 国产av一区二区精品久久| 亚洲免费av在线视频| 午夜视频精品福利| 久9热在线精品视频| 亚洲五月色婷婷综合| 叶爱在线成人免费视频播放| 黑人操中国人逼视频| 久久久水蜜桃国产精品网| 国产成人啪精品午夜网站| 午夜影院日韩av| 国产av又大| 国产精品98久久久久久宅男小说| 男女下面插进去视频免费观看| 久久精品国产综合久久久| 精品人妻熟女毛片av久久网站| √禁漫天堂资源中文www| 国产在线观看jvid| 欧美丝袜亚洲另类 | 看片在线看免费视频| 在线免费观看的www视频| 高清av免费在线| av天堂在线播放| 欧美日韩福利视频一区二区| 成人av一区二区三区在线看| 亚洲色图 男人天堂 中文字幕| 日韩免费高清中文字幕av| 涩涩av久久男人的天堂| 少妇 在线观看| 高清视频免费观看一区二区| 男人操女人黄网站| 黄片播放在线免费| 国产成人欧美| 久久中文字幕一级| 欧美中文综合在线视频| 亚洲国产精品sss在线观看 | 18禁黄网站禁片午夜丰满| 动漫黄色视频在线观看| 国产精品av久久久久免费| 亚洲成国产人片在线观看| 成人国语在线视频| 激情在线观看视频在线高清 | 成人三级做爰电影| 国产精品久久久久久精品古装| 老司机影院毛片| 久久草成人影院| 十八禁高潮呻吟视频| 18禁黄网站禁片午夜丰满| 美女视频免费永久观看网站| 69精品国产乱码久久久| 久久久久久久国产电影| 一进一出抽搐动态| 丝瓜视频免费看黄片| 亚洲人成电影免费在线| 大型黄色视频在线免费观看| 国产欧美日韩综合在线一区二区| 日韩免费av在线播放| 一区在线观看完整版| 动漫黄色视频在线观看| tocl精华| 国产欧美日韩一区二区三区在线| 国产国语露脸激情在线看| 午夜视频精品福利| 黄色片一级片一级黄色片| 黄色 视频免费看| 成年人黄色毛片网站| 一区二区三区激情视频| 成年人黄色毛片网站| 久久久精品区二区三区| 如日韩欧美国产精品一区二区三区| 久久国产精品影院| 欧美亚洲 丝袜 人妻 在线| 麻豆成人av在线观看| 色精品久久人妻99蜜桃| 久久香蕉精品热| 电影成人av| 亚洲色图av天堂| 欧美在线一区亚洲| 久久国产精品影院| 国产精品偷伦视频观看了| 黄网站色视频无遮挡免费观看| 色精品久久人妻99蜜桃| 成人特级黄色片久久久久久久| 国产成人影院久久av| 亚洲五月色婷婷综合| 1024视频免费在线观看| 午夜两性在线视频| 亚洲熟女精品中文字幕| 少妇粗大呻吟视频| 国产精品美女特级片免费视频播放器 | 婷婷丁香在线五月| 精品视频人人做人人爽| 亚洲精品国产色婷婷电影| 国产av一区二区精品久久| 国内久久婷婷六月综合欲色啪| 欧美黑人精品巨大| 91大片在线观看| 热99久久久久精品小说推荐| 最近最新中文字幕大全电影3 | 很黄的视频免费| av天堂在线播放| 两人在一起打扑克的视频| 午夜视频精品福利| 久久精品成人免费网站| 美国免费a级毛片| av有码第一页| 一个人免费在线观看的高清视频| 777米奇影视久久| 在线观看www视频免费| 久久久久久久精品吃奶| 高清欧美精品videossex| 国产一区二区三区在线臀色熟女 | 国产aⅴ精品一区二区三区波| 免费少妇av软件| 99精品久久久久人妻精品| 久久国产精品影院| 黄频高清免费视频| 亚洲午夜理论影院| 岛国毛片在线播放| 人人妻人人添人人爽欧美一区卜| 熟女少妇亚洲综合色aaa.| 欧美 日韩 精品 国产| 黄频高清免费视频| 精品国产国语对白av| 国产一区二区激情短视频| 久久人人爽av亚洲精品天堂| 他把我摸到了高潮在线观看| 丰满人妻熟妇乱又伦精品不卡| 亚洲片人在线观看| 麻豆国产av国片精品| 欧美成人午夜精品| 亚洲黑人精品在线| 久久精品亚洲熟妇少妇任你| 日本a在线网址| 欧美人与性动交α欧美软件| 亚洲九九香蕉| 一级毛片精品| 国产免费av片在线观看野外av| 亚洲精品乱久久久久久| 12—13女人毛片做爰片一| a在线观看视频网站| a级毛片黄视频| 免费高清在线观看日韩| 国精品久久久久久国模美| 国产精品久久久人人做人人爽| 久久久国产成人精品二区 | 国产野战对白在线观看| 中文字幕人妻熟女乱码| 久久香蕉精品热| 亚洲精华国产精华精| 99国产精品一区二区三区| 国产伦人伦偷精品视频| 精品久久久精品久久久| 99在线人妻在线中文字幕 | 欧美日韩亚洲综合一区二区三区_| 不卡av一区二区三区| 啪啪无遮挡十八禁网站| 999久久久精品免费观看国产| 国产色视频综合| 18禁观看日本| 国产单亲对白刺激| 精品国产美女av久久久久小说| 18在线观看网站| 午夜两性在线视频| 国产精品美女特级片免费视频播放器 | 可以免费在线观看a视频的电影网站| 国产不卡一卡二| 搡老乐熟女国产| 成年人免费黄色播放视频| 韩国av一区二区三区四区| 日韩欧美免费精品| 国产成人精品久久二区二区免费| 在线天堂中文资源库| 国产伦人伦偷精品视频| www.熟女人妻精品国产| 国产一区在线观看成人免费| 无人区码免费观看不卡| 中文亚洲av片在线观看爽 | 法律面前人人平等表现在哪些方面| 久久久久久人人人人人| 中国美女看黄片| 啦啦啦视频在线资源免费观看| 日韩欧美一区二区三区在线观看 | 又黄又粗又硬又大视频| 深夜精品福利| 欧美黄色淫秽网站| av线在线观看网站| 久9热在线精品视频| 亚洲精品在线美女| 少妇裸体淫交视频免费看高清 | 在线观看免费视频网站a站| 成年女人毛片免费观看观看9 | 午夜亚洲福利在线播放| 欧美日韩国产mv在线观看视频| 五月开心婷婷网| 99精品在免费线老司机午夜| 亚洲美女黄片视频| 1024香蕉在线观看| 久久久久国产一级毛片高清牌| 丝瓜视频免费看黄片| 精品一区二区三区四区五区乱码| 久久久久久人人人人人| 亚洲一卡2卡3卡4卡5卡精品中文| 久久久精品区二区三区| 丝袜人妻中文字幕| 亚洲精品成人av观看孕妇| a在线观看视频网站| 一区二区三区激情视频| 大香蕉久久成人网| 久久久久久免费高清国产稀缺| 中亚洲国语对白在线视频| 曰老女人黄片| 69av精品久久久久久| 欧美不卡视频在线免费观看 | 欧美国产精品va在线观看不卡| 捣出白浆h1v1| 人妻丰满熟妇av一区二区三区 | 波多野结衣一区麻豆| 日本黄色视频三级网站网址 | 女同久久另类99精品国产91| 中亚洲国语对白在线视频| 777久久人妻少妇嫩草av网站| 啪啪无遮挡十八禁网站| 老熟妇乱子伦视频在线观看| 亚洲av第一区精品v没综合| a级毛片黄视频| 男人操女人黄网站| 丁香欧美五月| 高潮久久久久久久久久久不卡| 精品国产乱码久久久久久男人| 国产精品亚洲一级av第二区| aaaaa片日本免费| 少妇被粗大的猛进出69影院| 精品国产乱子伦一区二区三区| 丝袜美腿诱惑在线| 午夜两性在线视频| e午夜精品久久久久久久| 国产精品久久久人人做人人爽| 99国产精品99久久久久| 母亲3免费完整高清在线观看| 中文字幕制服av| 一级片'在线观看视频| 国产欧美日韩精品亚洲av| 两性午夜刺激爽爽歪歪视频在线观看 | 国产有黄有色有爽视频| 亚洲三区欧美一区| 亚洲免费av在线视频| a级片在线免费高清观看视频| 韩国av一区二区三区四区| 18在线观看网站| 亚洲少妇的诱惑av| 成人18禁高潮啪啪吃奶动态图| 亚洲av日韩精品久久久久久密| 水蜜桃什么品种好| 国产麻豆69| 国产亚洲精品第一综合不卡| 9色porny在线观看| 一夜夜www| 999精品在线视频| 精品欧美一区二区三区在线| 欧美日本中文国产一区发布| 亚洲午夜精品一区,二区,三区| 欧美日韩福利视频一区二区| 亚洲片人在线观看| 热re99久久国产66热| 久久精品成人免费网站| 极品少妇高潮喷水抽搐| 黑人欧美特级aaaaaa片| 精品免费久久久久久久清纯 | 国产精品亚洲av一区麻豆| 人人妻人人爽人人添夜夜欢视频| 两性午夜刺激爽爽歪歪视频在线观看 | 国产成人欧美在线观看 | 在线观看舔阴道视频| 在线观看午夜福利视频| 亚洲美女黄片视频| 国产aⅴ精品一区二区三区波| 国产有黄有色有爽视频| 欧美日韩黄片免| 亚洲综合色网址| 成年人免费黄色播放视频| 下体分泌物呈黄色| 精品无人区乱码1区二区| 他把我摸到了高潮在线观看| 欧美乱码精品一区二区三区| a在线观看视频网站| tube8黄色片| 国产99久久九九免费精品| 国产精品自产拍在线观看55亚洲 | 香蕉丝袜av| 不卡av一区二区三区| 99国产精品一区二区蜜桃av | 亚洲一码二码三码区别大吗| 搡老熟女国产l中国老女人| 亚洲av熟女| 国产亚洲精品久久久久久毛片 | 成人av一区二区三区在线看| 久久这里只有精品19| 在线观看一区二区三区激情| 日韩欧美在线二视频 | 精品久久久久久久久久免费视频 | 亚洲一码二码三码区别大吗| 男人舔女人的私密视频| 高清在线国产一区| 久久中文字幕一级| 每晚都被弄得嗷嗷叫到高潮| √禁漫天堂资源中文www| 久久国产精品大桥未久av| 亚洲精品在线美女| 高清av免费在线| 精品久久久久久久毛片微露脸| 中文亚洲av片在线观看爽 | 欧美黄色片欧美黄色片| 国产精品乱码一区二三区的特点 | 国产精品久久视频播放| 精品亚洲成国产av| 99精品在免费线老司机午夜| 1024视频免费在线观看| 在线视频色国产色| 国产成人免费无遮挡视频| av超薄肉色丝袜交足视频| 精品亚洲成a人片在线观看| 免费观看精品视频网站| av超薄肉色丝袜交足视频| 村上凉子中文字幕在线| 欧美久久黑人一区二区| 一夜夜www| 丝瓜视频免费看黄片| 人人澡人人妻人|